Sarvam-M vs Solar Pro 2 vs Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 comes out ahead, 72 to 26 and 6 on our weighted score, though Solar Pro 2 is 13× cheaper per token.
Sarvam AI
Sarvam-M
6/100- ECI—
- Price—
- Context33K
UpstageSolar Pro 2
26/100- ECI—
- Price$0.25 / $0.25
- Context66K
- Our pick
GoogleGemini 2.5 Pro Preview 06-05
72/100- ECI—
- Price$1.22 / $9.75
- Context1.05M
Gemini 2.5 Pro Preview 06-05 is our pick
Gemini 2.5 Pro Preview 06-05 is the better all-round choice, scoring 72/100 against Solar Pro 2 (26) 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 priceSolar Pro 2Solar Pro 2 $0.25 · Gemini 2.5 Pro Preview 06-05 $3.35 per 1M tokens (3:1 blend) · Sarvam-M unpriced
- Longest contextGemini 2.5 Pro Preview 06-05Gemini 2.5 Pro Preview 06-05 1,048,576 · Solar Pro 2 65,536 · Sarvam-M 32,768 tokens
- Widest inputsGemini 2.5 Pro Preview 06-05Sarvam-M: Text · Solar Pro 2: Text · Gemini 2.5 Pro Preview 06-05: Text, Images, PDFs, Audio
- Self-hostingSarvam-MPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Sarvam-M | Solar Pro 2 | Gemini 2.5 Pro Preview 06-05 |
|---|---|---|---|---|
| Inputs & features | 60% | 10 | 35 | 80 |
| Context window | 40% | 0 | 12 | 61 |
| Overall | 100% | 6/100 | 26/100 | 72/100 |
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 | Solar Pro 2Upstage | Gemini 2.5 Pro Preview 06-05Google |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $0.25 (best) | $1.22 |
| Output | — | $0.25 (best) | $9.75 |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.25 (best) | $3.35 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Upstage API | Median of 4 providers |
| Limits | |||
| Context window | 32,768 tokens | 65,536 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 8,192 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | Yes |
| Video | No | No | No |
| Reasoning | Yes | Yesminimal · high | Yes |
| 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 | 4 (best) |
| Released | May 20, 2025 | May 20, 2025 | Jun 5, 2025 |
| Knowledge cutoff | — | Mar 2025 | Jan 31, 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—
- Solar Pro 2$3.00
- Gemini 2.5 Pro Preview 06-05$31.69
Which should you choose?
Which is better: Sarvam-M, Solar Pro 2 or Gemini 2.5 Pro Preview 06-05?
Gemini 2.5 Pro Preview 06-05 is the better all-round choice, scoring 72/100 against Solar Pro 2 (26) 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, Sarvam-M, Solar Pro 2 or Gemini 2.5 Pro Preview 06-05?
Solar Pro 2 is cheaper at $0.25 input / $0.25 output per million tokens (official Upstage API price). Gemini 2.5 Pro Preview 06-05 costs $1.22 input / $9.75 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.25 per million tokens for Solar Pro 2 versus $3.35 for Gemini 2.5 Pro Preview 06-05 (13× as much). Sarvam-M 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, Solar Pro 2 has not been scored yet and Gemini 2.5 Pro Preview 06-05 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Sarvam-M, Solar Pro 2 and Gemini 2.5 Pro Preview 06-05 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?
Gemini 2.5 Pro Preview 06-05 has the largest context window at 1,048,576 tokens, against 65,536 for Solar Pro 2 and 32,768 for Sarvam-M. Maximum output per response: Sarvam-M up to 32,768, Solar Pro 2 up to 8,192, Gemini 2.5 Pro Preview 06-05 up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Sarvam-M accepts text; Solar Pro 2 accepts text; Gemini 2.5 Pro Preview 06-05 accepts text, images, PDFs and audio. Gemini 2.5 Pro Preview 06-05 handles the widest range of inputs.
Are any of these open source?
Sarvam-M publishes its weights (Apache 2.0) and can be self-hosted; Solar Pro 2 and Gemini 2.5 Pro Preview 06-05 is proprietary.
Which is newer?
Gemini 2.5 Pro Preview 06-05 is the newest, released Jun 5, 2025. Sarvam-M came out May 20, 2025; Solar Pro 2 came out May 20, 2025. Knowledge cutoff: Solar Pro 2 Mar 2025, Gemini 2.5 Pro Preview 06-05 Jan 31, 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.
