Model comparison
Claude Sonnet 5 vs gpt-oss-20b
Claude Sonnet 5 is the stronger model overall, scoring 54.6 to 32.5 on the Noometry Index. gpt-oss-20b costs 111× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. Claude Sonnet 5 scores higher in 9 categories and gpt-oss-20b in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Sonnet 5 leads 69.2 to 35.5.
- The biggest single-benchmark swing is LMCA: 50% for Claude Sonnet 5 and 14.5% for gpt-oss-20b.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.
- Claude Sonnet 5 accepts more context: 1M tokens versus 131K.
- gpt-oss-20b has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 5 | gpt-oss-20b | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 54.6 | 32.5 |
| Released | 2026-06-29 | 2025-08-05 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 128K | 16K |
| Input $ / M tokens | $2 | $0.018 |
| Output $ / M tokens | $10 | $0.09 |
| Results tracked | 51 | 34 |
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Category by category
Coding Claude Sonnet 5 leads
Claude Sonnet 5: 55.5 (#26), gpt-oss-20b: 37.6 (#192)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| SciCode | 54.3% | 34.4% |
| WeirdML | 68.8% | 40.9% |
| LMArena Coding | 1483 | 1306 |
| ALE-Bench | 1,463 | 566.05 |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.7% | — |
| CursorBench | 34.1% | — |
| LMArena WebDev | 1541 | — |
| GSO | 37.3% | — |
Agentic & Tool Use Claude Sonnet 5 leads
Claude Sonnet 5: 42.8 (#18), gpt-oss-20b: 9.3 (#154)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| Terminal-Bench | — | 3.4% |
| APEX-Agents | 54.5% | — |
| GBAEval | 65.3% | — |
| LMArena Search | 1194 | — |
| Vending-Bench 2 | 6,378 | — |
Reasoning Claude Sonnet 5 leads
Claude Sonnet 5: 49.1 (#39), gpt-oss-20b: 19.3 (#261)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| CritPt | 16.9% | 1.4% |
| Chess Puzzles | 35% | 4% |
| LMArena Hard Prompts | 1461 | 1274 |
| DTBench | 92.5% | 68% |
| LMCA | 50% | 14.5% |
| Epoch Capabilities Index | 156.21 | 137.82 |
| SimpleBench | 60.6% | — |
| Kagi LLM Benchmark | — | 53.2% |
| NYT Connections (extended) | 75.1% | — |
| Mystery Game Puzzles | 35% | — |
| Surface Evolver Bench | 60% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 61.1 | — |
Math Claude Sonnet 5 leads
Claude Sonnet 5: 66.2 (#27), gpt-oss-20b: 39.4 (#103)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.7% | 65.3% |
| LMArena Math | 1467 | 1317 |
| FrontierMath (Tiers 1-3) | 65.6% | — |
| FrontierMath Tier 4 | 29.3% | — |
| ProofBench | 77% | — |
| Omni-MATH | — | 56.5% |
Knowledge Claude Sonnet 5 leads
Claude Sonnet 5: 55.6 (#47), gpt-oss-20b: 34.6 (#195)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| GPQA Diamond | 90.5% | 60.8% |
| LMArena Expert | 1490 | 1258 |
| SimpleQA Verified | 33.7% | — |
| MMLU-Pro | — | 74% |
| GPQA (HELM) | — | 59.4% |
Multimodal Not comparable
Claude Sonnet 5: 42.4 (#31), gpt-oss-20b: —
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| LMArena Vision | 1274 | — |
| Blueprint-Bench 2 | 24.9% | — |
| LMArena Document | 1466 | — |
Multilingual Claude Sonnet 5 leads
Claude Sonnet 5: 53.8 (#55), gpt-oss-20b: 42.2 (#197)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| LMArena Non-English | 1431 | 1268 |
| LMArena Chinese | 1477 | 1314 |
| LMArena German | 1440 | 1255 |
| LMArena Japanese | 1422 | 1244 |
| LMArena Korean | 1411 | 1236 |
| LMArena Russian | 1451 | 1278 |
| LMArena Spanish | 1437 | 1267 |
| LMArena French | 1460 | — |
Instruction Following Claude Sonnet 5 leads
Claude Sonnet 5: 76.3 (#41), gpt-oss-20b: 61.8 (#240)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| LMArena Instruction Following | 1452 | 1236 |
| IFEval | — | 73.2% |
Long Context Claude Sonnet 5 leads
Claude Sonnet 5: 44.8 (#55), gpt-oss-20b: 37.9 (#209)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| LMArena Longer Query | 1463 | 1250 |
Writing & Preference Claude Sonnet 5 leads
Claude Sonnet 5: 69.2 (#25), gpt-oss-20b: 35.5 (#265)
| Benchmark | Claude Sonnet 5 | gpt-oss-20b |
|---|---|---|
| LMArena Text | 1442 | 1287 |
| LMArena Creative Writing | 1416 | 1201 |
| EQ-Bench Creative Writing | 1794 | 666 |
| LMArena Multi-Turn | 1454 | 1268 |
| WildBench | — | 73.7% |
| EQ-Bench 4 | 1236 | — |
Frequently asked questions
Is Claude Sonnet 5 better than gpt-oss-20b?
Claude Sonnet 5 is the stronger model overall, scoring 54.6 to 32.5 on the Noometry Index. gpt-oss-20b costs 111× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 5 or gpt-oss-20b?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Claude Sonnet 5 lists at $2 and $10.
Is Claude Sonnet 5 or gpt-oss-20b better for coding?
Claude Sonnet 5 scores higher on coding benchmarks: 55.5 versus 37.6 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 5 does, with 1M tokens against 131K.
How many benchmarks do Claude Sonnet 5 and gpt-oss-20b share?
27 benchmarks have published results for both models. Claude Sonnet 5 has 51 scored results on Noometry and gpt-oss-20b has 34.