Trinity Large Preview vs Sarvam 105B
Trinity Large Preview comes out ahead, 34 to 31 on our weighted score.
- Our pick
Arcee AI
Trinity Large Preview
34/100- ECI—
- Price—
- Context524K
Sarvam AI
Sarvam 105B
31/100- ECI—
- Price$0.047 / $0.186
- Context131K
Add a model
Make it a three-way comparison.
Trinity Large Preview is our pick
Trinity Large Preview is the better all-round choice, scoring 34/100 against Sarvam 105B (31). It leads on context window. Sarvam 105B wins on inputs & features. 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 priceSarvam 105BSarvam 105B $0.082 per 1M tokens (3:1 blend) · Trinity Large Preview unpriced
- Longest contextTrinity Large PreviewTrinity Large Preview 524,288 · Sarvam 105B 131,072 tokens
- Widest inputsSame inputsTrinity Large Preview: Text · Sarvam 105B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Trinity Large Preview | Sarvam 105B |
|---|---|---|---|
| Inputs & features | 60% | 25 | 35 |
| Context window | 40% | 49 | 24 |
| Overall | 100% | 34/100 | 31/100 |
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 105BSarvam AI | |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | — | $0.047 |
| Output | — | $0.186 |
| Cached input | — | — |
| Blended (3:1) | — | $0.082 |
| Long-context rate | — | Same rate |
| Price source | — | Median of 2 providers |
| Limits | ||
| Context window | 524,288 tokens (best) | 131,072 tokens |
| Max output | 262,144 tokens (best) | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes · low · medium · high |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenOpenMDW-1.1 | Open |
| API model ID | — | sarvam-105b |
| API providers | 1 | 3 (best) |
| Released | Jan 27, 2026 | Sep 1, 2025 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Trinity Large Preview—
- Sarvam 105B$0.842
Which should you choose?
Which is better: Trinity Large Preview or Sarvam 105B?
Trinity Large Preview is the better all-round choice, scoring 34/100 against Sarvam 105B (31). It leads on context window. Sarvam 105B wins on inputs & features. 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, Trinity Large Preview or Sarvam 105B?
Sarvam 105B is cheaper at $0.047 input / $0.186 output per million tokens (median across 2 API providers). . At a typical mix of three input tokens to one output token, that is $0.082 per million tokens for Sarvam 105B versus . Trinity Large Preview has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Trinity Large Preview has not been scored yet and Sarvam 105B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Trinity Large Preview and Sarvam 105B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Trinity Large Preview has the largest context window at 524,288 tokens, against 131,072 for Sarvam 105B. Maximum output per response: Trinity Large Preview up to 262,144, Sarvam 105B up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Trinity Large Preview accepts text; Sarvam 105B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (OpenMDW-1.1), so you can self-host them.
Which is newer?
Trinity Large Preview is the newest, released Jan 27, 2026. Sarvam 105B came out Sep 1, 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 Oct 4, 2026.