MiniMax-M3.1-Flash
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
28.9
AA Index
Coding
22.8
AA Index
Agentic
46.7
AA Index
Intelligence Index - MiniMax-M3.1-Flash vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Coding Index comparison
Agentic Index comparison
Benchmark data from Artificial Analysis · updated 2026-10-31.
Hosted API cost & speed
What it costs to rent this model instead of running it locally
| Metric | Value |
|---|---|
| Input (per 1M tokens) | $0.15 |
| Output (per 1M tokens) | $0.60 |
| Median speed (hosted API) | 119 tok/s |
Median across hosted providers, measured by Artificial Analysis - updated 2026-10-31. Local llama.cpp speed depends on your hardware — see the hardware pages for estimates.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| HLE | 48 |
| SciCode | 53.4 |
Source: Artificial Analysis component evals - updated 2026-10-31.
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
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Deep dive
Notes, sources, and the full write-up
MiniMax-M3.1-Flash is a 220.5B-parameter other model from MiniMax. It scores 28.9 on the Artificial Analysis Intelligence Index (coding 22.8). At Q4_K_M it needs roughly 128 GB of VRAM, placing it in the 48 GB+ / multi-GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - MiniMax-M3.1-Flash vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| MiniMax-M3.1-Flash | 28.9 | 22.8 | - |
| Gemini 4 Carbon | 59.4 | 50.4 | - |
| Claude Opus 5.5 | 58.4 | 51.7 | - |
| GPT-6 Astra | 56.9 | 49.1 | 96.1 |
| GPT-6.1 Sol | 54.5 | 46.8 | - |
| Claude Sonnet 5.5 | 54.2 | 50.5 | - |
Source: Artificial Analysis (2026-10-31).
Popularity
MiniMax-M3.1-Flash has 18,795 downloads in the last month on HuggingFace and 501 likes.
Frequently asked
Quick answers to common questions
How much VRAM does MiniMax-M3.1-Flash need?
MiniMax-M3.1-Flash with 220.5B parameters needs approximately 128 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is MiniMax-M3.1-Flash better than other MiniMaxAI models?
MiniMax-M3.1-Flash has 220.5B parameters with 1,048,576 context - a strong choice for general use.
What license is MiniMax-M3.1-Flash under?
MiniMax-M3.1-Flash is released under the other license, making it suitable for most commercial and personal projects.
What hardware runs MiniMax-M3.1-Flash well?
With 220.5B parameters, MiniMax-M3.1-Flash requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for MiniMax-M3.1-Flash?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~157 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can MiniMax-M3.1-Flash's context window handle?
MiniMax-M3.1-Flash supports a 1,048,576-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with MiniMax-M3.1-Flash?
MiniMax-M3.1-Flash competes with other 110B–331B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec