Sarvam-M vs Mistral Small 4
Mistral Small 4 comes out ahead, 56 to 6 on our weighted score, and it is the cheaper option too.
Sarvam AI
Sarvam-M
6/100- ECI—
- Price—
- Context33K
- Our pick
Mistral AIMistral Small 4
56/100- ECI—
- Price$0.15 / $0.60
- Context256K
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Make it a three-way comparison.
Mistral Small 4 is our pick
Mistral Small 4 is the better all-round choice, scoring 56/100 against 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 priceMistral Small 4Mistral Small 4 $0.263 per 1M tokens (3:1 blend) · Sarvam-M unpriced
- Longest contextMistral Small 4Mistral Small 4 256,000 · Sarvam-M 32,768 tokens
- Widest inputsMistral Small 4Sarvam-M: Text · Mistral Small 4: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Sarvam-M | Mistral Small 4 |
|---|---|---|---|
| Inputs & features | 60% | 10 | 70 |
| Context window | 40% | 0 | 36 |
| Overall | 100% | 6/100 | 56/100 |
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 | Sarvam-MSarvam AI | Mistral Small 4Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | — | $0.15 |
| Output | — | $0.60 |
| Cached input | — | $0.015 |
| Blended (3:1) | — | $0.263 |
| Long-context rate | — | Same rate |
| Price source | — | Official Mistral API |
| Limits | ||
| Context window | 32,768 tokens | 256,000 tokens (best) |
| Max output | 32,768 tokens | 256,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yeshigh |
| Tool calling | No | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | OpenApache 2.0 | Open |
| API model ID | — | mistral-small-2603 |
| API providers | — | 21 |
| Released | May 20, 2025 | Mar 16, 2026 |
| Knowledge cutoff | — | Jun 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Sarvam-M—
- Mistral Small 4$2.70
Which should you choose?
Which is better: Sarvam-M or Mistral Small 4?
Mistral Small 4 is the better all-round choice, scoring 56/100 against 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, Sarvam-M or Mistral Small 4?
Mistral Small 4 is cheaper at $0.15 input / $0.60 output per million tokens (official Mistral API price). . At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for Mistral Small 4 versus . Sarvam-M has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Sarvam-M has not been scored yet and Mistral Small 4 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Sarvam-M and Mistral Small 4 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?
Mistral Small 4 has the largest context window at 256,000 tokens, against 32,768 for Sarvam-M. Maximum output per response: Sarvam-M up to 32,768, Mistral Small 4 up to 256,000 tokens.
Which can read images, PDFs, audio or video?
Sarvam-M accepts text; Mistral Small 4 accepts text and images. Mistral Small 4 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Mistral Small 4 is the newest, released Mar 16, 2026. Sarvam-M came out May 20, 2025. Knowledge cutoff: Mistral Small 4 Jun 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.
