What are the hardware requirements for MiniMax M2.7 8bit?

MiniMax M2.7 8bit requires approximately 228.2 GB of VRAM and supports a context window of 192K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MiniMax M2.7 8bit and how large is it?

MiniMax M2.7 8bit is developed by mlx-community, a model with 228.7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does MiniMax M2.7 8bit perform on standard benchmarks?

MiniMax M2.7 8bit has the following published scores: LMSYS ELO 1403. Compare against reference models on this page or on the LLM Explorer leaderboards.

MiniMax M2.7 8bit by mlx-community — VRAM 228.2GB, 192K context

Name: MiniMax M2.7 8bit
Author: mlx-community

MiniMax M2.7 8bit is an open-source language model by mlx-community. Features: 228.7b LLM, VRAM: 228.2GB, Context: 192K, License: other, Quantized, LLM Explorer Score: 0.39, ELO: 1403.

8-bit 8bit Base model:minimaxai/minimax-m... Base model:quantized:minimaxai... Conversational Custom code Minimax m2 Mlx Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/MiniMax-M2.7-8bit

MiniMax M2.7 8bit Benchmarks

LMSys ELO 1403 vs 1272 (so35) 10.3%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

MiniMax M2.7 8bit Parameters and Internals

LLM Name	MiniMax M2.7 8bit
Repository 🤗	https://huggingface.co/mlx-community/MiniMax-M2.7-8bit
Base Model(s)	MiniMaxAI/MiniMax-M2.7 MiniMaxAI/MiniMax-M2.7
Model Size	228.7b
Required VRAM	228.2 GB
Updated	2026-08-10
Maintainer	mlx-community
Model Type	minimax_m2
Model Files	4.6 GB: 1-of-47 5.2 GB: 2-of-47 5.2 GB: 3-of-47 5.2 GB: 4-of-47 5.2 GB: 5-of-47 5.2 GB: 6-of-47 5.2 GB: 7-of-47 5.2 GB: 8-of-47 5.2 GB: 9-of-47 5.2 GB: 10-of-47 5.2 GB: 11-of-47 5.2 GB: 12-of-47 5.2 GB: 13-of-47 5.2 GB: 14-of-47 5.2 GB: 15-of-47 5.2 GB: 16-of-47 5.2 GB: 17-of-47 5.2 GB: 18-of-47 5.2 GB: 19-of-47 5.2 GB: 20-of-47 5.2 GB: 21-of-47 5.2 GB: 22-of-47 5.2 GB: 23-of-47 5.2 GB: 24-of-47 5.2 GB: 25-of-47 5.2 GB: 26-of-47 5.2 GB: 27-of-47 5.2 GB: 28-of-47 5.2 GB: 29-of-47 5.2 GB: 30-of-47 5.2 GB: 31-of-47 5.2 GB: 32-of-47 5.2 GB: 33-of-47 5.2 GB: 34-of-47 5.2 GB: 35-of-47 5.2 GB: 36-of-47 5.2 GB: 37-of-47 5.2 GB: 38-of-47 5.2 GB: 39-of-47 5.2 GB: 40-of-47 5.2 GB: 41-of-47 5.2 GB: 42-of-47 5.2 GB: 43-of-47 5.2 GB: 44-of-47
Quantization Type	8bit
Model Architecture	MiniMaxM2ForCausalLM
License	other
Context Length	196608
Model Max Length	196608
Transformers Version	4.46.1
Vocabulary Size	200064

Rank the MiniMax M2.7 8bit capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to MiniMax M2.7 8bit

Best Alternatives	Context / RAM	Downloads	Likes
MiniMax M2.7 4bit Mxfp4	192K / 121.5 GB	746	10
MiniMax M2.7 4bit	192K / 128.3 GB	739	2
MiniMax M2.7 3bit	192K / 99.7 GB	319	4
MiniMax M2.7 6bit	192K / 185.8 GB	268	1
MiniMax M2.7 5bit	192K / 155.8 GB	189	2
MiniMax M2.7 8bit Gs32	192K / 211.8 GB	66	2
MiniMax M2 Mlx 8bit Gs32	192K / 206.5 GB	14	2
MiniMax M2.1 3bit	192K / 99.7 GB	3529	5
MiniMax M2.1 4bit	192K / 128.3 GB	2484	5
MiniMax M2.1 8bit	192K / 217.8 GB	2124	2

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/MiniMax-M2.7-8bit.