Model comparison
Claude Fable 5 vs gpt-oss-20b
Claude Fable 5 is the stronger model overall, scoring 66.3 to 32.1 on the Noometry Index. gpt-oss-20b costs 556× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
Summary
- They share 28 benchmarks with published results for both. Claude Fable 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 reasoning, where Claude Fable 5 leads 76.8 to 18.8.
- The biggest single-benchmark swing is WeirdML: 91.9% for Claude Fable 5 and 40.9% for gpt-oss-20b.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $10 / $50 for Claude Fable 5.
- Claude Fable 5 accepts more context: 1M tokens versus 131K.
- gpt-oss-20b has downloadable open weights; the other is API-only.
Side by side
| Claude Fable 5 | gpt-oss-20b | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 66.3 | 32.1 |
| Released | 2026-06-07 | 2025-08-05 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 128K | 16K |
| Input $ / M tokens | $10 | $0.018 |
| Output $ / M tokens | $50 | $0.09 |
| Results tracked | 61 | 34 |
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Category by category
Coding Claude Fable 5 leads
Claude Fable 5: 67.0 (#4), gpt-oss-20b: 37.1 (#185)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| SciCode | 61% | 34.4% |
| WeirdML | 91.9% | 40.9% |
| LMArena Coding | 1519 | 1307 |
| ALE-Bench | 2,041 | 566.05 |
| DeepSWE | 69.9% | — |
| FrontierCode | 53.5% | — |
| LMArena WebDev | 1626 | — |
| FrontierSWE | 47% | — |
| MirrorCode | 63.9% | — |
Agentic & Tool Use Claude Fable 5 leads
Claude Fable 5: 54.1 (#2), gpt-oss-20b: 9.2 (#146)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| Terminal-Bench | — | 3.4% |
| APEX-Agents | 63.6% | — |
| Remote Labor Index | 16.1% | — |
| τ²-bench Banking | 39.7% | — |
| PostTrainBench | 41.8% | — |
| GBAEval | 74.5% | — |
| GDP.pdf | 30% | — |
| LMArena Search | 1230 | — |
| Vending-Bench 2 | 5,680 | — |
Reasoning Claude Fable 5 leads
Claude Fable 5: 76.8 (#4), gpt-oss-20b: 18.8 (#251)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| Kagi LLM Benchmark | 91.4% | 53.2% |
| CritPt | 28.6% | 1.4% |
| Chess Puzzles | 41% | 4% |
| LMArena Hard Prompts | 1508 | 1274 |
| DTBench | 98.4% | 68% |
| LMCA | 61.1% | 14.5% |
| Epoch Capabilities Index | 163.6 | 137.81 |
| ARC-AGI-2 | 89.2% | — |
| SimpleBench | 81.9% | — |
| NYT Connections (extended) | 92.7% | — |
| ARC-AGI-1 | 98.5% | — |
| EnigmaEval | 39.3% | — |
| EBR-Bench | 39.5% | — |
| Mystery Game Puzzles | 52% | — |
| Surface Evolver Bench | 95% | — |
| Bench to the Future 3 | 0.13 | — |
Math Claude Fable 5 leads
Claude Fable 5: 88.4 (#5), gpt-oss-20b: 37.6 (#93)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 100% | 65.3% |
| LMArena Math | 1519 | 1317 |
| FrontierMath (Tiers 1-3) | 87% | — |
| FrontierMath Tier 4 | 90.2% | — |
| ProofBench | 95% | — |
| Omni-MATH | — | 56.5% |
| FrontierMath Erdős | 0% | — |
Knowledge Claude Fable 5 leads
Claude Fable 5: 62.3 (#22), gpt-oss-20b: 34.6 (#186)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| GPQA Diamond | 85.9% | 60.8% |
| LMArena Expert | 1534 | 1258 |
| SimpleQA Verified | 70.7% | — |
| MMLU-Pro | — | 74% |
| GPQA (HELM) | — | 59.4% |
Multimodal Not comparable
Claude Fable 5: 45.6 (#14), gpt-oss-20b: —
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| LMArena Vision | 1326 | — |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 35.8% | — |
| LMArena Document | 1496 | — |
Multilingual Claude Fable 5 leads
Claude Fable 5: 57.6 (#8), gpt-oss-20b: 42.4 (#192)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| LMArena Non-English | 1483 | 1269 |
| LMArena Chinese | 1546 | 1311 |
| LMArena German | 1486 | 1249 |
| LMArena Japanese | 1507 | 1245 |
| LMArena Korean | 1493 | 1239 |
| LMArena Russian | 1507 | 1279 |
| LMArena Spanish | 1503 | 1267 |
| LMArena French | 1509 | — |
Instruction Following Claude Fable 5 leads
Claude Fable 5: 78.8 (#7), gpt-oss-20b: 62.0 (#235)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| LMArena Instruction Following | 1503 | 1236 |
| IFEval | — | 73.2% |
Long Context Claude Fable 5 leads
Claude Fable 5: 46.3 (#22), gpt-oss-20b: 37.9 (#203)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| LMArena Longer Query | 1510 | 1251 |
Writing & Preference Claude Fable 5 leads
Claude Fable 5: 76.1 (#5), gpt-oss-20b: 35.8 (#260)
| Benchmark | Claude Fable 5 | gpt-oss-20b |
|---|---|---|
| LMArena Text | 1491 | 1288 |
| LMArena Creative Writing | 1494 | 1201 |
| EQ-Bench Creative Writing | 1943 | 666 |
| LMArena Multi-Turn | 1505 | 1268 |
| WildBench | — | 73.7% |
| EQ-Bench 4 | 1340 | — |
Frequently asked questions
Is Claude Fable 5 better than gpt-oss-20b?
Claude Fable 5 is the stronger model overall, scoring 66.3 to 32.1 on the Noometry Index. gpt-oss-20b costs 556× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Which is cheaper, Claude Fable 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 Fable 5 lists at $10 and $50.
Is Claude Fable 5 or gpt-oss-20b better for coding?
Claude Fable 5 scores higher on coding benchmarks: 67.0 versus 37.1 in the Noometry coding category.
Which has the bigger context window?
Claude Fable 5 does, with 1M tokens against 131K.
How many benchmarks do Claude Fable 5 and gpt-oss-20b share?
28 benchmarks have published results for both models. Claude Fable 5 has 61 scored results on Noometry and gpt-oss-20b has 34.