Model comparison
GPT-5.5 vs Kanana Nano
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.5 #9 (Estimated); Kanana Nano unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.5 and Kanana Nano share 0 comparable benchmark results. 0 of 8 categories are comparable. 57 results are unique to GPT-5.5; 0 to Kanana Nano.
Updated July 22, 2026- Shared results
- 0
- GPT-5.5 only
- 57
- Kanana Nano only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.5 and Kanana Nano 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 Kanana Nano yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
GPT-5.5 has the larger context window at 1M, compared with 64K for Kanana Nano.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.5 | Kanana Nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.5$5 input / $30 output | Kanana NanoNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.5Not available | Kanana NanoNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.5Not available | Kanana NanoNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.51M | Kanana Nano64K | GPT-5.5 lists the larger context window. |
Benchmark Deep Dive
Agentic24 benchmarks
| Benchmark | GPT-5.5 | Kanana Nano | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 82% | — | Not comparable |
| CyberGymSource | 81.8% | — | Not comparable |
| BrowseCompSource | 84.4% | — | Not comparable |
| OSWorld-VerifiedSource | 78.7% | — | Not comparable |
| MCP AtlasSource | 75.3% | — | Not comparable |
| ToolathlonSource | 55.6% | — | Not comparable |
| τ²-bench resultsSource | 93.9% | — | Not comparable |
| AA Agentic IndexSource | 44.9% | — | Not comparable |
| APEX-Agents-AASource | 37.7% | — | Not comparable |
| GDPval-AASource | 49.5% | — | Not comparable |
| GDPval-AASource | 1490 | — | Not comparable |
| Gert LabsSource | 72.93% | — | Not comparable |
| ResearchClawBenchSource | 17.0% | — | Not comparable |
| OSWorld 2.0Source | 13.0% | — | Not comparable |
| JobBenchSource | 42.7% | — | Not comparable |
| ExploitGymSource | 13.4% | — | Not comparable |
| AA BriefcaseSource | 1154 | — | Not comparable |
| AA AutomationBenchSource | 42.1% | — | Not comparable |
| AA EnterpriseOps-GymSource | 46.6% | — | Not comparable |
| AA Harvey LABSource | 86.3% | — | Not comparable |
| AA ITBenchSource | 45.8% | — | Not comparable |
| AA Tau3 BankingSource | 31.3% | — | Not comparable |
| terminalBenchHardSource | 60.6% | — | Not comparable |
| aaTerminalBench21Source | 84.3% | — | Not comparable |
Coding9 benchmarks
| Benchmark | GPT-5.5 | Kanana Nano | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.6% | — | Not comparable |
| Terminal-Bench 2.0Source | 82.0% | — | Not comparable |
| Vibe Code BenchSource | 69.85% | — | Not comparable |
| React Native EvalsSource | 84.7% | — | Not comparable |
| cursorBench31Source | 59.2% | — | Not comparable |
| cursorBench32Source | 58.4% | — | Not comparable |
| AA Coding IndexSource | 74.9% | — | Not comparable |
| AA-SciCodeSource | 56.1% | — | Not comparable |
| FrontierCode 1.1 MainSource | 43.0% | — | Not comparable |
Reasoning5 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5.5 | Kanana Nano | Result |
|---|---|---|---|
| GPQASource | 93.6% | — | Not comparable |
| GPQA-DSource | 93.6% | — | Not comparable |
| HLESource | 52.2% | — | Not comparable |
| HLE w/o toolsSource | 41.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 54.8% | — | Not comparable |
| AA-GPQA DiamondSource | 93.5% | — | Not comparable |
| AA-HLESource | 44.3% | — | Not comparable |
| AA-Omniscience IndexSource | 20.1% | — | Not comparable |
| AA-Omniscience AccuracySource | 56.9% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 85.5% | — | Not comparable |
Math3 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.5 | Kanana Nano | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5.5 and Kanana Nano 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-5.5 and Kanana Nano today?
GPT-5.5: $5.00 input / $30.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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