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Minimax

246 items · started 2025-10-30 · ongoing (last activity 2026-09-18)

  1. HyperFlow for MiniMax-H3 HyperFlow is Video Rebirth's 8-step LoRA for MiniMax-H3, obtained by data-free flow self-distillation and running on the official diffusers Modular Pipeline. Diffusers' default 50-point sigma schedule performs 49 m…

  2. We study smooth strongly convex--strongly concave minimax optimization with general nonlinear coupling in the deterministic unconstrained setting. We propose a pure single-loop damped extragradient method with fixed parameters and two new…

  3. We study repeated contract design when a principal observes outcomes but not the actions that generate them. The principal may use any bounded outcome-contingent payment vector, and the agent's best response can make expected profit discon…

  4. We introduce a new single-loop algorithmic framework for smooth nonconvex--concave minimax optimization. The resulting projected damped extragradient method combines projected extragradient updates, dual momentum, and a moving proximal cen…

  5. In this paper, we present a Mixture-of-Experts (MoE) quantization method based on activation entropy. Although quantization reduces memory and computational costs, it can substantially degrade performance.

  6. VC-Attention: Faster Low-Bit Attention Without Retraining Attention speedup over BF16 FlashAttention-4 [1] on B200 and B300. We benchmark the attention workload in MiniMax-H3 when generating 243 frames at 1344×768.

  7. Awesome MiniMax H3 Max Prompts English · 简体中文 Learn MiniMax H3 Max through real public examples: watch a shot, read the breakdown, then copy a prompt to make your own version. Explore action, performance, animation, short stories, referenc…

  8. Measured GPU runs What rented GPUs actually cost per unit of work. Measured runs on rented GPUs: what each provider actually charged, and the cost per finished unit of work — a video clip, an image, a thousand training steps, a million tex…

  9. This study investigates the use of stochastic gradient descent (SGD) to learn operators between general Hilbert spaces. We study weak and strong regularity conditions for the target operator that characterize its structure and complexity.

  10. We study a class of distributionally robust optimization (DRO) problems for the statistical risk problem, formulated as minimax problems over the product of a Euclidean space and a Riemannian manifold. Because the resulting minimax landsca…

  11. We study stochastic linear contextual bandits with arbitrary action menus that may depend on the fixed parameter and the interaction history. We establish matching upper and lower bounds, up to logarithmic factors.

  12. Sol-H3- Spark Accelerating MiniMax-H3 768p Video Generation on a Single NVIDIA DGX Spark in 1 Minute NVIDIA Research, Efficient AI Team & Singapore Lab. A two-stage pipeline specialized for a single NVIDIA DGX Spark generates a 384p draft…

  13. I bought a Fable dataset from one of the top Chinese LLM routers yesterday. With just 6TB data, I can take over 7 Chinese/CIS gov entities & 19 top Chinese firms like Xiaomi, Huawei, NIO, Minimax using SSH keys, VPN configs, Aliyun key…

  14. Estimating a low-dimensional subspace shared across noisy data matrices is a fundamental problem in multi-view matrix estimation. We study this problem under the two-view JIVE model, where each data matrix contains shared and view-specific…

  15. We study distributed one-dimensional mean estimation under a 1-bit communication constraint. Each agent observes one sample, drawn independently from an unknown distribution, and returns a single bit in response to a query $Q: \mathbb{R}\t…

  16. We characterize the sharp structure-agnostic minimax risk for coefficient estimation in the partial linear model when the outcome and treatment nuisances are learned by two distinct black-box learners, which resolves the open problem in do…

  17. chess5.ai Human vs LLM · Five Games Pit yourself against GPT, Claude, Gemini, Grok, Muse Spark, Mistral, DeepSeek, Kimi, Qwen, GLM, or MiniMax across five classic boards. How it works - Human vs model, or model vs model — with spectating a…

  18. While diffusion-based methods have recently emerged as effective tools for probing the intrinsic geometry of high-dimensional data, their statistical difficulty remains largely unexplored. We study estimation of the finite-scale population…

  19. https://preview.redd.it/v6s6tqnkrlnh1.png?width=2487&format=png&auto=webp&s=cdfdf416dc46186aa6389cc0d9d4b1eddf049cb2 My Claude did this when I asked it to write me a prompt for Minimax H3.

  20. A performance with spatial sound Human movement · prop contact · working-room ambience Max H3 creator workspace MiniMax H3 Max delivers faster, more stable AI video generation with stronger prompt adherence. Turn text, key frames, or a ref…

  21. Tired of paying for Suno, I made this local desktop app for Windows and macOS to generate songs through MiniMax's hosted Music API (free for up to 3 songs/minute!). I wanted something tailor-made for a songwriter, so I implemented some QoL…

  22. Watermarking has been proposed as a way to identify synthetic samples in estimation settings where no metadata is available to distinguish them from real samples, but its precise effects remain unexplored. In the absence of a distinguishin…

  23. For finite-horizon tabular CVaR reinforcement learning, prior work proves a $\widetilde{O}(\tau^{-1}\sqrt{SAK})$ leading regret bound for arbitrary normalized return laws and the sharper $\widetilde{O}(\sqrt{SAK/\tau})$ rate under a densit…

  24. Small MCP experiment: I asked Claude to plan a low-cost 30-second vertical video without sending every shot to the most expensive model. It came back with five shots: - 20s total on LTX 2.3 Fast for the establishing, transition and cutaway…

  25. About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Test new features NFL Sunday Ticket © 2026 Google LLC

  26. Video generated faster than it plays. We serve MiniMax Fast H3 — the FastH3 VSA checkpoint distilled from MiniMax H3 — on eight H100s.

