MiniMax-M3
- In Input modalities: TextImageVideo Out Output modalities: Text
- Reasoning
- Reasoning can be off
- Tool use
- Open weights
Prices
2 offerings · prices as listedMiniMax-M3| Conditions/ 1M tokens | Input | Cache read | Output |
|---|---|---|---|
| Standard | $0.30 | $0.060 | $1.20 |
| Prompts over 512K tokens | $0.60 | $0.12 | $2.40 |
| Priority tier | $0.45 | $0.090 | $1.80 |
| Prompts over 512K tokensPriority tier | $0.90 | $0.18 | $3.60 |
Prices from Pricing Overview - MiniMax API Docs (opens in a new tab) (checked Nov 1, 2026)
MiniMax-M3| Conditions/ 1M tokens | Input | Cache read | Output |
|---|---|---|---|
| Standard | ¥2.10 | ¥0.42 | ¥8.40 |
| Prompts over 512K tokens | ¥4.20 | ¥0.84 | ¥16.80 |
| Priority tier | ¥3.15 | ¥0.63 | ¥12.60 |
| Prompts over 512K tokensPriority tier | ¥6.30 | ¥1.26 | ¥25.20 |
Prices from MiniMax 按量计费价格 (opens in a new tab) (checked Nov 1, 2026)
Standard: the price a request with no conditions pays (the headline price elsewhere on the site).
Details
- Family
- minimax-m
- Model ID
Not stated on MiniMax’s pages: max input, reasoning efforts, max thinking budget, structured output, built-in tools, knowledge cutoff, licence, aliases.
Run locally
Weights: MiniMaxAI/MiniMax-M3- Parameters 427B
- Active 23B · 128 experts, 4 per token
- Native precision BF16
- Layers 60
- KV cache per token 120 KB
- Config positions 1024K (config.json max_position_embeddings)
- API context 977K (maker’s API)
- Needs
- ≈ 222.8 GB (weights 211.3 + KV cache 0.9 + overhead 10.6)
- Usable
- 21.6 GB (90% of its memory)
- Try
- it’s too large for this hardware; see the smallest that runs it below
| Precision | Weights | Needs at 8K | On your hardware | Longest context |
|---|---|---|---|---|
| BF16 (native)maker’s file | 795.5 GB | ≈ 836.2 | ✕Doesn’t fit | — |
| Q8_0 | 422.6 GB | ≈ 444.6 | ✕Doesn’t fit | — |
| FP8 | 397.7 GB | ≈ 418.5 | ✕Doesn’t fit | — |
| Q6_K | 326.6 GB | ≈ 343.9 | ✕Doesn’t fit | — |
| Q5_K_M | 282.9 GB | ≈ 298.0 | ✕Doesn’t fit | — |
| Q5_0 | 273.4 GB | ≈ 288.0 | ✕Doesn’t fit | — |
| Q4_K_M | 241.6 GB | ≈ 254.6 | ✕Doesn’t fit | — |
| Q4_0 | 223.7 GB | ≈ 235.8 | ✕Doesn’t fit | — |
| IQ4_XS | 211.3 GB | ≈ 222.8 | ✕Doesn’t fit | — |
| Q3_K_Mquality drops | 194.4 GB | ≈ 205.0 | ✕Doesn’t fit | — |
| IQ3_XXSquality drops | 152.1 GB | ≈ 160.7 | ✕Doesn’t fit | — |
| Q2_Kquality drops | 149.1 GB | ≈ 157.5 | ✕Doesn’t fit | — |
| IQ2_XXSquality drops | 102.4 GB | ≈ 108.5 | ✕Doesn’t fit | — |
Click a row to choose a precision. “Maker’s file” sizes are the maker’s own files; others are parameters × bits per weight.
Compared with other hardware
Each at the highest precision it runs. Click one for details.
Smallest that runs it (Q4_K_M, 8K): no single listed GPU; unified memory Apple M5 Ultra (80-core GPU) · 512 GB.
Run commands
The maker publishes no files at this precision. Choose its native precision or one of its own builds, or quantise it yourself with llama.cpp.
Memory to fine-tune
Batch 1, 2,048-token sequences, gradient checkpointing; LoRA and QLoRA train rank-16 adapters on the attention projections.
Estimates; facts from the maker’s Hugging Face repositories, as of 2026-11-06. How it’s estimated
Cited scores
From third-party leaderboards, not measured by us- Epoch Capabilities Index 147.6
#67 of 118 listed models · CI 145.4–149.8
- LMArena Text 1,439
#64 of 163 listed models · CI 1,436–1,443 · 68,611 votes
- Epoch AI · Chess Puzzles 17%
#69 of 85 listed models · ±3.78
Also listed: reasoning off 8%
- Epoch AI · GPQA Diamond 90.9%
#32 of 168 listed models · ±2.05
Also listed: reasoning off 81.3%
- Epoch AI, 'Capabilities & benchmarking'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/benchmarks'. Licensed CC BY 4.0. · License · as of Oct 28 – Nov 5, 2026
- LMArena (Arena), leaderboard-dataset on Hugging Face, licensed CC BY 4.0 · License · as of Sep 13 – Oct 28, 2026
- EQ-Bench by Samuel J. Paech (eqbench.com; EQ-bench/EQ-bench-site on GitHub), MIT License. · License · as of Oct 24, 2026
- LiveBench (White et al.), release 2026-06-25, livebench.ai, licensed CC BY-SA 4.0. This board, adapted from it, is shared under CC BY-SA 4.0. · License · as of Jun 25, 2026
- changes we made
Included in coding plans
- 5× the usage of the Lite plan
Changes
All changes →No changes recorded yet.
Sources
- Pricing Overview - MiniMax API Docs (opens in a new tab) platform.minimax.io · checked Nov 1, 2026
- MiniMax 按量计费价格in Chinese (opens in a new tab) platform.minimaxi.com · checked Nov 1, 2026
- MiniMax models (opens in a new tab) platform.minimax.io · checked Nov 1, 2026
- Anthropic SDK (opens in a new tab) platform.minimax.io · checked Nov 1, 2026
- MiniMax model release notes (opens in a new tab) platform.minimax.io · checked Nov 1, 2026
- MiniMaxAI/MiniMax-M3 model card (opens in a new tab) huggingface.co · checked Nov 2, 2026
- GitHub - MiniMax-AI/MiniMax-M3 · GitHub (opens in a new tab) github.com · checked Nov 4, 2026
- MiniMaxAI/MiniMax-M3 model card (opens in a new tab) huggingface.co · checked Nov 3, 2026
- MiniMax Text API OpenAI (opens in a new tab) platform.minimaxi.com · checked Nov 5, 2026
- MiniMaxAI/MiniMax-M3 model card (opens in a new tab) huggingface.co · checked Oct 30, 2026
- MiniMaxAI/MiniMax-M3 config.json (opens in a new tab) huggingface.co · checked Nov 4, 2026
- MiniMaxAI/MiniMax-M3 files (opens in a new tab) huggingface.co · checked Nov 3, 2026
- MiniMaxAI/MiniMax-M3 README.md (opens in a new tab) huggingface.co · checked Nov 2, 2026
MiniMax’s official policies: data use, privacy, terms →
MiniMax · China · minimax.io
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