Sarvam-M vs Mistral Nemotron vs Solar Pro 2
Too close to call on our weighted score (Solar Pro 2 26, Mistral Nemotron 25, Sarvam-M 6). The right pick depends on what you value most.
Sarvam AI
Sarvam-M
6/100- ECI—
- Price—
- Context33K
NVIDIAMistral Nemotron
25/100- ECI—
- Price—
- Context128K
UpstageSolar Pro 2
26/100- ECI—
- Price$0.25 / $0.25
- Context66K
Too close to call
It is close. Our weighted score puts them within 1 points (Solar Pro 2 26/100, Mistral Nemotron 25/100, Sarvam-M 6/100), so choose by what matters most for your work: Solar Pro 2 on price and Mistral Nemotron 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 priceSolar Pro 2Solar Pro 2 $0.25 per 1M tokens (3:1 blend) · Sarvam-M and Mistral Nemotron unpriced
- Longest contextMistral NemotronMistral Nemotron 128,000 · Solar Pro 2 65,536 · Sarvam-M 32,768 tokens
- Widest inputsSame inputsSarvam-M: Text · Mistral Nemotron: Text · Solar Pro 2: Text
- Self-hostingSarvam-MPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Sarvam-M | Mistral Nemotron | Solar Pro 2 |
|---|---|---|---|---|
| Inputs & features | 60% | 10 | 25 | 35 |
| Context window | 40% | 0 | 24 | 12 |
| Overall | 100% | 6/100 | 25/100 | 26/100 |
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 NemotronNVIDIA | Solar Pro 2Upstage |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | — | $0.25 |
| Output | — | — | $0.25 |
| Cached input | — | — | — |
| Blended (3:1) | — | — | $0.25 |
| Long-context rate | — | — | Same rate |
| Price source | — | — | Official Upstage API |
| Limits | |||
| Context window | 32,768 tokens | 128,000 tokens (best) | 65,536 tokens |
| Max output | 32,768 tokens (best) | 8,192 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yesminimal · high |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Proprietary | Proprietary |
| API model ID | — | — | solar-pro2 |
| API providers | — | — | 2 |
| Released | May 20, 2025 | Jun 11, 2025 | May 20, 2025 |
| Knowledge cutoff | — | — | Mar 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 Nemotron—
- Solar Pro 2$3.00
Which should you choose?
Which is better: Sarvam-M, Mistral Nemotron or Solar Pro 2?
It is close. Our weighted score puts them within 1 points (Solar Pro 2 26/100, Mistral Nemotron 25/100, Sarvam-M 6/100), so choose by what matters most for your work: Solar Pro 2 on price and Mistral Nemotron 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, Sarvam-M, Mistral Nemotron or Solar Pro 2?
Solar Pro 2 is cheaper at $0.25 input / $0.25 output per million tokens (official Upstage API price). . At a typical mix of three input tokens to one output token, that is $0.25 per million tokens for Solar Pro 2 versus . Sarvam-M and Mistral Nemotron has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Sarvam-M has not been scored yet, Mistral Nemotron has not been scored yet and Solar Pro 2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Sarvam-M, Mistral Nemotron and Solar Pro 2 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 Nemotron has the largest context window at 128,000 tokens, against 65,536 for Solar Pro 2 and 32,768 for Sarvam-M. Maximum output per response: Sarvam-M up to 32,768, Mistral Nemotron up to 8,192, Solar Pro 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Sarvam-M accepts text; Mistral Nemotron accepts text; Solar Pro 2 accepts text. They handle the same number of input types.
Are any of these open source?
Sarvam-M publishes its weights (Apache 2.0) and can be self-hosted; Mistral Nemotron and Solar Pro 2 is proprietary.
Which is newer?
Mistral Nemotron is the newest, released Jun 11, 2025. Sarvam-M came out May 20, 2025; Solar Pro 2 came out May 20, 2025. Knowledge cutoff: Solar Pro 2 Mar 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.
