Model comparison
Kimi K2.6 vs Trinity-Large-Thinking
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Kimi K2.6 #13; Trinity-Large-Thinking unranked
Evidence parity. Kimi K2.6 and Trinity-Large-Thinking share 15 comparable benchmark results. 0 of 8 categories are comparable. 45 results are unique to Kimi K2.6; 3 to Trinity-Large-Thinking.
Updated July 13, 2026- Shared results
- 15
- Kimi K2.6 only
- 45
- Trinity-Large-Thinking only
- 3
- Comparable categories
- 0 / 8
Benchmark data for Kimi K2.6 and Trinity-Large-Thinking is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 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 $0.25 input / $0.90 output per 1M tokens for Trinity-Large-Thinking. Trinity-Large-Thinking has the larger context window at 512K, compared with 256K for Kimi K2.6.
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 | Trinity-Large-Thinking |
|---|---|---|---|
| Agentic | Kimi K2.673.5 | MarginNo overlap | Trinity-Large-ThinkingNot measured |
| Coding | Kimi K2.672.6 | MarginNo overlap | Trinity-Large-ThinkingNot measured |
| Knowledge | Kimi K2.642.2 | MarginNo overlap | Trinity-Large-ThinkingNot measured |
| Math | Kimi K2.667.1 | MarginNo overlap | Trinity-Large-ThinkingNot measured |
| Multimodal | Kimi K2.679.8 | MarginNo overlap | Trinity-Large-ThinkingNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.6 | Trinity-Large-Thinking | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.6$0.95 input / $4 output | Trinity-Large-Thinking$0.25 input / $0.9 output | Trinity-Large-Thinking has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.6Not available | Trinity-Large-ThinkingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.6Not available | Trinity-Large-ThinkingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.6256K | Trinity-Large-Thinking512K | Trinity-Large-Thinking lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | Kimi K2.6 | Trinity-Large-Thinking | 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% | 90.1% | 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% | 32.55% | Kimi K2.6 leads |
| 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 |
Coding14 benchmarks
| Benchmark | Kimi K2.6 | Trinity-Large-Thinking | 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% | 22.7% | Kimi K2.6 leads |
| AA-SciCodeSource | 53.5% | 36.1% | Kimi K2.6 leads |
| AA Terminal-Bench 2.1Source | 65.9% | — | Not comparable |
| SWE-bench Verified*Source | — | 63.2% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Kimi K2.6 | Trinity-Large-Thinking | Result |
|---|---|---|---|
| GPQASource | 90.5% | — | Not comparable |
| GPQA-DSource | 90.5% | 76.3% | Kimi K2.6 leads |
| HLESource | 34.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 44.2% | 24.5% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 91.1% | 75.2% | Kimi K2.6 leads |
| AA-HLESource | 35.9% | 14.7% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | 6.4% | -44.2% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 32.8% | 22.8% | Kimi K2.6 leads |
| AA-Omniscience Hallucination RateSource | 39.3% | 86.6% | Kimi K2.6 leads |
| AA Openness IndexSource | 33.3% | — | Not comparable |
| MMLU-Pro (Arcee)Source | — | 83.4% | Not comparable |
Math6 benchmarks
| Benchmark | Kimi K2.6 | Trinity-Large-Thinking | Result |
|---|---|---|---|
| AIME26Source | 96.4% | — | Not comparable |
| HMMT Feb 2026Source | 92.7% | — | Not comparable |
| MMAnswerBenchSource | 86.0% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 38.966% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 14.580% | — | Not comparable |
| AIME25 (Arcee)Source | — | 96.3% | Not comparable |
Multimodal7 benchmarks
| Benchmark | Kimi K2.6 | Trinity-Large-Thinking | Result |
|---|---|---|---|
| MMMU-ProSource | 79.4% | — | Not comparable |
| MMMU-Pro w/ PythonSource | 80.1% | — | Not comparable |
| CharXivSource | 80.4% | — | Not comparable |
| MathVisionSource | 87.4% | — | Not comparable |
| V*Source | 96.9% | — | Not comparable |
| AA-MMMU-ProSource | 79.4% | — | Not comparable |
| Design Arena WebsiteSource | 1318 | 1177 | Kimi K2.6 leads |
Inst. Following1 benchmarks
| Benchmark | Kimi K2.6 | Trinity-Large-Thinking | Result |
|---|---|---|---|
| AA-IFBenchSource | 76.0% | 56.3% | Kimi K2.6 leads |
Frequently Asked Questions (3)
Can I compare Kimi K2.6 and Trinity-Large-Thinking 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 Trinity-Large-Thinking today?
Kimi K2.6: $0.95 input / $4.00 output per 1M tokens Trinity-Large-Thinking: $0.25 input / $0.90 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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