Sarvam-M vs Gemma 3n E2B IT vs Solar Pro 2
Solar Pro 2 comes out ahead, 26 to 21 and 6 on our weighted score, and it is the cheaper option too.
Sarvam AI
Sarvam-M
6/100- ECI—
- Price—
- Context33K
GoogleGemma 3n E2B IT
21/100- ECI—
- Price—
- Context33K
- Our pick
UpstageSolar Pro 2
26/100- ECI—
- Price$0.25 / $0.25
- Context66K
Solar Pro 2 is our pick
Solar Pro 2 is the better all-round choice, scoring 26/100 against Gemma 3n E2B IT (21) and Sarvam-M (6). It leads 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 priceSolar Pro 2Solar Pro 2 $0.25 per 1M tokens (3:1 blend) · Sarvam-M and Gemma 3n E2B IT unpriced
- Longest contextSolar Pro 2Solar Pro 2 65,536 · Sarvam-M 32,768 · Gemma 3n E2B IT 32,768 tokens
- Widest inputsGemma 3n E2B ITSarvam-M: Text · Gemma 3n E2B IT: Text, Images, Audio · Solar Pro 2: Text
- Self-hostingSarvam-M and Gemma 3n E2B ITPublishes downloadable weights (Apache 2.0 and Gemma Terms of Use)
| Measure | Weight | Sarvam-M | Gemma 3n E2B IT | Solar Pro 2 |
|---|---|---|---|---|
| Inputs & features | 60% | 10 | 35 | 35 |
| Context window | 40% | 0 | 0 | 12 |
| Overall | 100% | 6/100 | 21/100 | 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 | Gemma 3n E2B ITGoogle | 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 | 32,768 tokens | 65,536 tokens (best) |
| Max output | 32,768 tokens (best) | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yesminimal · high |
| Tool calling | No | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | OpenGemma Terms of Use | Proprietary |
| API model ID | — | — | solar-pro2 |
| API providers | — | — | 2 |
| Released | May 20, 2025 | Jun 26, 2025 | May 20, 2025 |
| Knowledge cutoff | — | Jun 2024 | 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—
- Gemma 3n E2B IT—
- Solar Pro 2$3.00
Which should you choose?
Which is better: Sarvam-M, Gemma 3n E2B IT or Solar Pro 2?
Solar Pro 2 is the better all-round choice, scoring 26/100 against Gemma 3n E2B IT (21) and Sarvam-M (6). It leads 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, Sarvam-M, Gemma 3n E2B IT 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 Gemma 3n E2B IT 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, Gemma 3n E2B IT 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, Gemma 3n E2B IT 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 and Gemma 3n E2B IT does not support tool calling, which most coding agents need.
Which has the bigger context window?
Solar Pro 2 has the largest context window at 65,536 tokens, against 32,768 for Sarvam-M and 32,768 for Gemma 3n E2B IT. Maximum output per response: Sarvam-M up to 32,768, Gemma 3n E2B IT up to 32,768, Solar Pro 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Sarvam-M accepts text; Gemma 3n E2B IT accepts text, images and audio; Solar Pro 2 accepts text. Gemma 3n E2B IT handles the widest range of inputs.
Are any of these open source?
Sarvam-M and Gemma 3n E2B IT publishes its weights (Apache 2.0 and Gemma Terms of Use) and can be self-hosted; Solar Pro 2 is proprietary.
Which is newer?
Gemma 3n E2B IT is the newest, released Jun 26, 2025. Sarvam-M came out May 20, 2025; Solar Pro 2 came out May 20, 2025. Knowledge cutoff: Gemma 3n E2B IT Jun 2024, 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.