  27. Channel One | AI Interdimensional Cable (Original)

  28. Chat Directs the Show with Minimax H3 Max | Live AI Broadcast Experiment | Streaming just chatting for 113 viewers.

  29. We study online prediction for a specific finite-alphabet, exogenously driven source with infinite input memory. Independent Rademacher inputs $(Ut)$ are observed sequentially, and the next binary mark has logit $\sum{j=1}^{t}\thetajU{t+1-…

  30. Directed graph learning naturally leads to trainable nonsymmetric propagation operators with distinct right and left spectral structures. Building on the two-sided cone Rayleigh framework for generalized pencils \[ B_\theta-\lambda G, \] w…

  31. audio.cpp 0.7 is out :) This release adds a lot of new audio models and a new way to compare them locally. Audio.cpp is now at 62 model families and 85+ model variants.

  32. how many models are going by 3 rn like Gemini 3.7, qwen 3.8, minimax m3, kimi k3, hy3, deeseek v4 flash, glm 5.3. (not deepseek and glm but close enough)

  33. Functional data analysis is an important statistical field that treats data as random functions. In practice, the random functions are often not fully observed but instead measured at discrete times.

  34. In this paper, we study alternating regret in online convex optimization (OCO), motivated by the success of alternating learning dynamics in two-player games. Although previous works have shown that $o(\sqrt{T})$ alternating regret is achi…

  35. I personally stopped reading the launch table once GLM-5, MiniMax M2.5, and Gemini 3 Deep Think dropped in two days and all claimed the same coding, reasoning, and agent wins. They optimize different constraints.

  36. BREAKING: MiniMax H3 Max sets the new Pareto Frontier for video generation, nearly 50x faster than the base model. This model is post-trained by @fal on @MiniMax_AI H3, and it's in a league of its own: no other Image to Video model on the…

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  38. Nearest neighbor (NN) algorithms have been extensively used for missing data problems in recommender systems and sequential decision-making systems. Prior theoretical analysis has established favorable guarantees for NN when the underlying…

  39. MiniMax now lists H3 as available, with confirmed 4–15 second output, 768P and 2K options, and multimodal references. Generate on this site, or read our API guide for the workflow, supported formats, and site pricing.

  40. MiniMax H3 Super Acceleration fast draft generation and high-resolution refinement, powered by Sol Engine 6.85 s for a 5-second 768p video · 14.93 s for a 10-second video H3 Super Acceleration first uses H3 with a LoRA to generate a four-s…

  41. I installed an R9700 in my Strix Halo machine over the weekend, via Oculink, and so far it hasn't been life-changing. First I tried running the Unsloth Q4_K_XL quant of DSv4 Flash 0731, and that failed.

  42. Howdy folks, You might (or likely not) know me around here with shilling of Pi harness, and the use of Pi as productivity assistant and KB manager. Lately, I have also been telling anyone who listens to try Qwen 3.8 27B IQ3_K_XXS by Unslot…

  43. This is so stupid. I made a fake Zoom call with AI coworkers.

  44. For those that don't know, Minimax is increasing their rates and token plan costs by ~60%-65% on the 25th. This is pretty much the last chance to lock in at the current rates if you use minimax and haven't yet.

  45. Discrete diffusion models have demonstrated strong performance across a range of datasets, including natural language data and graph-structured data. Among many variants, score-entropy discrete diffusion (SEDD) has achieved particularly st…

  46. Does anyone have a first-hand experience with four Sparks cluster, and how much of an upgrade is it comparing to just two considering the available models? While there's plenty of noise for the smaller models (Qwen) and our older king Deep…

  47. I trained a instrumental game music generator. The 1.2B DiT was trained on 1 cloud H100 from scratch in 8 days; I used the VAE from Stable Audio 3.

  48. MiniMax M3 DeepSearchQA Skill Eval Evaluates minimax/minimax-m3 on google/deepsearchqa using a Pi agent, You.com MCP tools, and a research skill optimized for this harness, model, and tool surface. MiniMax M3 Medium Reasoning with the You.…

  49. VPIPE Lightweight local multimodal AI pipelines and custom Metal inference for Apple Silicon Macs. Multimodal graph: video, audio, images, text, and tool actions in one pipeline.

  50. We study finite-sample parameter estimation in logistic regression with Gaussian design, where the goal is to estimate $\mathbf{\theta}^\in \mathbb{R}^d$ with $R=\|\mathbf{\theta}^\|2\ge 1$ from i.i.d. samples $\{(\mathbf{x}i,yi)\}{i=1}^n,…

  51. We study how many observations are needed to determine the causal direction between two linearly related variables. Classical LiNGAM theory shows that independent non-Gaussian disturbances identify the direction, but does not quantify the…

  52. We solve exactly a fundamental problem of adaptive control against adversarial disturbances: regulate the scalar system $x{t+1} = axt + ut + wt$, $x0=0$, $\|w\|\infty \le 1$, where the constant pole $a \in [-\Delta, \Delta]$ is unknown in…

  53. Estimating covariance matrices is fundamental to a wide range of statistical applications. This paper studies minimax and adaptive estimation of high-dimensional covariance matrices under $\rho$-zero-concentrated differential privacy ($\rh…

  54. We introduce an original minimax framework for finite-time performance analysis in queueing control and propose a surprisingly simple Lyapunov-based scheduling policy with superior finite-time performance. The framework quantitatively char…

  55. MiniMax Music 3 MiniMax Music 3 is a high-performance music generation model for creating complete songs up to five minutes long. Conditioned on lyrics and a detailed music description, it generates structurally coherent songs with express…

  56. Transfer-based adversarial attacks craft adversarial examples using surrogate models to mislead black-box victim models. Beyond perturbation generation, transferability is fundamentally governed by the coupling of initialization, surrogate…

  57. I am comparing a few model options for coding-agent work and MiniMax-M3 caught my attention because it is described as supporting coding, tool use, and long-context tasks. The questions I cannot answer from the documentation are fairly pra…

  58. I am planning to use GPT-5.6 luna high as my main autonomous coding agent. Before this, I was using MiniMax M3, which gives around 1.7B tokens monthly.

