Model comparison
GPT-5.5 vs GPT-OSS 20B
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.5 #9 (Estimated); GPT-OSS 20B #159 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.5 and GPT-OSS 20B share 18 comparable benchmark results. 0 of 8 categories are comparable. 39 results are unique to GPT-5.5; 0 to GPT-OSS 20B.
Updated July 22, 2026- Shared results
- 18
- GPT-5.5 only
- 39
- GPT-OSS 20B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.5 and GPT-OSS 20B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 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 has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.5 is priced at $5.00 input / $30.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GPT-OSS 20B. GPT-5.5 has the larger context window at 1M, compared with 128K for GPT-OSS 20B.
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-5.5 | Δ | GPT-OSS 20B |
|---|---|---|---|
| Agentic | GPT-5.581.6 | MarginNo overlap | GPT-OSS 20BNot measured |
| Coding | GPT-5.558.6 | MarginNo overlap | GPT-OSS 20BNot measured |
| Reasoning | GPT-5.585.0 | MarginNo overlap | GPT-OSS 20BNot measured |
| Knowledge | GPT-5.557.8 | MarginNo overlap | GPT-OSS 20BNot measured |
| Math | GPT-5.547.6 | MarginNo overlap | GPT-OSS 20BNot measured |
| Multimodal | GPT-5.570.4 | MarginNo overlap | GPT-OSS 20BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.5 | GPT-OSS 20B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.5$5 input / $30 output | GPT-OSS 20B$0 input / $0 output | GPT-OSS 20B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.5Not available | GPT-OSS 20B313 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.5Not available | GPT-OSS 20B0.65 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.51M | GPT-OSS 20B128K | GPT-5.5 lists the larger context window. |
Benchmark Deep Dive
Agentic24 benchmarks
| Benchmark | GPT-5.5 | GPT-OSS 20B | 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% | 60.2% | GPT-5.5 leads |
| AA Agentic IndexSource | 44.9% | 3.1% | GPT-5.5 leads |
| APEX-Agents-AASource | 37.7% | 0.7% | GPT-5.5 leads |
| GDPval-AASource | 49.5% | 3.0% | GPT-5.5 leads |
| GDPval-AASource | 1490 | 559 | GPT-5.5 leads |
| 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 | GPT-OSS 20B | 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% | 71% | GPT-5.5 leads |
| cursorBench31Source | 59.2% | — | Not comparable |
| cursorBench32Source | 58.4% | — | Not comparable |
| AA Coding IndexSource | 74.9% | 20.7% | GPT-5.5 leads |
| AA-SciCodeSource | 56.1% | 34.4% | GPT-5.5 leads |
| FrontierCode 1.1 MainSource | 43.0% | — | Not comparable |
Reasoning5 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5.5 | GPT-OSS 20B | 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% | 14.9% | GPT-5.5 leads |
| AA-GPQA DiamondSource | 93.5% | 68.8% | GPT-5.5 leads |
| AA-HLESource | 44.3% | 9.8% | GPT-5.5 leads |
| AA-Omniscience IndexSource | 20.1% | -63.9% | GPT-5.5 leads |
| AA-Omniscience AccuracySource | 56.9% | 15.5% | GPT-5.5 leads |
| AA-Omniscience Hallucination RateSource | 85.5% | 94.1% | GPT-5.5 leads |
Math3 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.5 | GPT-OSS 20B | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | 65.1% | GPT-5.5 leads |
Frequently Asked Questions (3)
Can I compare GPT-5.5 and GPT-OSS 20B 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 GPT-OSS 20B today?
GPT-5.5: $5.00 input / $30.00 output per 1M tokens GPT-OSS 20B: $0.00 input / $0.00 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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