Model comparison
GPT-5.6 Luna vs Kimi K2.6
Head-to-head evidence from 27 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Luna #22 (Estimated); Kimi K2.6 #74 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Luna and Kimi K2.6 share 27 comparable benchmark results. 5 of 8 categories are comparable. 14 results are unique to GPT-5.6 Luna; 24 to Kimi K2.6.
Updated July 23, 2026- Shared results
- 27
- GPT-5.6 Luna only
- 14
- Kimi K2.6 only
- 24
- Comparable categories
- 5 / 8
Pick GPT-5.6 Luna if you want the stronger benchmark profile. Kimi K2.6 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 27 shared benchmark results across 6 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 Luna is clearly ahead on the BenchAlign aggregate, 67.17 to 56.79. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Luna's sharpest advantage is in knowledge, where it averages 92.3 against 42.2. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 58.500% to 14.580%. Kimi K2.6 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.6 Luna is also the more expensive model on tokens at $1.00 input / $6.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.6. GPT-5.6 Luna gives you the larger context window at 1M, 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 | GPT-5.6 Luna | Δ | Kimi K2.6 |
|---|---|---|---|
| Knowledge | GPT-5.6 Luna92.3 | Margin← 50.1 | Kimi K2.642.2 |
| Agentic | GPT-5.6 Luna84.1 | Margin← 10.6 | Kimi K2.673.5 |
| Math | GPT-5.6 Luna73.6 | Margin← 6.5 | Kimi K2.667.1 |
| Coding | GPT-5.6 Luna62.7 | Margin→ 1.7 | Kimi K2.664.4 |
| Multimodal | GPT-5.6 Luna78.4 | Margin→ 1.4 | Kimi K2.679.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 58.500%B 14.580%Winner: GPT-5.6 LunaΔ 43.9FrontierMath v2 (Tier 4): GPT-5.6 Luna scored 58.500%; Kimi K2.6 scored 14.580%. GPT-5.6 Luna wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 78.600%B 38.966%Winner: GPT-5.6 LunaΔ 39.6FrontierMath v2 (Tiers 1-3): GPT-5.6 Luna scored 78.600%; Kimi K2.6 scored 38.966%. GPT-5.6 Luna wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 84.7%B 66.7%Winner: GPT-5.6 LunaΔ 18Terminal-Bench 2.0: GPT-5.6 Luna scored 84.7%; Kimi K2.6 scored 66.7%. GPT-5.6 Luna wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 62.7%B 58.6%Winner: GPT-5.6 LunaΔ 4.1SWE-bench Pro: GPT-5.6 Luna scored 62.7%; Kimi K2.6 scored 58.6%. GPT-5.6 Luna wins this benchmark. - Source ↗
GPQA
KnowledgeA 92.3%B 90.5%Winner: GPT-5.6 LunaΔ 1.8GPQA: GPT-5.6 Luna scored 92.3%; Kimi K2.6 scored 90.5%. GPT-5.6 Luna wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.6 Luna | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Luna$1 input / $6 output | Kimi K2.6$0.95 input / $4 output | Kimi K2.6 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 LunaNot available | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 LunaNot available | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Luna1M | Kimi K2.6256K | GPT-5.6 Luna lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.6 Luna wins24 benchmarks
| Benchmark | GPT-5.6 Luna | Kimi K2.6 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 84.7% | 66.7% | GPT-5.6 Luna leads |
| BrowseCompSource | 83.3% | 83.2% | GPT-5.6 Luna leads |
| OSWorld 2.0Source | 45.6% | 4.6% | GPT-5.6 Luna leads |
| CyberGymSource | 77.9% | — | Not comparable |
| ExploitGymSource | 12.4% | — | Not comparable |
| ToolathlonSource | 53.4% | 50% | GPT-5.6 Luna leads |
| AA Agentic IndexSource | 45.6% | 30.3% | GPT-5.6 Luna leads |
| GDPval-AASource | 54.2% | 34.5% | GPT-5.6 Luna leads |
| GDPval-AASource | 1584 | 1189 | GPT-5.6 Luna leads |
| AA Harvey LABSource | 87.9% | — | Not comparable |
| AA ITBenchSource | 40.3% | — | Not comparable |
| AA Tau3 BankingSource | 27.2% | — | Not comparable |
| AA AutomationBenchSource | 42.2% | — | Not comparable |
| aaTerminalBench21Source | 80.9% | — | Not comparable |
| APEX-Agents-AASource | 35.8% | 28.5% | GPT-5.6 Luna leads |
| OSWorld-VerifiedSource | — | 73.1% | Not comparable |
| MCP AtlasSource | — | 55.9% | Not comparable |
| Claw-EvalSource | — | 62.3% | Not comparable |