  59. Modern data science increasingly gives rise to hypothesis-testing problems that are not naturally formulated in terms of parameters within prespecified statistical models. One important example is the dynamic evaluation of optimization alg…

  60. The Naive Bayes (NB) classifier remains a standard choice for categorical data, yet its widely used smoothing rules, such as Laplace, Lidstone, Krichevsky-Trofimov, and the $m$-estimate, all prescribe a fixed smoothing strength that ignore…

  61. We study sequential decision-making in partially observable environments against strategic, adaptive opponents, modeled as partially observable Markov games (POMGs). The central challenge is to learn latent dynamics from partial observatio…

  62. h3-metal Native MiniMax-H3 inference for Apple Silicon. The project is being built as a sequence of working vertical slices: deterministic host/model metadata first, then portable Metal block parity, prompt encoding, prompt-to-video/audio,…

  63. Distributionally robust Markov decision processes provide a principled framework for sequential decision making under model uncertainty. We study how many samples are necessary and sufficient to learn an $\varepsilon$-optimal robust policy…

  64. In overparameterised classification, training data can be linearly separable even when the underlying distribution is not. In this setting, gradient descent (GD) on the logistic loss diverges in norm while converging in direction to a max-…

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  66. We study contextual dynamic pricing with arbitrary covariate sequences and bounded, possibly nonbinary purchase quantities. Demand follows a semiparametric surplus-index model with an unknown linear valuation parameter and an unknown Hölde…

  67. 4th August 2026 - Link Blog PipeNetwork/minimax-h3-mlx. MiniMax released MiniMax-H3 two days ago - they describe it as a "a general-purpose, omni-modal generative system", which in practice means it accepts text, images, audio and video an…

  68. Competitive analysis is central to the study of online algorithms, but upper bounds are often highly problem-specific. We develop a more unifying methodology via the minimax viewpoint.

  69. Sequential decision-making in real-world applications often involves uncertainty about the environment's model. Uncertain Markov decision processes (UMDPs) represent the possible environments as a set of MDPs with shared states and actions…

  70. MiniMax H3 Day-0 Support in ComfyUI: Open Weights, Native Audio, and 2K Video An open-weights omni-modal video model with real stereo sound and 2K output — this powerful model is greatly optimized in ComfyUI and can run locally on a 3060.…

  71. We study the expected improvement (EI) policy for minimizing a deterministic objective function $f$ on a nonempty compact set $\mathcal X \subset\mathbb R^d$. We assume that $f$ belongs to the RKHS $\mathcal H_k$ of a continuous positive-s…

  72. @MiniMax_AI H3 is live in SGLang Diffusion, with day-0 serving support 🎬 This open model matches Seedance 2.0 at 1/3 the cost, or $0 if you run it locally on 2x 5090 or 1 RTX 6000. With SGLang Diffusion, you can build visual concepts, m…

  73. MiniMax H3 System Overview MiniMax H3 is a general-purpose, omni-modal generative system. It supports unified understanding of multimodal contexts composed of text, images, video, and audio, and can generate video with native stereo audio…

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  75. On July 31, 2026, Chinese AI company MiniMax officially launched MiniMax H3 — the third-generation model in its Hailuo video family, also known as Hailuo 3.0. First previewed at WAIC 2026 just two weeks earlier, H3 arrives with a clear amb…

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  78. We introduce the MiniMax-M2 series, a family of Mixture-of-Experts language models built around the principle that mini activations can unleash maximum real-world intelligence. The flagship M2 contains 229.9B total parameters with only 9.8…

  79. MiniMax H3: Omni-Reference, Commercial-Grade Generation, Unbeatable Cost Efficiency, Open Weights - As I said, MiniMax-H3 is Open! #1 Video Editing (With Audio) #2 Text to Video (With Audio) #2 Image to Video (No Audio) artificialanalysis.…

  80. We study kernel ridge regression for nonparametric regression over the Hölder-Zygmund class. Using an RKHS equivalent to a Sobolev space of smoothness s+d/2, we prove that misspecified KRR attains the minimax L2 rate n^{-2s/(2s+d)}.

  81. Clustering is a fundamental problem in statistics, with applications across many scientific disciplines. In many modern applications involving clustering, the primary dataset (the target data) is accompanied by related datasets (the source…

  82. The tremendous success of Transformer models in fields such as large language models and computer vision necessitates a rigorous theoretical investigation. To the best of our knowledge, this paper is the first work proving that standard Tr…

  83. If U.S. labs slow down AGI development, this could be 2028: Moonshot Kimi 6, Alibaba Qwen 5, Z.ai, and MiniMax are all claiming AGI-level capabilities.

  84. Probabilistic text generators supply conditional distributions over tokens and complete verbal continuations, whereas scientific use often requires a posterior over a finite state. Large language models are the leading example: phrase prob…

  85. Over the past 20 years, kernel discrepancies have been leveraged as a highly powerful tool for quantifying the disagreement of distributions, with numerous successful applications in two-sample, goodness-of-fit, and independence testing, a…

  86. I benchmarked Claude Haiku 4.5 against 8 free/alt models (NVIDIA NIM plus a second free-tier provider) on a real task: writing outreach proposals from actual job postings, not a synthetic prompt. Same production prompts, same 3 real jobs,…

  87. I run a few agents for research and drafting. In one long chat the good output was always buried 200 messages up, I couldn't tell done vs running, and my team couldn't see any of it.

