Gemini 2.5 Flash-Lite vs Sarvam 105B vs Solar Pro 2
Gemini 2.5 Flash-Lite comes out ahead, 83 to 52 and 51 on our weighted score, and it is the cheaper option too.
- Our pick
GoogleGemini 2.5 Flash-Lite
83/100- ECI—
- Price$0.10 / $0.40
- Context1.05M
Sarvam AI
Sarvam 105B
52/100- ECI—
- Price$0.158 / $0.632
- Context131K
UpstageSolar Pro 2
51/100- ECI—
- Price$0.25 / $0.25
- Context66K
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Sarvam 105B (52) and Solar Pro 2 (51). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. 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 priceGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite $0.175 · Solar Pro 2 $0.25 · Sarvam 105B $0.276 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Sarvam 105B 131,072 · Solar Pro 2 65,536 tokens
- Widest inputsGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Sarvam 105B: Text · Solar Pro 2: Text
- Self-hostingSarvam 105BPublishes downloadable weights
| Measure | Weight | Gemini 2.5 Flash-Lite | Sarvam 105B | Solar Pro 2 |
|---|---|---|---|---|
| Price | 50% | 82 | 73 | 75 |
| Inputs & features | 30% | 100 | 35 | 35 |
| Context window | 20% | 61 | 25 | 12 |
| Overall | 100% | 83/100 | 52/100 | 51/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 Flash-LiteGoogle | Sarvam 105BSarvam AI | Solar Pro 2Upstage |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.158 | $0.25 |
| Output | $0.40 | $0.632 | $0.25 (best) |
| Cached input | $0.01 (best) | $0.053 | — |
| Blended (3:1) | $0.175 (best) | $0.276 | $0.25 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Official Sarvam AI API | Official Upstage API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 131,072 tokens | 65,536 tokens |
| Max output | 65,536 tokens | 131,072 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yeslow · medium · high | Yesminimal · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gemini-2.5-flash-lite | sarvam-105b | solar-pro2 |
| API providers | 24 (best) | 3 | 2 |
| Released | Jun 17, 2025 | Feb 18, 2026 | May 20, 2025 |
| Knowledge cutoff | Jan 2025 | — | 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.
- Gemini 2.5 Flash-Lite$1.80
- Sarvam 105B$2.84
- Solar Pro 2$3.00
Which should you choose?
Which is better: Gemini 2.5 Flash-Lite, Sarvam 105B or Solar Pro 2?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 83/100 against Sarvam 105B (52) and Solar Pro 2 (51). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Gemini 2.5 Flash-Lite, Sarvam 105B or Solar Pro 2?
Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). Solar Pro 2 costs $0.25 input / $0.25 output per million tokens (official Upstage API price); Sarvam 105B costs $0.158 input / $0.632 output per million tokens (official Sarvam AI API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Gemini 2.5 Flash-Lite versus $0.25 for Solar Pro 2 (1.4× as much) and $0.276 for Sarvam 105B (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Flash-Lite has not been scored yet, Sarvam 105B 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 Gemini 2.5 Flash-Lite, Sarvam 105B and Solar Pro 2 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 131,072 for Sarvam 105B and 65,536 for Solar Pro 2. Maximum output per response: Gemini 2.5 Flash-Lite up to 65,536, Sarvam 105B up to 131,072, Solar Pro 2 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Sarvam 105B accepts text; Solar Pro 2 accepts text. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Sarvam 105B publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite and Solar Pro 2 is proprietary.
Which is newer?
Sarvam 105B is the newest, released Feb 18, 2026. Gemini 2.5 Flash-Lite came out Jun 17, 2025; Solar Pro 2 came out May 20, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 2025, 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.
