Model comparison
GPT-5 nano vs Kimi K2.6
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: GPT-5 nano unranked; Kimi K2.6 #11
Evidence parity. GPT-5 nano and Kimi K2.6 share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to GPT-5 nano; 58 to Kimi K2.6.
Updated July 14, 2026- Shared results
- 0
- GPT-5 nano only
- 0
- Kimi K2.6 only
- 58
- Comparable categories
- 0 / 8
Benchmark data for GPT-5 nano and Kimi K2.6 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for GPT-5 nano yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Kimi K2.6 is priced at $0.95 input / $4.00 output per 1M tokens, versus $0.05 input / $0.40 output per 1M tokens for GPT-5 nano. GPT-5 nano has the larger context window at 400K, compared with 256K for Kimi K2.6.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5 nano | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5 nano$0.05 input / $0.4 output | Kimi K2.6$0.95 input / $4 output | GPT-5 nano has the lower combined listed price. |
| Generation speedtokens per second | GPT-5 nano137 tok/s | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5 nano83.30 s | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5 nano400K | Kimi K2.6256K | GPT-5 nano lists the larger context window. |
Benchmark Deep Dive
Agentic20 benchmarks
| Benchmark | GPT-5 nano | Kimi K2.6 | 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% | Not comparable |
| 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 | — | 811 | Not comparable |
| AA EnterpriseOps-GymSource | — | 38.5% | Not comparable |
| AA ITBenchSource | — | 31.2% | Not comparable |
| AA Tau3 BankingSource | — | 20.6% | Not comparable |
Coding13 benchmarks
| Benchmark | GPT-5 nano | Kimi K2.6 | 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% | Not comparable |
| AA-SciCodeSource | — | 53.5% | Not comparable |
| AA Terminal-Bench 2.1Source | — | 65.9% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5 nano | Kimi K2.6 | Result |
|---|---|---|---|
| GPQASource | — | 90.5% | Not comparable |
| GPQA-DSource | — | 90.5% | Not comparable |
| HLESource | — | 34.7% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 44.2% | Not comparable |
| AA-GPQA DiamondSource | — | 91.1% | Not comparable |
| AA-HLESource | — | 35.9% | Not comparable |
| AA-Omniscience IndexSource | — | 6.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 32.8% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 39.3% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math5 benchmarks
Multimodal7 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5 nano | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 76.0% | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5 nano and Kimi K2.6 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 GPT-5 nano and Kimi K2.6 today?
GPT-5 nano: $0.05 input / $0.40 output per 1M tokens Kimi K2.6: $0.95 input / $4.00 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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