  88. Sparse-support uncertainty is usually quantified by treating the dictionary as known, an assumption that can produce overconfident, label-dependent conclusions when the dictionary is learned from latent sparse mixtures. Near collisions of…

  89. https://t.co/v9huIornsf elvis@omarsar0ArticleMiniMax M3: How Sparse Attention Makes Long-Horizon Agents Practical GLM 5.2 has taken over much of the AI timeline lately, and most of the conversation has centered on how it stacks up against…

  90. This study investigates minimax and Bayes optimal strategies for fixed-budget best-arm identification. We consider an adaptive procedure consisting of a sampling phase followed by a recommendation phase, and we design an adaptive experimen…

  91. Fable 5 · GPT 5.6 Sol · Kimi K3 · Grok 4.5 · Gemini 3.5 Flash · MiMo V2.5 Pro · MiniMax M3 · GLM 5.2 — low-poly, semi-realistic, very realistic.

  92. https://t.co/iJsDrlGy45 Harry Partridge@part_harry_ArticleGLM 5.2 With VisionGLM 5.2 is one of the best currently available open source language models. However, unlike other flagship models like Qwen, Kimi and Minimax, GLM 5.2 does not su…

  93. New day new model....... can't wait to see in a few weeks how Minimax 3 Pro (2.7T parameters) and GLM 5.3 reinforces the narrative.

  94. I expected Anthropic's flagship model to be expensive but sit near the quality ceiling. The current results are considerably worse than that.

  95. Long story short, it doesn’t matter if you’re using Opus or Fable or Sol and on what level of reasoning, if you put the output into any other model, from any lab or even the exact same model, and ask for an adversarial review, it will sugg…

  96. Speckle noise is a multiplicative noise commonly encountered in coherent imaging modalities such as synthetic aperture radar, optical coherence tomography, and digital holography. Although deep learning methods, in practice, have achieved…

  97. In bandit problems, standard regret-minimizing algorithms treat exploration as an amortized cost, which can expose early participants to unfair ex-ante losses in settings such as clinical trials. Recent work addresses this by evaluating th…

  98. been using cursor full time for about six months. was on opus the whole time and never questioned it because the output quality was there.

  99. We study contextual bilateral trade under full feedback when, conditionally on the context, trader valuations have bounded density but infinite variance. We first extend the self-bounding property of Bachoc et al.

  100. This paper addresses the distributed stochastic minimax optimization problem subject to stochastic constraints. We propose a novel first-order Softmax-Weighted Switching Gradient method tailored for federated learning.

  101. We study the bandit-feedback version of online principal component analysis (Bandit PCA): in each round $t = 1,\dots,T$, the adversary selects a $d \times d$ symmetric gain matrix $Gt$ with spectrum in $[0,1]$ and rank at most $r$; the lea…

  102. Adversarial team games (ATGs) with asymmetric information, such as adversarial path-finding, goal search, and reachability games on graphs, require strategies that are robust to hidden opponent types, such as a hidden goal flag, and to dec…

  103. Fireworks built a KV-stationary sparse-attention kernel for MiniMax M3 on NVIDIA Blackwell (SM100), reaching ~980 TFLOP/s: 1.9–2.4× a query-stationary baseline and ~1.6× open-source MSA. The post walks through the Q-outer vs KV-outer desig…

  104. We present in this paper novel accelerated fully first-order methods in \emph{Bilevel Optimization} (BLO). Firstly, for BLO under the assumption that the lower-level functions admit the typical strong convexity assumption, the \emph{(Pertu…

  105. Large language models increasingly provide labels, evaluations, and feedback for tasks specified in natural language. When a specification admits multiple readings but the supervision channel does not reveal which is operative, additional…

  106. [Github] [MiniMax Paper] [Trainer] Several frontier models [1, 2, 3, 4, 5] use sparse attention to greatly speedup their inference, though no one has posted code to train it efficiently. Today I introduce the world's first performant open-…

  107. The principal objective of this work is twofold within nonparametric regression settings: (1) to establish the minimax optimal convergence rates for fixed-bandwidth Gaussian kernel spectral algorithms when the true regression function resi…

  108. cheap and free from corporate oversight Low prices Open models Zero data retention First 100 million tokens free DEMO CHAT — try it Affordable AI inference Get access to powerful open models through a decentralized GPU network built to red…

  109. Zhipu AI, MiniMax shares to provide gut check for Hong Kong investors as lock-ups end Shares worth US$11.5 billion to hit market as record wave of lock-up expirations starts and some firms eye share placements Hong Kong’s stock market coul…

  110. Kernel Stein Discrepancy (KSD) compares a sample to a fixed target distribution known only through its score, and is widely used for goodness-of-fit testing, sample quality assessment, and approximate inference. We study the estimation of…

  111. Relay An open-source, dark-mode desktop coding agent — built for people who want to use non-mainstream LLM providers, not just the big three. Relay is an Electron app that puts DeepSeek, Qwen, GLM, Kimi, MiniMax, and other open/Chinese mod…

  112. Hi I'm Saoud, founder of Cline. We’ve been impressed with GLM-5.2 and so are introducing a $9.99/month subscription to give you 2-5x discounted access to it and other open weight models like DeepSeek, Kimi, MiniMax, Mimo, and Qwen.

  113. Pervasive data contamination -- stemming from measurement errors, outliers, or adversarial corruption -- has motivated the development of robust statistical methods. In this context, we propose a two-stage Adversarial Contamination-resista…

  114. I'm an SDE and I feel like I'm not getting much productivity out of coding agents. Yeah, they can generate code and build features, but most of what I get isn't really deployment-ready or easy to maintain.

