Model comparison
Claude Opus 5.5 vs gpt-oss-120b
Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 36.0 on the Noometry Index. gpt-oss-120b costs 114× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. Claude Opus 5.5 scores higher in 9 categories and gpt-oss-120b in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 5.5 leads 79.5 to 19.5.
- The biggest single-benchmark swing is APEX-Agents: 73.5% for Claude Opus 5.5 and 4.4% for gpt-oss-120b.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $4 / $20 for Claude Opus 5.5.
- Claude Opus 5.5 accepts more context: 1M tokens versus 131K.
- gpt-oss-120b has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 5.5 | gpt-oss-120b | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 68.5 | 36.0 |
| Released | 2026-09-22 | 2025-08-05 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 128K | 41K |
| Input $ / M tokens | $4 | $0.037 |
| Output $ / M tokens | $20 | $0.17 |
| Results tracked | 35 | 48 |
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Category by category
Coding Claude Opus 5.5 leads
Claude Opus 5.5: 71.4 (#1), gpt-oss-120b: 33.2 (#251)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| SciCode | 66.9% | 36% |
| LMArena Coding | 1545 | 1380 |
| FrontierCode | 54.4% | — |
| SWE-bench Verified (bash only) | — | 26% |
| Aider Polyglot | — | 41.8% |
| CursorBench | 57.8% | — |
| LMArena WebDev | 1820 | — |
| FrontierSWE | 62.3% | — |
| WeirdML | — | 48.2% |
| MirrorCode | 77.4% | — |
| ALE-Bench | — | 575.62 |
| AlgoTune | — | 1.41 |
Agentic & Tool Use Claude Opus 5.5 leads
Claude Opus 5.5: 45.3 (#13), gpt-oss-120b: 12.1 (#145)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| APEX-Agents | 73.5% | 4.4% |
| Terminal-Bench | — | 18.7% |
| GDP.pdf | 30.6% | — |
| METR Time Horizons | — | 56.6% |
| Vending-Bench 2 | — | -21.53 |
Reasoning Claude Opus 5.5 leads
Claude Opus 5.5: 79.5 (#2), gpt-oss-120b: 19.5 (#236)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| CritPt | 31.7% | 1.1% |
| LMArena Hard Prompts | 1545 | 1364 |
| Mystery Game Puzzles | 71% | 2% |
| DTBench | 98.9% | 76.3% |
| LMCA | 68.2% | 22.1% |
| ARC-AGI-2 | 92.5% | — |
| SimpleBench | — | 22.1% |
| Kagi LLM Benchmark | — | 58.6% |
| NYT Connections (extended) | 88.5% | — |
| ARC-AGI-1 | 97.5% | — |
| Chess Puzzles | — | 20% |
| EBR-Bench | 71.4% | — |
| Surface Evolver Bench | — | 25% |
| Epoch Capabilities Index | — | 139.94 |
Math Claude Opus 5.5 leads
Claude Opus 5.5: 92.4 (#2), gpt-oss-120b: 50.6 (#43)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 88.9% |
| FrontierMath (Tiers 1-3) | 91.2% | — |
| FrontierMath Tier 4 | 95% | — |
| ProofBench | 100% | — |
| Omni-MATH | — | 68.8% |
| LMArena Math | — | 1388 |
Knowledge Claude Opus 5.5 leads
Claude Opus 5.5: 66.6 (#9), gpt-oss-120b: 42.3 (#89)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| GPQA Diamond | 90.6% | 75.8% |
| LMArena Expert | 1564 | 1356 |
| SimpleQA Verified | 72.2% | — |
| MMLU-Pro | — | 79.5% |
| Confabulations | — | 15.7% |
| Vectara Hallucination Rate | — | 14.2% |
| GPQA (HELM) | — | 68.4% |
Multimodal Not comparable
Claude Opus 5.5: 56.5 (#2), gpt-oss-120b: —
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| Furniture Assembly | 83.3% | — |
Multilingual Claude Opus 5.5 leads
Claude Opus 5.5: 59.8 (#1), gpt-oss-120b: 48.2 (#142)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| LMArena Non-English | 1513 | 1350 |
| LMArena Chinese | 1572 | 1384 |
| LMArena Russian | 1532 | 1343 |
| LMArena French | — | 1370 |
| LMArena German | — | 1355 |
| LMArena Japanese | — | 1332 |
| LMArena Korean | — | 1283 |
| LMArena Spanish | — | 1388 |
Instruction Following Claude Opus 5.5 leads
Claude Opus 5.5: 80.1 (#2), gpt-oss-120b: 69.5 (#168)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| LMArena Instruction Following | 1535 | 1318 |
| IFEval | — | 83.6% |
Long Context Claude Opus 5.5 leads
Claude Opus 5.5: 47.3 (#18), gpt-oss-120b: 31.4 (#273)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| LMArena Longer Query | 1540 | 1319 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference Claude Opus 5.5 leads
Claude Opus 5.5: 78.7 (#3), gpt-oss-120b: 46.7 (#213)
| Benchmark | Claude Opus 5.5 | gpt-oss-120b |
|---|---|---|
| LMArena Text | 1518 | 1366 |
| LMArena Creative Writing | 1538 | 1274 |
| EQ-Bench Creative Writing | 2050 | 961 |
| LMArena Multi-Turn | 1520 | 1340 |
| Short-Story Creative Writing | — | 77.1% |
| WildBench | — | 84.5% |
Frequently asked questions
Is Claude Opus 5.5 better than gpt-oss-120b?
Claude Opus 5.5 is the stronger model overall, scoring 68.5 to 36.0 on the Noometry Index. gpt-oss-120b costs 114× less per token, which makes it the better buy when Claude Opus 5.5's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 5.5 or gpt-oss-120b?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Claude Opus 5.5 lists at $4 and $20.
Is Claude Opus 5.5 or gpt-oss-120b better for coding?
Claude Opus 5.5 scores higher on coding benchmarks: 71.4 versus 33.2 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 5.5 does, with 1M tokens against 131K.
How many benchmarks do Claude Opus 5.5 and gpt-oss-120b share?
20 benchmarks have published results for both models. Claude Opus 5.5 has 35 scored results on Noometry and gpt-oss-120b has 48.