Model comparison
GPT-5.6 Sol vs Kimi K2.5
Head-to-head evidence from 25 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Kimi K2.5 share 25 comparable benchmark results. 5 of 8 categories are comparable. 21 results are unique to GPT-5.6 Sol; 38 to Kimi K2.5.
Updated July 23, 2026- Shared results
- 25
- GPT-5.6 Sol only
- 21
- Kimi K2.5 only
- 38
- Comparable categories
- 5 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 25 shared benchmark results across 7 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.6 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 59.66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol's sharpest advantage is in knowledge, where it averages 94.6 against 56.9. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 83.000% to 4.200%.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 10.0x on output cost alone. GPT-5.6 Sol is the reasoning model in the pair, while Kimi K2.5 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. GPT-5.6 Sol gives you the larger context window at 1M, compared with 256K for Kimi K2.5.
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 | GPT-5.6 Sol | Δ | Kimi K2.5 |
|---|---|---|---|
| Knowledge | GPT-5.6 Sol94.6 | Margin← 37.7 | Kimi K2.556.9 |
| Agentic | GPT-5.6 Sol92.0 | Margin← 37.0 | Kimi K2.555.0 |
| Math | GPT-5.6 Sol87.5 | Margin← 26.9 | Kimi K2.560.6 |
| Coding | GPT-5.6 Sol64.6 | Margin← 5.2 | Kimi K2.559.4 |
| Multimodal | GPT-5.6 Sol83.0 | Margin← 4.5 | Kimi K2.578.5 |
| Reasoning | GPT-5.6 SolNot measured | MarginNo overlap | Kimi K2.561.0 |
| Multilingual | GPT-5.6 SolNot measured | MarginNo overlap | Kimi K2.582.3 |
| Inst. Following | GPT-5.6 SolNot measured | MarginNo overlap | Kimi K2.593.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 83.000%B 4.200%Winner: GPT-5.6 SolΔ 78.8FrontierMath v2 (Tier 4): GPT-5.6 Sol scored 83.000%; Kimi K2.5 scored 4.200%. GPT-5.6 Sol wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 89.000%B 27.900%Winner: GPT-5.6 SolΔ 61.1FrontierMath v2 (Tiers 1-3): GPT-5.6 Sol scored 89.000%; Kimi K2.5 scored 27.900%. GPT-5.6 Sol wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 91.9%B 50.8%Winner: GPT-5.6 SolΔ 41.1Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Kimi K2.5 scored 50.8%. GPT-5.6 Sol wins this benchmark. - Source ↗
BrowseComp
AgenticA 92.2%B 60.6%Winner: GPT-5.6 SolΔ 31.6BrowseComp: GPT-5.6 Sol scored 92.2%; Kimi K2.5 scored 60.6%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.6%B 50.7%Winner: GPT-5.6 SolΔ 13.9SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Kimi K2.5 scored 50.7%. GPT-5.6 Sol wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.6 Sol | Kimi K2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Kimi K2.5$0.6 input / $3 output | Kimi K2.5 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Kimi K2.545 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Kimi K2.52.38 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Kimi K2.5256K | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins29 benchmarks
| Benchmark | GPT-5.6 Sol | Kimi K2.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | 50.8% | GPT-5.6 Sol leads |
| BrowseCompSource | 92.2% | 60.6% | GPT-5.6 Sol leads |
| OSWorld 2.0Source | 62.6% | — | Not comparable |
| CyberGymSource | 84.5% | — | Not comparable |
| ExploitGymSource | 33.7% | — | Not comparable |
| ToolathlonSource | 58% | 27.8% | GPT-5.6 Sol leads |
| AA Agentic IndexSource | 54.0% | 21.7% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 85.1% | 95.9% | Kimi K2.5 leads |
| GDPval-AASource | 61.8% | 25.4% | GPT-5.6 Sol leads |
| GDPval-AASource | 1736 | 1009 | GPT-5.6 Sol leads |
| AA BriefcaseSource | 1501 | — | Not comparable |
| AA ITBenchSource | 56.2% | — | Not comparable |
| AA Tau3 BankingSource | 33.0% | — | Not comparable |
| AA AutomationBenchSource | 51.2% | — | Not comparable |
| AA Harvey LABSource | 87.2% | — | Not comparable |
| terminalBenchHardSource | 65.9% | — | Not comparable |
| aaTerminalBench21Source | 88% | — | Not comparable |
| Claw-EvalSource | — | 52.3% | Not comparable |
| QwenClawBenchSource | — | 54.3% | Not comparable |
| τ³-bench resultsSource | — | 65.7% | Not comparable |
| DeepSearchQASource | — | 77.1% | Not comparable |
| DeepPlanningSource | — | 14.4% | Not comparable |