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  116. When I first installed openclaw, I immediately set up an obsidian vault. When they added the memory_wiki plugin, I migrated everything to that and deleted obsidian..

  117. We study PAC learning in tabular discounted Markov decision processes with exogenous i.i.d. contexts, with discount factor $\gamma$, finite state space $\mathcal X$, action space $\mathcal A$, and context space $\mathcal Z$.

  118. Foundation models are often used as fixed black-box predictors for downstream tasks with limited labeled data, but their predictions may be biased and unsafe to trust blindly. We study this setting through black-box assisted nonparametric…

  119. We study the mean-squared error of $k$-fold cross-validation as a risk estimator, with particular emphasis on how its accuracy depends on the number of folds $k$. Despite the widespread use of cross-validation, principled guidance for choo…

  120. Minimax risk and regret are expectation-based criteria and do not capture rare but consequential failures. To address this concern, we develop a $\delta$-explicit minimax-quantile theory for interactive statistical decision making (ISDM).

  121. Hello, I'm having this problem with Cowork 3P, I cannot use Minimax model with Cowork 3P. This API key works when I use it with Hermes Agent Desktop, but it does not work with Cowork whatever I do.

  122. We benchmarked GLM 5.2, MiniMax M3, Kimi K2.7-code, Qwen 3.7-Plus and Sonnet 4.6 across nearly 1,000 coding-agent scenarios. The scenarios were run twice.

  123. Thinkbench, our custom evaluation harness, was used to drive both models through the same autonomous coding loop: read files, write files, run shell commands, and stop when the task was complete. The scored suite covered greenfield builds,…

  124. Optimal Reinforcement Learning (RL) algorithms typically rely on carefully constructed count-based uncertainty estimates to drive exploration. Although theoretically sound, such estimates are hard to compute in practical settings and there…

  125. We subsidize Deepseek 4.0, MiniMax M3, and more!

  126. Exciting news: GLM-5.2 (Max) ranks #2 in Code Arena: Frontend, with +29pt over Claude Opus 4.7 (Thinking) and only behind Fable 5! GLM-5.2 is the best open model vs Kimi-K2.6 and Minimax-M3 by a large margin.

  127. I'm a PM, not a researcher. My job is pulling 12-18 sources into one strategy doc and not losing the caveats.

  128. Data collection is a critical component of modern statistical and machine learning pipelines, particularly when data must be gathered from multiple heterogeneous sources to study a target population of interest. In many use cases, such as…

  129. The rapid advancement of large language models (LLMs) necessitates effective mechanisms to ensure their responsible deployment by accurately distinguishing unsafe content from benign content. While substantial safety datasets are available…

  130. MiniMax-M3 is a native multimodal model with 1M context. It has ~428B parameters and ~23B activated parameters.

  131. In anticipation of MiniMax reported upcoming open-weight release of M3, wanted to do comprehensive review of what I’m aware of regarding speed optimizations. Hopefully it can be helpful reference for some people too.

  132. Has anyone personally compared the Minimax M3 model against other proprietary models to determine its relative performance tier? I am trying to understand where it currently ranks in the broader Al landscape.

  133. https://www.minimax.io/blog/minimax-m3 They advertise it as open weight and have these words everywhere in their advertisements, but they have not released it.

  134. A hands-on look at MiniMax M3 through Claude Code — what its new MiniMax Sparse Attention (MSA) is and how it differs from the lightning-attention and full-attention designs of earlier MiniMax models, plus three real tasks: auditing and re…

  135. Long time lurker, and I say this as someone who genuinely loves this community and runs many local models myself. I’ve been using LLMs since the early GPT and LLaMA days.

  136. I'm currently using Minimax 2.7-AWQ-4bit for an specific coding agentic workflow. I see many of you are currently using Qwen3.6 and wanted to know how does it compare with Minimax2.7 .

  138. It should be at least 7-8 months until we have an open Fable(not just as good as Fable in benchmarks, but actually as good as Fable), probably more like 9-12 months. By the time, an open Fable model comes out, Fable 6.5-7 will be way bette…

  140. We study the minimax rate of estimating a future value $\mu{tn+h}$ of a curve $t\mapsto\mut$ in the $2$-Wasserstein space $\mathcal{P}2(\mathbb{R}^d)$ from finitely many noisy snapshots of its past, under an adiabatic bound $\|\nablat^k v\…

  141. Understanding the generalization performance of over-parameterized neural networks has become a central topic in deep learning theory. While recent advances, particularly works under the Neural Tangent Kernel (NTK) regime, have shed light…

  142. Context: I run an autonomous engineering "org" of AI agents on my own product. Once it grew past ~5 agents and started running around the clock, it maxed my Claude Max weekly limit by mid-week.

  143. I picked models I consider local (usable on 3×3090), so there are no 300B models, and you should probably skip 200B models too (but MiniMax and Step are pretty fast in Q3) Gemma-4 12B is still missing

  144. I have Mimo subscription alongside Claude Code Max. You won’t believe how suck Claude Opus can be at certain task but it does get more job done than any other model I have tried.

  145. I do not derive the Chinchilla scaling law; I map the boundaries of the regime in which such a derivation could even be attempted. Working in the μP feature-learning setting on a Sobolev-on-manifold data model, I establish what the station…

  148. - Together AI is the preferred cloud partner for MiniMax M3. Together AI will host the open-weights model as a developer endpoint upon its public release.

  149. I ran my usual coding tests — two websites, a poker sim, and a code audit. Here's how MiniMax M3 actually stacks up against GPT-5.5 and Opus 4.8.

