Model comparison
Claude 4 Sonnet vs Kimi K2.6
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Claude 4 Sonnet unranked; Kimi K2.6 #13
Evidence parity. Claude 4 Sonnet and Kimi K2.6 share 16 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Claude 4 Sonnet; 44 to Kimi K2.6.
Updated July 13, 2026- Shared results
- 16
- Claude 4 Sonnet only
- 1
- Kimi K2.6 only
- 44
- Comparable categories
- 1 / 8
Pick Kimi K2.6 if you want the stronger benchmark profile. Claude 4 Sonnet only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Kimi K2.6 is clearly ahead on the provisional aggregate, 74 to 49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude 4 Sonnet is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.6. That is roughly 3.8x on output cost alone. Kimi K2.6 is the reasoning model in the pair, while Claude 4 Sonnet is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Kimi K2.6 gives you the larger context window at 256K, compared with 200K for Claude 4 Sonnet.
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 | Claude 4 Sonnet | Δ | Kimi K2.6 |
|---|---|---|---|
| Coding | Claude 4 Sonnet72.7 | Margin← 0.1 | Kimi K2.672.6 |
| Agentic | Claude 4 SonnetNot measured | MarginNo overlap | Kimi K2.673.5 |
| Knowledge | Claude 4 SonnetNot measured | MarginNo overlap | Kimi K2.642.2 |
| Math | Claude 4 SonnetNot measured | MarginNo overlap | Kimi K2.667.1 |
| Multimodal | Claude 4 SonnetNot measured | MarginNo overlap | Kimi K2.679.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 72.7%B 80.2%Winner: Kimi K2.6Δ 7.5SWE-bench Verified: Claude 4 Sonnet scored 72.7%; Kimi K2.6 scored 80.2%. Kimi K2.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 4 Sonnet | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 4 Sonnet$3 input / $15 output | Kimi K2.6$0.95 input / $4 output | Kimi K2.6 has the lower combined listed price. |
| Generation speedtokens per second | Claude 4 Sonnet40 tok/s | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude 4 Sonnet1.33 s | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude 4 Sonnet200K | Kimi K2.6256K | Kimi K2.6 lists the larger context window. |
Benchmark Deep Dive
Agentic23 benchmarks
| Benchmark | Claude 4 Sonnet | Kimi K2.6 | Result |
|---|---|---|---|
| Tau2-TelecomSource | 52.3% | 95.9% | Kimi K2.6 leads |
| Gert LabsSource | 39.66% | 56.82% | Kimi K2.6 leads |
| JobBenchSource | 18.4% | — | Not comparable |
| 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 |
| GDPval-AASource | — | 34.5% | Not comparable |
| GDPval-AASource | — | 1190 | Not comparable |
| APEX-Agents-AASource | — | 28.5% | 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 |
CodingClaude 4 Sonnet wins13 benchmarks
| Benchmark | Claude 4 Sonnet | Kimi K2.6 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 72.7% | 80.2% | Kimi K2.6 leads |
| Terminal-Bench HardSource | 27.3% | 43.9% | Kimi K2.6 leads |
| AA-SciCodeSource | 37.3% | 53.5% | Kimi K2.6 leads |
| 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 |
| AA Terminal-Bench 2.1Source | — | 65.9% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude 4 Sonnet | Kimi K2.6 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.5% | 44.2% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 68.3% | 91.1% | Kimi K2.6 leads |
| AA-HLESource | 4.0% | 35.9% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | -9.2% | 6.4% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 22.4% | 32.8% | Kimi K2.6 leads |
| AA-Omniscience Hallucination RateSource | 40.8% | 39.3% | Kimi K2.6 leads |
| GPQASource | — | 90.5% | Not comparable |
| GPQA-DSource | — | 90.5% | Not comparable |
| HLESource | — | 34.7% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math5 benchmarks
Multimodal7 benchmarks
| Benchmark | Claude 4 Sonnet | Kimi K2.6 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 62.4% | 79.4% | Kimi K2.6 leads |
| Design Arena WebsiteSource | 1188 | 1318 | Kimi K2.6 leads |
| 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 |
Inst. Following1 benchmarks
| Benchmark | Claude 4 Sonnet | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | 45.4% | 76.0% | Kimi K2.6 leads |
Frequently Asked Questions (2)
Which is better, Claude 4 Sonnet or Kimi K2.6?
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 74 to 49. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 72.7% and 80.2%.
Which is better for coding, Claude 4 Sonnet or Kimi K2.6?
Claude 4 Sonnet has the edge for coding in this comparison, averaging 72.7 versus 72.6. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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