| MCP AtlasSource | — | 29.5% | Not comparable |
| MCP-TasksSource | — | 59.1% | Not comparable |
| WideResearchSource | — | 72.7% | Not comparable |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
| Gert LabsSource | — | 45.88% | Not comparable |
| ResearchClawBenchSource | — | 14.0% | Not comparable |
| JobBenchSource | — | 8.7% | Not comparable |
CodingGPT-5.6 Sol wins15 benchmarks
| Benchmark | GPT-5.6 Sol | Kimi K2.5 | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | 50.7% | GPT-5.6 Sol leads |
| Terminal-Bench 2.0Source | 91.9% | — | Not comparable |
| deepSweSource | 72.7% | — | Not comparable |
| FrontierCode 1.1 ExtendedSource | 60.6% | — | Not comparable |
| cursorBench32Source | 67.2% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 77.4% | 46.8% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 56.1% | 49.0% | GPT-5.6 Sol leads |
| SWE-bench VerifiedSource | — | 76.8% | Not comparable |
| SWE-bench Verified*Source | — | 70.8% | Not comparable |
| LiveCodeBench v6Source | — | 85.0% | Not comparable |
| SWE MultilingualSource | — | 73% | Not comparable |
| SWE-RebenchSource | — | 58.5% | Not comparable |
| React Native EvalsSource | — | 77.2% | Not comparable |
| SciCodeSource | — | 48.7% | Not comparable |
Reasoning5 benchmarks
KnowledgeGPT-5.6 Sol wins14 benchmarks
| Benchmark | GPT-5.6 Sol | Kimi K2.5 | Result |
|---|---|---|---|
| GPQASource | 94.6% | 87.6% | GPT-5.6 Sol leads |
| GPQA-DSource | 94.6% | 87.6% | GPT-5.6 Sol leads |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | 35.4% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 94.1% | 87.9% | GPT-5.6 Sol leads |
| AA-HLESource | 47.2% | 29.4% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 21.7% | -8.1% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 58.5% | 34.3% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 88.8% | 64.6% | Kimi K2.5 leads |
| SuperGPQASource | — | 69.2% | Not comparable |
| MMLU-ProSource | — | 87.1% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 87.1% | Not comparable |
| HLESource | — | 30.1% | Not comparable |
MathGPT-5.6 Sol wins10 benchmarks
| Benchmark | GPT-5.6 Sol | Kimi K2.5 | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 89% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 89.000% | 27.900% | GPT-5.6 Sol leads |
| FrontierMath v2 (Tier 4)Source | 83.000% | 4.200% | GPT-5.6 Sol leads |
| AIME 2025Source | — | 96.1% | Not comparable |
| AIME26Source | — | 95.8% | Not comparable |
| AIME25 (Arcee)Source | — | 96.3% | Not comparable |
| HMMT Feb 2025Source | — | 95.4% | Not comparable |
| HMMT Nov 2025Source | — | 91.1% | Not comparable |
| HMMT Feb 2026Source | — | 87.1% | Not comparable |
| MMAnswerBenchSource | — | 81.8% | Not comparable |
Multilingual2 benchmarks
MultimodalGPT-5.6 Sol wins7 benchmarks
| Benchmark | GPT-5.6 Sol | Kimi K2.5 | Result |
|---|---|---|---|
| MMMU-ProSource | 83% | 78.5% | GPT-5.6 Sol leads |
| MMMU-Pro w/ PythonSource | 84.6% | — | Not comparable |
| AA-MMMU-ProSource | 83.4% | 75.4% | GPT-5.6 Sol leads |
| Video-MMESource | — | 87.4% | Not comparable |
| MMVUSource | — | 80.4% | Not comparable |
| VideoMMMUSource | — | 86.6% | Not comparable |
| Design Arena WebsiteSource | — | 1279 | Not comparable |
Frequently Asked Questions (6)
Which is better, GPT-5.6 Sol or Kimi K2.5?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 59.66. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 83.000% and 4.200%.
Which is better for knowledge tasks, GPT-5.6 Sol or Kimi K2.5?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 56.9. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Sol or Kimi K2.5?
GPT-5.6 Sol has the edge for coding in this comparison, averaging 64.6 versus 59.4. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.6 Sol or Kimi K2.5?
GPT-5.6 Sol has the edge for math in this comparison, averaging 87.5 versus 60.6. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.6 Sol or Kimi K2.5?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 55. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.6 Sol or Kimi K2.5?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 78.5. Inside this category, AA-MMMU-Pro 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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