Model comparison
GPT-5.2 vs GPT-OSS 120B
Head-to-head evidence from 14 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.2 #64 (Estimated); GPT-OSS 120B #116 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2 and GPT-OSS 120B share 14 comparable benchmark results. 0 of 8 categories are comparable. 14 results are unique to GPT-5.2; 13 to GPT-OSS 120B.
Updated July 20, 2026- Shared results
- 14
- GPT-5.2 only
- 14
- GPT-OSS 120B only
- 13
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.2 and GPT-OSS 120B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 7 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-5.2 is priced at $1.75 input / $14.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GPT-OSS 120B. GPT-5.2 has the larger context window at 400K, 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-5.2 | Δ | GPT-OSS 120B |
|---|---|---|---|
| Agentic | GPT-5.255.7 | MarginNo overlap | GPT-OSS 120BNot measured |
| Coding | GPT-5.270.6 | MarginNo overlap | GPT-OSS 120BNot measured |
| Reasoning | GPT-5.252.9 | MarginNo overlap | GPT-OSS 120BNot measured |
| Knowledge | GPT-5.292.4 | MarginNo overlap | GPT-OSS 120BNot measured |
| Math | GPT-5.235.2 | MarginNo overlap | GPT-OSS 120BNot measured |
| Multimodal | GPT-5.280.4 | 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-5.2 | GPT-OSS 120B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 output | GPT-OSS 120B$0 input / $0 output | GPT-OSS 120B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.273 tok/s | GPT-OSS 120B262 tok/s | GPT-OSS 120B has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | GPT-OSS 120B0.79 s | GPT-OSS 120B reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-5.2400K | GPT-OSS 120B128K | GPT-5.2 lists the larger context window. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | GPT-5.2 | GPT-OSS 120B | Result |
|---|---|---|---|
| BrowseCompSource | 65.8% | — | Not comparable |
| OSWorld-VerifiedSource | 47.3% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | 65.8% | GPT-5.2 leads |
| Gert LabsSource | 46.54% | 29.61% | GPT-5.2 leads |
| JobBenchSource | 34.3% | — | Not comparable |
| AA Agentic IndexSource | — | 13.2% | Not comparable |
| APEX-Agents-AASource | — | 3.1% | Not comparable |
| GDPval-AASource | — | 15.0% | Not comparable |
| GDPval-AASource | — | 799 | Not comparable |
| AA EnterpriseOps-GymSource | — | 25.5% | Not comparable |
| AA Harvey LABSource | — | 0.0% | Not comparable |
| AA ITBenchSource | — | 5.6% | Not comparable |
Coding7 benchmarks
| Benchmark | GPT-5.2 | GPT-OSS 120B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80% | — | Not comparable |
| SWE-bench ProSource | 55.6% | — | Not comparable |
| Vibe Code BenchSource | 53.50% | — | Not comparable |
| AA-SciCodeSource | 52.1% | 38.9% | GPT-5.2 leads |
| React Native EvalsSource | — | 71.6% | Not comparable |
| AA Coding IndexSource | — | 30.4% | Not comparable |
| AA LiveCodeBenchSource | — | 87.8% | Not comparable |
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | GPT-5.2 | GPT-OSS 120B | Result |
|---|---|---|---|
| GPQASource | 92.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 42.2% | 23.8% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 90.3% | 78.2% | GPT-5.2 leads |
| AA-HLESource | 35.4% | 18.5% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -1.0% | -50.0% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 43.8% | 21.5% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 79.7% | 91.2% | GPT-5.2 leads |
| AA Openness IndexSource | — | 38.9% | Not comparable |
| AA MMLU-ProSource | — | 80.8% | Not comparable |
Math3 benchmarks
Multilingual1 benchmarks
| Benchmark | GPT-5.2 | GPT-OSS 120B | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | — | 82.8% | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.2 | GPT-OSS 120B | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 69.0% | GPT-5.2 leads |
Frequently Asked Questions (3)
Can I compare GPT-5.2 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-5.2 and GPT-OSS 120B today?
GPT-5.2: $1.75 input / $14.00 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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