| DeepSearchQASource | — | 92.5% | Not comparable |
| WideResearchSource | — | 80.8% | Not comparable |
| τ²-bench resultsSource | — | 95.9% | Not comparable |
| Gert LabsSource | — | 56.82% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
| terminalBenchHardSource | — | 43.9% | Not comparable |
CodingKimi K2.6 wins13 benchmarks
| Benchmark | GPT-5.6 Luna | Kimi K2.6 | Result |
|---|---|---|---|
| SWE-bench ProSource | 62.7% | 58.6% | GPT-5.6 Luna leads |
| Terminal-Bench 2.0Source | 84.7% | 66.7% | GPT-5.6 Luna leads |
| deepSweSource | 67.2% | — | Not comparable |
| FrontierCode 1.1 ExtendedSource | 55.1% | — | Not comparable |
| cursorBench32Source | 61.1% | — | Not comparable |
| AA Coding IndexSource | 71.5% | 61.8% | GPT-5.6 Luna leads |
| AA-SciCodeSource | 52.5% | 53.5% | Kimi K2.6 leads |
| SWE-bench VerifiedSource | — | 80.2% | Not comparable |
| LiveCodeBench v6Source | — | 89.6% | Not comparable |
| SWE MultilingualSource | — | 76.7% | Not comparable |
| SciCodeSource | — | 52.2% | Not comparable |
| Vibe Code BenchSource | — | 37.89% | Not comparable |
| cursorBench31Source | — | 47.6% | Not comparable |
Reasoning3 benchmarks
KnowledgeGPT-5.6 Luna wins11 benchmarks
| Benchmark | GPT-5.6 Luna | Kimi K2.6 | Result |
|---|---|---|---|
| GPQASource | 92.3% | 90.5% | GPT-5.6 Luna leads |
| GPQA-DSource | 92.3% | 90.5% | GPT-5.6 Luna leads |
| HealthBench ProfessionalSource | 55.7% | — | Not comparable |
| HealthBench HardSource | 32.0% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 51.2% | 44.2% | GPT-5.6 Luna leads |
| AA-GPQA DiamondSource | 91.1% | 91.1% | Tie |
| AA-HLESource | 37.2% | 35.9% | GPT-5.6 Luna leads |
| AA-Omniscience IndexSource | -11.2% | 6.4% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 41.5% | 32.8% | GPT-5.6 Luna leads |
| AA-Omniscience Hallucination RateSource | 90.1% | 39.3% | Kimi K2.6 leads |
| HLESource | — | 34.7% | Not comparable |
MathGPT-5.6 Luna wins6 benchmarks
| Benchmark | GPT-5.6 Luna | Kimi K2.6 | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 78.6% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 78.600% | 38.966% | GPT-5.6 Luna leads |
| FrontierMath v2 (Tier 4)Source | 58.500% | 14.580% | GPT-5.6 Luna leads |
| AIME26Source | — | 96.4% | Not comparable |
| HMMT Feb 2026Source | — | 92.7% | Not comparable |
| MMAnswerBenchSource | — | 86.0% | Not comparable |
MultimodalKimi K2.6 wins7 benchmarks
| Benchmark | GPT-5.6 Luna | Kimi K2.6 | Result |
|---|---|---|---|
| MMMU-ProSource | 78.4% | 79.4% | Kimi K2.6 leads |
| MMMU-Pro w/ PythonSource | 79.5% | 80.1% | Kimi K2.6 leads |
| AA-MMMU-ProSource | 78.6% | 79.4% | Kimi K2.6 leads |
| CharXivSource | — | 80.4% | Not comparable |
| MathVisionSource | — | 87.4% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| Design Arena WebsiteSource | — | 1306 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Luna | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 76.0% | Not comparable |
Frequently Asked Questions (6)
Which is better, GPT-5.6 Luna or Kimi K2.6?
GPT-5.6 Luna is ahead on BenchLM's BenchAlign leaderboard, 67.17 to 56.79. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 58.500% and 14.580%.
Which is better for knowledge tasks, GPT-5.6 Luna or Kimi K2.6?
GPT-5.6 Luna has the edge for knowledge tasks in this comparison, averaging 92.3 versus 42.2. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Luna or Kimi K2.6?
Kimi K2.6 has the edge for coding in this comparison, averaging 64.4 versus 62.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.6 Luna or Kimi K2.6?
GPT-5.6 Luna has the edge for math in this comparison, averaging 73.6 versus 67.1. 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 Luna or Kimi K2.6?
GPT-5.6 Luna has the edge for agentic tasks in this comparison, averaging 84.1 versus 73.5. 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 Luna or Kimi K2.6?
Kimi K2.6 has the edge for multimodal and grounded tasks in this comparison, averaging 79.8 versus 78.4. Inside this category, 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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