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  151. MiniMax debuts AI model built for long and complex coding tasks Shanghai-based company says M3 can process data five times faster than its predecessor, while also slashing inference costs Chinese artificial intelligence start-up MiniMax ha…

  152. Coding & Agentic Frontier. 1M-context MSA.

  153. MiniMax (official) @MiniMax_AI Introducing MiniMax M3: The First Open-Weights Model to Combine Three Frontier Capabilities - Coding & Agentic Frontier: 59.0% SWE-Bench Pro, 66.0% Terminal Bench 2.1, 34.8% SWE-fficiency, 28.8% KernelBench H…

  154. MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding, and tool use.

  155. Hey HN, We believe we have the easiest onboarding from signup to being able to spin up coding agents in slack like Stripe, Ramp & Coinbase. Demo of the onboarding: https://www.tella.tv/video/connecting-cord-to-slack-1-19ep Every signup get…

  156. been self-hosting hermes agent locally for a few months and rotating through different model backends for it. tried claude sonnet 4.5, gpt-5.5, qwen 3.6 coder, and most recently minimax m2.7.

  157. Have you ever wondered, how DeepSeek may make money, and lot of it? They didn't come up with competitive coding plans like GLM, MoonShot and MiniMax.

  158. Don’t miss what’s happening People on X are the first to know. Log in Sign up Post Conversation Skyler Miao @SkylerMiao7 Something BIG is coming 2:49 PM · May 26, 2026 307.3K Views New to X?

  159. Been using Claude for everything creative lately and got tired of switching to Runway every time I needed video. Found out Higgsfield supports MCP, connected it once, and now Claude generates video directly in chat.

  160. I code for 20 years and make mobile apps for 15+. This February I decided to try vibe coding, but at scale.

  161. My use-cases will be to test open-weight LLMs and work on harnesses, inference systems and possibly other non-ML workflows (CS-related) in the future. Fine-tuning would not be something I do locally because I can rent a B200 from RunPod fo…

  162. https://preview.redd.it/i90oxxk7n03h1.png?width=1898&format=png&auto=webp&s=7d219c804fda7dfe122b84fcdb6d0d6883818c68 A while back I came across TradingAgents — a really cool multi-agent LLM stock analysis framework where like a dozen "agen…

  163. Hi everyone 👋 I’m trying to choose an LLM provider for my personal projects and side experiments, but I also don’t want my API bill to quietly consume my entire salary 😅 My primary use cases are: Coding assistance Agentic workflows Browser…

  164. I'm daily driving dual Asus GX10 (spark) with vllm and it's fantastic. But I want to try model that is GGUF only and won't fit into single spark.

  165. Testing MiniMax M2.7 via API on three real ML and coding workflows I recently got access to some MiniMax M2.7 API credits, so I decided to plug this model directly into Claude Code and run it on three workflows I do regularly. The same tas…

  166. Spent weeks running Hermes Agent in production on my Mac Mini M4 before recording this. Wanted to show things nobody else was covering.

  167. Made LLMs play Texas Hold’em against each other. 6 models at the table: a tiny 1.2B running locally on my 16GB MacBook, a couple mid-size ones, and cloud models going up to about 1 trillion parameters.

  168. I made 6 LLMs play Texas Hold’em against each other. Ran 5 tournaments on my 16GB MacBook.

  169. Basically the title. Recently I've been trying various open source and comparatively cheaper models like minimax m2.7, qwen models and glm5.1 in Pi agent from openrouter, and the performance on coding tasks have be moderately adequate at b…

  170. CPU is just a secondhand 10900x. Using 128k context, unquantized kv cache.

  171. llmfan46/MiniMax-M2.7-BF16-ultra-uncensored-heretic: https://huggingface.co/llmfan46/MiniMax-M2.7-BF16-ultra-uncensored-heretic llmfan46/MiniMax-M2.7-ultra-uncensored-heretic-GGUF: https://huggingface.co/llmfan46/MiniMax-M2.7-ultra-uncenso…

  172. by Nicholas Carlini 2025-01-05 Over the holidays I decided it's been too long since I did something with entirely no purpose. So without further ado, I present to you ...

  173. Ungate A Cursor-first extension for using Claude, ChatGPT, and MiniMax subscriptions in Cursor instead of paying for API tokens. How it works Ungate lets you use Claude, ChatGPT, and MiniMax in Cursor through account subscriptions instead…

  174. Original plan was to use Kimi/GLM for planning and DeepSeek for implementation, but seeing a lot of love for MiMo and Minimax lately. Anyone running a planner + coder split on Opencode?

  175. With the lowering usage limit in Claude, I am thinking of jumping ship to Chinese AI, since the benchmark is already very near compared to Sonnet or Haiku 4.5 , but for a fraction of the price. I am not worried about where is my data endin…

  176. With the lowering usage limit in Claude, I am thinking of jumping ship to Chinese AI, since the benchmark is already very near compared to Sonnet or Haiku 4.5 , but for a fraction of the price. I am not worried about where is my data endin…

  177. Just wanted to share because it took me a lot of tweaking to get here: llama-server -hf unsloth/MiniMax-M2.7-GGUF:UD-IQ3_XXS --temp 1.0 --top-k 40 --top-p 0.95 --host 0.0.0.0 --port 8080 -c 100000 -fa on -ngl 999 --no-context-shift -fit of…

  178. Hey r/AI_Agents — we're launching Irene today, and I want to be straight about what it is, why we built it, and where it's going. What makes Irene different Affordable with massive token limits and the latest open-source models We have gen…

  179. MTP was not released for m2.7, so would anyone have experience with setting up speculative decoding for minimax m2.7 and its results? Whether via EAGLE3 or a distilled variant

