Model comparison
Sarvam 30B vs Trinity-Large-Preview
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Sarvam 30B #169 (Estimated); Trinity-Large-Preview #79 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Sarvam 30B and Trinity-Large-Preview share 11 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Sarvam 30B; 7 to Trinity-Large-Preview.
Updated July 21, 2026- Shared results
- 11
- Sarvam 30B only
- 0
- Trinity-Large-Preview only
- 7
- Comparable categories
- 0 / 8
Benchmark data for Sarvam 30B and Trinity-Large-Preview is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Trinity-Large-Preview is priced at $0.25 input / $1.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Sarvam 30B. Trinity-Large-Preview has the larger context window at 512K, compared with 64K for Sarvam 30B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Sarvam 30B | Trinity-Large-Preview | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Sarvam 30B$0 input / $0 output | Trinity-Large-Preview$0.25 input / $1 output | Sarvam 30B has the lower combined listed price. |
| Generation speedtokens per second | Sarvam 30BNot available | Trinity-Large-PreviewNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Sarvam 30BNot available | Trinity-Large-PreviewNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Sarvam 30B64K | Trinity-Large-Preview512K | Trinity-Large-Preview lists the larger context window. |
Benchmark Deep Dive
Agentic3 benchmarks
Coding1 benchmarks
| Benchmark | Sarvam 30B | Trinity-Large-Preview | Result |
|---|---|---|---|
| AA-SciCodeSource | 19.2% | 36.1% | Trinity-Large-Preview leads |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | Sarvam 30B | Trinity-Large-Preview | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 6.6% | 24.5% | Trinity-Large-Preview leads |
| AA-GPQA DiamondSource | 63.3% | 75.2% | Trinity-Large-Preview leads |
| AA-HLESource | 7.0% | 14.7% | Trinity-Large-Preview leads |
| AA-Omniscience IndexSource | -72.0% | -44.2% | Trinity-Large-Preview leads |
| AA-Omniscience AccuracySource | 12.7% | 22.8% | Trinity-Large-Preview leads |
| AA-Omniscience Hallucination RateSource | 97.0% | 86.6% | Trinity-Large-Preview leads |
| MMLUSource | — | 87.2% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 75.2% | Not comparable |
| GPQA-DSource | — | 63.3% | Not comparable |
Math1 benchmarks
| Benchmark | Sarvam 30B | Trinity-Large-Preview | Result |
|---|---|---|---|
| AIME25 (Arcee)Source | — | 24.0% | Not comparable |
Multimodal1 benchmarks
| Benchmark | Sarvam 30B | Trinity-Large-Preview | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1165 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Sarvam 30B | Trinity-Large-Preview | Result |
|---|---|---|---|
| AA-IFBenchSource | 26.5% | 56.3% | Trinity-Large-Preview leads |
Frequently Asked Questions (3)
Can I compare Sarvam 30B and Trinity-Large-Preview on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Sarvam 30B and Trinity-Large-Preview today?
Sarvam 30B: $0.00 input / $0.00 output per 1M tokens Trinity-Large-Preview: $0.25 input / $1.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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