Model reference · open weights

MiniMax-Text-01

Available as managed deployment Licence fee LLMs MiniMaxAI Text gen 1 variants 17k dl/mo

MiniMax-Text-01 is an open-weight language model from MiniMaxAI. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

MakerMiniMaxAI
TypeLanguage models
TaskText gen
Parameters (lead)456.1B
Runs withtransformers
Released2025-06-03
Popularity17k downloads / month
LicenceCommercial licence needed

About

What MiniMax-Text-01 is

This repository is primarily for the Transformers framework. If you're using other open-source frameworks, please use the alternative repository: MiniMax-Text-01

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MiniMax-Text-01

1. Introduction

MiniMax-Text-01 is a powerful language model with 456 billion total parameters, of which 45.9 billion are activated per token. To better unlock the long context capabilities of the model, MiniMax-Text-01 adopts a hybrid architecture that combines Lightning Attention, Softmax Attention and Mixture-of-Experts (MoE). Leveraging advanced parallel strategies and innovative compute-communication overlap methods—such as Linear Attention Sequence Parallelism Plus (LASP+), varlen ring attention, Expert Tensor Parallel (ETP), etc., MiniMax-Text-01's training context length is extended to 1 million tokens, and it can handle a context of up to 4 million tokens during the inference. On various academic benchmarks, MiniMax-Text-01 also demonstrates the performance of a top-tier model.

2. Model Architecture

The architecture of MiniMax-Text-01 is briefly described as follows:

  • Total Parameters: 456B
  • Activated Parameters per Token: 45.9B
  • Number Layers: 80
  • Hybrid Attention: a softmax attention is positioned after every 7 lightning attention.
    • Number of attention heads: 64
    • Attention head dimension: 128
  • Mixture of Experts:
    • Number of experts: 32
    • Expert hidden dimension: 9216
    • Top-2 routing strategy
  • Positional Encoding: Rotary Position Embedding (RoPE) applied to half of the attention head dimension with a base frequency of 10,000,000
  • Hidden Size: 6144
  • Vocab Size: 200,064

3. Evaluation

Core Academic Benchmarks

TasksGPT-4o (11-20)Claude-3.5-Sonnet (10-22)Gemini-1.5-Pro (002)Gemini-2.0-Flash (exp)Qwen2.5-72B-Inst.DeepSeek-V3Llama-3.1-405B-Inst.MiniMax-Text-01
General
MMLU*85.788.386.886.586.188.588.688.5
MMLU-Pro*74.478.075.876.471.175.973.375.7
SimpleQA39.028.123.426.610.324.923.223.7
C-SimpleQA64.656.859.463.352.264.854.767.4
IFEval (avg)84.190.189.488.487.287.386.489.1
Arena-Hard92.487.685.372.781.291.463.589.1
Reasoning
GPQA* (diamond)46.065.059.162.149.059.150.754.4
DROP* (F1)89.288.889.289.385.091.092.587.8
Mathematics
GSM8k*95.696.995.295.495.896.796.794.8
MATH*76.674.184.683.981.884.673.877.4
Coding
MBPP +76.275.175.475.977.078.873.071.7
HumanEval90.293.786.689.686.692.189.086.9

Long Benchmarks

4M Needle In A Haystack Test

Ruler

| Model | 4k | 8k | 16k |

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys minimax-text-01 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (minimax-text-01 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"minimax-text-01","messages":[{"role":"user","content":"Hello"}]}'

Create an account — your API key is available in the console. 5M tokens/month currently included with every new account at launch.

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