  180. llama-server.exe --model "H:\gptmodel\AesSedai\MiMo-V2.5-GGUF\MiMo-V2.5-IQ3_S-00001-of-00004.gguf" --ctx-size 1048576 --threads 16 --host 127.0.0.1 --no-mmap --jinja --fit on --flash-attn on -sm layer --n-cpu-moe 0 --threads 16 --parallel…

  181. So I'm brand new to this scene but I'm using Claude to help me fine tune a model for a startup idea I have in the Healthcare space. I have been working with the 27-35B parameter mdoels (Qwen3.6, Gemma 4) and the couple of 120B+ models (Qwe…

  182. Model Catalog Filter Connected Peers | ID | Role | Version | Status | Model | Latency | VRAM | Share | | --- | --- | --- | --- | --- | --- | --- | --- | | | Host | 0.65.1 | Serving | MiniMax-M2.5 | <1 ms | 256.0 GB | 42% | | | Host | 0.65.…

  183. MiniMax-M2.7-JANGTQ_K MiniMax M2.7 — 74 GB on disk (down from ~230 GB FP8 source) — mixed-bit JANGTQ_K quantization in JANGTQ-PRESTACK layout. Source: MiniMaxAI/MiniMax-M2.7 (62 layers, 256 routed experts top-8, 196K context) Quantization:…

  184. Just cancelled my claude subscription due to poor rate limits, gemini cli doesn't really excel in coding from my personal experience, and my local hardware isn't that powerful to run local AI models, and while codex is good, I wanna try so…

  185. wanted a terminal AI coding agent that doesn't lock me into one model provider. So I forked Qwen Code and added full support for every model available in AWS Bedrock.

  186. Here once again A Token Usage Meter for 12+ AI Providers Anthropic, OpenAI, Google, Alibaba qween, Moonshot Kimi, MiniMax, ElevenLabs, Deepgram, Perplexity. Qlaud.ai provides token usage meter / AI billing layer.

  187. I'm currently running a 4x RTX 3090 system (96GB VRAM, DDR4 2133 RAM) and have tested opencode and pi.dev using Qwen3.5-122B-A10B (AWQ) up to 200k context for web app coding (html/js/python). I'm now seriously considering picking up two Sp…

  188. So I saw an article recently about exo disaggregated prefill with DGX Spark and M3 Ultra - prefill on one machine and decode on another. DGX Spark apparently has 4x matmul performance over an M3 Ultra - same as the M5 Ultra should have.

  189. Hello, This model/quant is my daily driver and I wanted to have some reference benchs for comparing my setup with a 3x more expensive and 4x time power hungry setup. Results first, methodology after, link at the end with all results Model:…

  190. This is the hardest I've ever seen it riff. Full shared link at the bottom, but here are some highlights.

  191. Which of these do you think we'll get in May? Also, feel free to pick/rank which ones you'd want the most badly: more Gemma4 models (124b?) (other sizes?) more Qwen3.6 models (9b?

  192. True story, I got interested in AI after seeing it at work and wanted to run models locally. I started with an M3 Ultra 96GB, quickly learned it was not enough for what I wanted, and kept upgrading hardware (including refurbished Mac Studi…

  193. I invested quite a bit of time and it wasn't easy but finally I can run models like Minimax 2.7 Q4 using Cuda+ROCm at the same time bypassing Vulkan. load_tensors: offloaded 63/63 layers to GPU load_tensors: CUDA0 model buffer size = 83650…

  194. I’m pretty overwhelmed. I feel like there are so many options that I don’t know which one to choose, and trying things until I find a decent one isn’t really my thing—even though I enjoy it.

  195. Any underrated or overlooked models? FYI MiniMax-M2.7 switched their license(from MIT to Non-Commercial) so it's not in graph.

  196. https://preview.redd.it/kgkv6knv2dyg1.png?width=1026&format=png&auto=webp&s=d2e37f1914136ad672bcecf98741eee5e8cd69da MiniMax M2.7 AWQ 4bit hallucinated a URL and instantly pivoted to treating its own error as a joke. That made me laugh (do…

  197. Source: https://docs.tenstorrent.com/systems/quietbox/quietbox-bh-2/specifications.html Currently supported models: https://tenstorrent.com/developers From the specification docs above: CPU: Ryzen 7 9700X 65W Granite Ridge 3.8GHz Memory: 2…

  198. I was experimenting yesterday with running oversized models with smaller context size, hoping that leaving them overnight could compensate for the slow token generation and periodic pauses for compaction or task chunking. Summary: For rese…

  199. Some of the larger models (like Llama) weren't available on OpenRouter, so I had to work with what was there. Best small model: Gemma 4 26B For its size, I think it had the best output.

  200. DISCLAIMER: I am not a programmer nor do I have experience coding. I've been thinking about a small app running on gradio for some time now, and I want to try tweaking some extension for ComfyUI.

  201. It all started yesterday with this post by u/antirez https://www.reddit.com/r/LocalLLaMA/comments/1sw3stb/llamacpp_deepseek_v4_flash_experimental_inference/ I was intrigued by the first Deepseek V4 Flash GGUF in a small size that can fit o…

  202. So build[.]nvidia[.]com[/]models give access to free APIs for llms ranging from SLMs to frontier models. I tried building with it and let's say the APIs are so slow to respond.

  203. other companies are slowly going away from open weight, not releasing base models, delaying open weight distribution, not releasing top models (this one I think is fair, but still), and I also noticed they stopped publishing research (old…

  204. I’m trying to understand the current open-source LLM landscape beyond surface-level hype. We all got used to the nerfed products of Claude/Geminj so I believe really in opensource as a solution.

