MiniMax M1 80K vs Mistral Nemotron vs Mistral Small 3.2 24B
Too close to call on our weighted score (MiniMax M1 80K 45, Mistral Small 3.2 24B 44, Mistral Nemotron 25). The right pick depends on what you value most.
MiniMaxMiniMax M1 80K
45/100- ECI—
- Price$0.55 / $2.20
- Context1M
NVIDIAMistral Nemotron
25/100- ECI—
- Price—
- Context128K
Mistral AIMistral Small 3.2 24B
44/100- ECI—
- Price$0.10 / $0.305
- Context256K
Too close to call
It is close. Our weighted score puts them within a point (MiniMax M1 80K 45/100, Mistral Small 3.2 24B 44/100, Mistral Nemotron 25/100), so choose by what matters most for your work: Mistral Small 3.2 24B on price and MiniMax M1 80K for long inputs. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceMistral Small 3.2 24BMistral Small 3.2 24B $0.151 · MiniMax M1 80K $0.963 per 1M tokens (3:1 blend) · Mistral Nemotron unpriced
- Longest contextMiniMax M1 80KMiniMax M1 80K 1,000,000 · Mistral Small 3.2 24B 256,000 · Mistral Nemotron 128,000 tokens
- Widest inputsMistral Small 3.2 24BMiniMax M1 80K: Text · Mistral Nemotron: Text · Mistral Small 3.2 24B: Text, Images
- Self-hostingMiniMax M1 80K and Mistral Small 3.2 24BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | MiniMax M1 80K | Mistral Nemotron | Mistral Small 3.2 24B |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 25 | 50 |
| Context window | 40% | 60 | 24 | 36 |
| Overall | 100% | 45/100 | 25/100 | 44/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | MiniMax M1 80KMiniMax | Mistral NemotronNVIDIA | Mistral Small 3.2 24BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.55 | — | $0.10 (best) |
| Output | $2.20 | — | $0.305 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.963 | — | $0.151 (best) |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 5 providers | — | Median of 8 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 128,000 tokens | 256,000 tokens |
| Max output | 80,000 tokens (best) | 8,192 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Open |
| API model ID | — | — | — |
| API providers | 5 | — | 8 (best) |
| Released | Jun 17, 2025 | Jun 11, 2025 | Jun 20, 2025 |
| Knowledge cutoff | — | — | Oct 31, 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- MiniMax M1 80K$9.90
- Mistral Nemotron—
- Mistral Small 3.2 24B$1.61
Which should you choose?
Which is better: MiniMax M1 80K, Mistral Nemotron or Mistral Small 3.2 24B?
It is close. Our weighted score puts them within a point (MiniMax M1 80K 45/100, Mistral Small 3.2 24B 44/100, Mistral Nemotron 25/100), so choose by what matters most for your work: Mistral Small 3.2 24B on price and MiniMax M1 80K for long inputs. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, MiniMax M1 80K, Mistral Nemotron or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is cheaper at $0.10 input / $0.305 output per million tokens (median across 8 API providers). MiniMax M1 80K costs $0.55 input / $2.20 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.151 per million tokens for Mistral Small 3.2 24B versus $0.963 for MiniMax M1 80K (6.4× as much). Mistral Nemotron has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax M1 80K has not been scored yet, Mistral Nemotron has not been scored yet and Mistral Small 3.2 24B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax M1 80K, Mistral Nemotron and Mistral Small 3.2 24B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
MiniMax M1 80K has the largest context window at 1,000,000 tokens, against 256,000 for Mistral Small 3.2 24B and 128,000 for Mistral Nemotron. Maximum output per response: MiniMax M1 80K up to 80,000, Mistral Nemotron up to 8,192, Mistral Small 3.2 24B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
MiniMax M1 80K accepts text; Mistral Nemotron accepts text; Mistral Small 3.2 24B accepts text and images. Mistral Small 3.2 24B handles the widest range of inputs.
Are any of these open source?
MiniMax M1 80K and Mistral Small 3.2 24B publishes its weights (Apache-2.0) and can be self-hosted; Mistral Nemotron is proprietary.
Which is newer?
Mistral Small 3.2 24B is the newest, released Jun 20, 2025. MiniMax M1 80K came out Jun 17, 2025; Mistral Nemotron came out Jun 11, 2025. Knowledge cutoff: Mistral Small 3.2 24B Oct 31, 2023.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
