Model comparison
Kimi K2.6 vs Sarvam 30B
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Kimi K2.6 #13; Sarvam 30B unranked
Evidence parity. Kimi K2.6 and Sarvam 30B share 12 comparable benchmark results. 0 of 8 categories are comparable. 48 results are unique to Kimi K2.6; 0 to Sarvam 30B.
Updated July 13, 2026- Shared results
- 12
- Kimi K2.6 only
- 48
- Sarvam 30B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Kimi K2.6 and Sarvam 30B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 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.
Kimi K2.6 is priced at $0.95 input / $4.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Sarvam 30B. Kimi K2.6 has the larger context window at 256K, 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.
| Category | Kimi K2.6 | Δ | Sarvam 30B |
|---|---|---|---|
| Agentic | Kimi K2.673.5 | MarginNo overlap | Sarvam 30BNot measured |
| Coding | Kimi K2.672.6 | MarginNo overlap | Sarvam 30BNot measured |
| Knowledge | Kimi K2.642.2 | MarginNo overlap | Sarvam 30BNot measured |
| Math | Kimi K2.667.1 | MarginNo overlap | Sarvam 30BNot measured |
| Multimodal | Kimi K2.679.8 | MarginNo overlap | Sarvam 30BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.6 | Sarvam 30B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.6$0.95 input / $4 output | Sarvam 30B$0 input / $0 output | Sarvam 30B has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.6Not available | Sarvam 30BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.6Not available | Sarvam 30BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.6256K | Sarvam 30B64K | Kimi K2.6 lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | Kimi K2.6 | Sarvam 30B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 66.7% | — | Not comparable |
| BrowseCompSource | 83.2% | — | Not comparable |
| OSWorld-VerifiedSource | 73.1% | — | Not comparable |
| ToolathlonSource | 50% | — | Not comparable |
| MCP AtlasSource | 55.9% | — | Not comparable |
| Claw-EvalSource | 62.3% | — | Not comparable |
| DeepSearchQASource | 92.5% | — | Not comparable |
| WideResearchSource | 80.8% | — | Not comparable |
| AA Agentic IndexSource | 30.3% | — | Not comparable |
| Tau2-TelecomSource | 95.9% | 34.5% | Kimi K2.6 leads |
| GDPval-AASource | 34.5% | — | Not comparable |
| GDPval-AASource | 1190 | — | Not comparable |
| APEX-Agents-AASource | 28.5% | — | Not comparable |
| Gert LabsSource | 56.82% | — | Not comparable |
| ResearchClawBenchSource | 18.0% | — | Not comparable |
| OSWorld 2.0Source | 4.6% | — | Not comparable |
| AA BriefcaseSource | 809 | — | Not comparable |
| AA AutomationBenchSource | 19.6% | — | Not comparable |
| AA EnterpriseOps-GymSource | 38.5% | — | Not comparable |
| AA Harvey LABSource | 0.0% | — | Not comparable |
| AA ITBenchSource | 31.2% | — | Not comparable |
| AA Tau3 BankingSource | 20.6% | — | Not comparable |
Coding13 benchmarks
| Benchmark | Kimi K2.6 | Sarvam 30B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.2% | — | Not comparable |
| LiveCodeBenchSource | 89.6% | — | Not comparable |
| LiveCodeBench v6Source | 89.6% | — | Not comparable |
| SWE-bench ProSource | 58.6% | — | Not comparable |
| SWE MultilingualSource | 76.7% | — | Not comparable |
| SciCodeSource | 52.2% | — | Not comparable |
| Terminal-Bench 2.0Source | 66.7% | — | Not comparable |
| Vibe Code BenchSource | 37.89% | — | Not comparable |
| cursorBench31Source | 47.6% | — | Not comparable |
| AA Coding IndexSource | 61.8% | — | Not comparable |
| Terminal-Bench HardSource | 43.9% | 2.3% | Kimi K2.6 leads |
| AA-SciCodeSource | 53.5% | 19.2% | Kimi K2.6 leads |
| AA Terminal-Bench 2.1Source | 65.9% | — | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Kimi K2.6 | Sarvam 30B | Result |
|---|---|---|---|
| GPQASource | 90.5% | — | Not comparable |
| GPQA-DSource | 90.5% | — | Not comparable |
| HLESource | 34.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 44.2% | 6.6% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 91.1% | 63.3% | Kimi K2.6 leads |
| AA-HLESource | 35.9% | 7.0% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | 6.4% | -72.0% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 32.8% | 12.7% | Kimi K2.6 leads |
| AA-Omniscience Hallucination RateSource | 39.3% | 97.0% | Kimi K2.6 leads |
| AA Openness IndexSource | 33.3% | — | Not comparable |
Math5 benchmarks
Multimodal7 benchmarks
Inst. Following1 benchmarks
| Benchmark | Kimi K2.6 | Sarvam 30B | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.0% | 26.5% | Kimi K2.6 leads |
Frequently Asked Questions (3)
Can I compare Kimi K2.6 and Sarvam 30B 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 Kimi K2.6 and Sarvam 30B today?
Kimi K2.6: $0.95 input / $4.00 output per 1M tokens Sarvam 30B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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