  209. TL;DR I try to keep most traffic on very cheap models (Nano / GLM‑Flash / Qwen / MiniMax) and only escalate to stronger models for genuinely complex or reasoning‑heavy queries. I’m still actively testing this and tweaking it several times…

  210. anyone knows how to setup opencode to work with self hosted minimax-2.7 properly? It has <think> and </think> in the message and OpenCode failed to parse the answer correctly.

  211. For context i used to ask many near 30b model this question --> **^(Calculate the precise VRAM requirement for the \*KV Cache only** at the maximum context window for **DeepSeek V3.2** and **MiniMax M2.5**. * **DeepSeek V3.2 Max Context:**…

  212. could not extract summary

  213. Hi everyone. It's been a while since I posted (was a lil burned out), but some of you may have seen my older SanityHarness posts.

  214. I keep on hearing from community here that Minimax models are pretty solid, their benchmark are also always respectable but I am never able to get decent result from them. I have tried local setup (multiple harness) I have even tried their…

  215. Ryzen AI MAX+ 395, Bosgame M5, 128GB LPDDR5x. Proxmox VE 9.1 LXC containers with GPU passthrough.

  216. Im running the raw version straight from the minimax release on hugging face (https://huggingface.co/MiniMaxAI/MiniMax-M2.7) on 3 rtx pro 6000's on vllm. So no quantization.

  217. Inference engine used (vllm fork): https://github.com/ai-infos/vllm-gfx906-mobydick/tree/main Huggingface Quants used: cyankiwi/MiniMax-M2.7-AWQ-4bit Relevant commands to run: docker run -it --name vllm-gfx906-mobydick-mixa3607 -v ~/llm/mo…

  218. I’ve been running various AI harnesses like OpenClaw, ForgeCode, ClaudeCode, etc. Most of these are running via OpenRouter or Minimax (credits/subscription model).

  219. Hey guys, come fight me: how do you justify local LLMs from a value perspective? It doesn't seem economical?

  220. Ungate A Cursor-first extension for using Claude, ChatGPT, and MiniMax subscriptions in Cursor instead of paying for API tokens. How it works Ungate lets you use Claude, ChatGPT, and MiniMax in Cursor through account subscriptions instead…

  221. I currently am looking for models to fit into my single DGX Spark for use. I have an RTX Pro 6000 and also a 5090 as well that I'm considering using in combination if the DGX Spark is too slow, but the intent here is to play around with Op…

  222. Hey guys, just checked out minimax 2.7, where they used AI to train itself, and ran over a hundred loops, and it improved it's performance by 30%, how does that work, can I also run a script that makes AI store it's memory in a loop on a m…

  223. Hi. I've been looking at ollama cloud's Pro offering ($20), which says "Run 3 cloud models at a time".

  224. I made this due to the usage problem. Enjoy and tell me what you guys think!

  225. So i have been seeing more of those pelican on a bike svg tests and while they work i feel like (and maybe you guys do too) they are getting kinda benchmaxxed so we should switch things up soon and this is my idea generate me a html svg of…

  226. RyanLee's(MiniMax) recent tweets for same. I just updated our license.

  227. I'm not sure if the AesSedai's Q5_K_M version of Minimax M2.7 is too much lobotomized or if the model itself is kind of weak. I did a simple experiment with both models running with the recommended parameters.

  228. Badda Boom.

  229. could not extract summary

  230. Hey r/LocalLLaMA, we did an investigation into MiniMax-M2.7 GGUF causing NaNs on perplexity. Our findings show the issue affects 21%-38% of all GGUFs on Hugging Face (not just ours).

  231. Hello, I've been on a quest to get something "close enough" of Opus 4.5 running locally, for agentic coding, as SWE with 15 years of experience. I tried with one spark (yeah I'm calling my Asus Ascent GX10 sparks - they're the same), with…

  232. We’ve been benchmarking a few models on our API platform and got some interesting performance numbers: - MiniMax M2.5 → 0.118s time-to-first-token, 103 tokens/sec - GLM 5.1 → 120 tokens/sec throughput - Kimi K2.5 → 0.643s TTFT, 69 tokens/s…

  233. I spent too much time trying to find one AI dev tool that could do everything. Planning, coding, fixing, reviewing, maybe filing my taxes too It never really worked.

  234. https://huggingface.co/JANGQ-AI/MiniMax-M2.7-JANGTQ Used TQ as quantization method where it matters. Finally mac users under 64 gb - esp base m5 users can get a real cloud SOTA-like level LLM running from home.

  235. What am I doing wrong here? I can't get models to follow my instructions, pretty much at all.

  236. I'm curious if there is a rule of thumb regarding how to best load Minimax given varying amounts of VRAM/RAM configurations. Is there a way to estimate how many experts versus layers to offload for individuals running either 16GB/24GB/32GB…

  237. I have the following hardware and want to run MiniMax-M2.7 (230B) locally. What is the best software stack and configuration to maximize performance?

  238. MiniMax just open-sourced MMX-CLI, a command-line tool built specifically for AI agents. Seven command groups: mmx text, mmx image, mmx video, mmx speech, mmx music, mmx vision, mmx search.

  239. I need help. I want to self-contain my MiniMax 2.7 and Qwen 3.5 (122 billion parameter) models.

  240. WEB SEARCH WAS ALWAYS ON!!!! Question Calculate the precise VRAM requirement for the **KV Cache only** at the maximum context window for **DeepSeek V3.2** and **MiniMax M2.5**.

  241. could not extract summary

  242. I get good, cheap, fast feature coding success with grok-4.1-fast for planning and grok-code-fast-1 for execution. But according to the Openrouter usage stats, grok-code-fast-1 is now old hat - usage dropped off a cliff in mid-Feb.

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