MiniMax M1 80K vs Mistral Nemotron vs o3-deep-research
o3-deep-research comes out ahead, 49 to 45 and 25 on our weighted score, though MiniMax M1 80K is 16× cheaper per token.
MiniMaxMiniMax M1 80K
45/100- ECI—
- Price$0.55 / $2.20
- Context1M
NVIDIAMistral Nemotron
25/100- ECI—
- Price—
- Context128K
- Our pick
OpenAIo3-deep-research
49/100- ECI—
- Price$9.00 / $36.00
- Context200K
o3-deep-research is our pick
o3-deep-research is the better all-round choice, scoring 49/100 against MiniMax M1 80K (45) and Mistral Nemotron (25). It leads on inputs & features. MiniMax M1 80K wins on context window. 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 priceMiniMax M1 80KMiniMax M1 80K $0.963 · o3-deep-research $15.75 per 1M tokens (3:1 blend) · Mistral Nemotron unpriced
- Longest contextMiniMax M1 80KMiniMax M1 80K 1,000,000 · o3-deep-research 200,000 · Mistral Nemotron 128,000 tokens
- Widest inputso3-deep-researchMiniMax M1 80K: Text · Mistral Nemotron: Text · o3-deep-research: Text, Images
- Self-hostingMiniMax M1 80KPublishes downloadable weights (Apache-2.0)
| Measure | Weight | MiniMax M1 80K | Mistral Nemotron | o3-deep-research |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 25 | 60 |
| Context window | 40% | 60 | 24 | 32 |
| Overall | 100% | 45/100 | 25/100 | 49/100 |
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 | o3-deep-researchOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.55 (best) | — | $9.00 |
| Output | $2.20 (best) | — | $36.00 |
| Cached input | — | — | — |
| Blended (3:1) | $0.963 (best) | — | $15.75 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 5 providers | — | Median of 1 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 128,000 tokens | 200,000 tokens |
| Max output | 80,000 tokens | 8,192 tokens | 100,000 tokens (best) |
| 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 | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Proprietary |
| API model ID | — | — | — |
| API providers | 5 (best) | — | 1 |
| Released | Jun 17, 2025 | Jun 11, 2025 | Jun 26, 2025 |
| Knowledge cutoff | — | — | May 2024 |
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—
- o3-deep-research$162.00
Which should you choose?
Which is better: MiniMax M1 80K, Mistral Nemotron or o3-deep-research?
o3-deep-research is the better all-round choice, scoring 49/100 against MiniMax M1 80K (45) and Mistral Nemotron (25). It leads on inputs & features. MiniMax M1 80K wins on context window. 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 o3-deep-research?
MiniMax M1 80K is cheaper at $0.55 input / $2.20 output per million tokens (median across 5 API providers). o3-deep-research costs $9.00 input / $36.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.963 per million tokens for MiniMax M1 80K versus $15.75 for o3-deep-research (16× 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 o3-deep-research 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 o3-deep-research 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 200,000 for o3-deep-research and 128,000 for Mistral Nemotron. Maximum output per response: MiniMax M1 80K up to 80,000, Mistral Nemotron up to 8,192, o3-deep-research up to 100,000 tokens.
Which can read images, PDFs, audio or video?
MiniMax M1 80K accepts text; Mistral Nemotron accepts text; o3-deep-research accepts text and images. o3-deep-research handles the widest range of inputs.
Are any of these open source?
MiniMax M1 80K publishes its weights (Apache-2.0) and can be self-hosted; Mistral Nemotron and o3-deep-research is proprietary.
Which is newer?
o3-deep-research is the newest, released Jun 26, 2025. MiniMax M1 80K came out Jun 17, 2025; Mistral Nemotron came out Jun 11, 2025. Knowledge cutoff: o3-deep-research May 2024.
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.
