Model comparison
GPT-5.6 Sol vs GPT-OSS 120B
Head-to-head evidence from 16 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); GPT-OSS 120B #116 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and GPT-OSS 120B share 16 comparable benchmark results. 0 of 8 categories are comparable. 30 results are unique to GPT-5.6 Sol; 10 to GPT-OSS 120B.
Updated July 23, 2026- Shared results
- 16
- GPT-5.6 Sol only
- 30
- GPT-OSS 120B only
- 10
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.6 Sol and GPT-OSS 120B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 5 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-5.6 Sol 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 120B. GPT-5.6 Sol has the larger context window at 1M, compared with 128K for GPT-OSS 120B.
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 | GPT-OSS 120B |
|---|---|---|---|
| Agentic | GPT-5.6 Sol92.0 | MarginNo overlap | GPT-OSS 120BNot measured |
| Coding | GPT-5.6 Sol64.6 | MarginNo overlap | GPT-OSS 120BNot measured |
| Knowledge | GPT-5.6 Sol94.6 | MarginNo overlap | GPT-OSS 120BNot measured |
| Math | GPT-5.6 Sol87.5 | MarginNo overlap | GPT-OSS 120BNot measured |
| Multimodal | GPT-5.6 Sol83.0 | MarginNo overlap | GPT-OSS 120BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.6 Sol | GPT-OSS 120B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | GPT-OSS 120B$0 input / $0 output | GPT-OSS 120B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 SolNot available | GPT-OSS 120B262 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | GPT-OSS 120B0.79 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | GPT-OSS 120B128K | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
Agentic20 benchmarks
| Benchmark | GPT-5.6 Sol | GPT-OSS 120B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | — | Not comparable |
| BrowseCompSource | 92.2% | — | Not comparable |
| OSWorld 2.0Source | 62.6% | — | Not comparable |
| CyberGymSource | 84.5% | — | Not comparable |
| ExploitGymSource | 33.7% | — | Not comparable |
| ToolathlonSource | 58% | — | Not comparable |
| AA Agentic IndexSource | 54.0% | 13.2% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 85.1% | 65.8% | GPT-5.6 Sol leads |
| GDPval-AASource | 61.8% | 15.0% | GPT-5.6 Sol leads |
| GDPval-AASource | 1736 | 799 | GPT-5.6 Sol leads |
| AA BriefcaseSource | 1501 | — | Not comparable |
| AA ITBenchSource | 56.2% | 5.6% | GPT-5.6 Sol leads |
| 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 |
| APEX-Agents-AASource | — | 3.1% | Not comparable |
| Gert LabsSource | — | 29.61% | Not comparable |
| AA EnterpriseOps-GymSource | — | 25.5% | Not comparable |
Coding10 benchmarks
| Benchmark | GPT-5.6 Sol | GPT-OSS 120B | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | — | Not comparable |
| 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% | 30.4% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 56.1% | 38.9% | GPT-5.6 Sol leads |
| React Native EvalsSource | — | 71.6% | Not comparable |
| AA LiveCodeBenchSource | — | 87.8% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | GPT-5.6 Sol | GPT-OSS 120B | Result |
|---|---|---|---|
| GPQASource | 94.6% | — | Not comparable |
| GPQA-DSource | 94.6% | — | Not comparable |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | 23.8% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 94.1% | 78.2% | GPT-5.6 Sol leads |
| AA-HLESource | 47.2% | 18.5% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 21.7% | -50.0% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 58.5% | 21.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 88.8% | 91.2% | GPT-5.6 Sol leads |
| AA Openness IndexSource | — | 38.9% | Not comparable |
| AA MMLU-ProSource | — | 80.8% | Not comparable |
Math4 benchmarks
Multilingual1 benchmarks
| Benchmark | GPT-5.6 Sol | GPT-OSS 120B | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | — | 82.8% | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Sol | GPT-OSS 120B | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.7% | 69.0% | GPT-5.6 Sol leads |
Frequently Asked Questions (3)
Can I compare GPT-5.6 Sol and GPT-OSS 120B 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-5.6 Sol and GPT-OSS 120B today?
GPT-5.6 Sol: $5.00 input / $30.00 output per 1M tokens GPT-OSS 120B: $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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