Mistral Nemotron vs Sarvam-M vs MiniMax M1 80K
MiniMax M1 80K comes out ahead, 45 to 25 and 6 on our weighted score, and it is the cheaper option too.
NVIDIAMistral Nemotron
25/100- ECI—
- Price—
- Context128K
Sarvam AI
Sarvam-M
6/100- ECI—
- Price—
- Context33K
- Our pick
MiniMaxMiniMax M1 80K
45/100- ECI—
- Price$0.55 / $2.20
- Context1M
MiniMax M1 80K is our pick
MiniMax M1 80K is the better all-round choice, scoring 45/100 against Mistral Nemotron (25) and Sarvam-M (6). It leads on inputs & features and 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 per 1M tokens (3:1 blend) · Mistral Nemotron and Sarvam-M unpriced
- Longest contextMiniMax M1 80KMiniMax M1 80K 1,000,000 · Mistral Nemotron 128,000 · Sarvam-M 32,768 tokens
- Widest inputsSame inputsMistral Nemotron: Text · Sarvam-M: Text · MiniMax M1 80K: Text
- Self-hostingSarvam-M and MiniMax M1 80KPublishes downloadable weights (Apache 2.0 and Apache-2.0)
| Measure | Weight | Mistral Nemotron | Sarvam-M | MiniMax M1 80K |
|---|---|---|---|---|
| Inputs & features | 60% | 25 | 10 | 35 |
| Context window | 40% | 24 | 0 | 60 |
| Overall | 100% | 25/100 | 6/100 | 45/100 |
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 | Mistral NemotronNVIDIA | Sarvam-MSarvam AI | MiniMax M1 80KMiniMax |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | — | $0.55 |
| Output | — | — | $2.20 |
| Cached input | — | — | — |
| Blended (3:1) | — | — | $0.963 |
| Long-context rate | — | — | Same rate |
| Price source | — | — | Median of 5 providers |
| Limits | |||
| Context window | 128,000 tokens | 32,768 tokens | 1,000,000 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens | 80,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | OpenApache 2.0 | OpenApache-2.0 |
| API model ID | — | — | — |
| API providers | — | — | 5 |
| Released | Jun 11, 2025 | May 20, 2025 | Jun 17, 2025 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Nemotron—
- Sarvam-M—
- MiniMax M1 80K$9.90
Which should you choose?
Which is better: Mistral Nemotron, Sarvam-M or MiniMax M1 80K?
MiniMax M1 80K is the better all-round choice, scoring 45/100 against Mistral Nemotron (25) and Sarvam-M (6). It leads on inputs & features and 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, Mistral Nemotron, Sarvam-M or MiniMax M1 80K?
MiniMax M1 80K is cheaper at $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 $0.963 per million tokens for MiniMax M1 80K versus . Mistral Nemotron and Sarvam-M has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mistral Nemotron has not been scored yet, Sarvam-M has not been scored yet and MiniMax M1 80K has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Nemotron, Sarvam-M and MiniMax M1 80K yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Sarvam-M does not support tool calling, which most coding agents need.
Which has the bigger context window?
MiniMax M1 80K has the largest context window at 1,000,000 tokens, against 128,000 for Mistral Nemotron and 32,768 for Sarvam-M. Maximum output per response: Mistral Nemotron up to 8,192, Sarvam-M up to 32,768, MiniMax M1 80K up to 80,000 tokens.
Which can read images, PDFs, audio or video?
Mistral Nemotron accepts text; Sarvam-M accepts text; MiniMax M1 80K accepts text. They handle the same number of input types.
Are any of these open source?
Sarvam-M and MiniMax M1 80K publishes its weights (Apache 2.0 and Apache-2.0) and can be self-hosted; Mistral Nemotron is proprietary.
Which is newer?
MiniMax M1 80K is the newest, released Jun 17, 2025. Mistral Nemotron came out Jun 11, 2025; Sarvam-M came out May 20, 2025.
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.
