model roundup

MiniMax 2.7

9 items · started 2026-04-13 · closed 2026-04-19

  1. 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.

  2. 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.

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

  4. 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…

  5. So I was just about to give up playing with local models, until I realised I can actually run GLM 5.1 at not too horrible speeds, using this quant https://huggingface.co/ubergarm/GLM-5.1-GGUF/tree/main/IQ2_KL in ik llama. Getting around 6.…

  6. 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…

  7. Badda Boom.

  8. 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…

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

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