Model comparison
gpt-oss-20b vs Mercury
Mercury is the stronger model overall, scoring 37.6 to 32.5 on the Noometry Index.
Last verified . 9 shared benchmarks.
Summary
- They share 9 benchmarks with published results for both. gpt-oss-20b scores higher in 2 categories and Mercury in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Mercury leads 46.2 to 35.5.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 53.2% for gpt-oss-20b and 21.6% for Mercury.
- gpt-oss-20b has downloadable open weights; the other is API-only.
Side by side
| gpt-oss-20b | Mercury | |
|---|---|---|
| Provider | OpenAI | Inception |
| Noometry Index | 32.5 | 37.6 |
| Released | 2025-08-05 | — |
| Weights | Open | Proprietary |
| Context window | 131K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.018 | — |
| Output $ / M tokens | $0.09 | — |
| Results tracked | 34 | 9 |
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Category by category
Coding Mercury leads
gpt-oss-20b: 37.6 (#192), Mercury: 38.7 (#170)
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| LMArena Coding | 1306 | 1322 |
| SciCode | 34.4% | — |
| WeirdML | 40.9% | — |
| ALE-Bench | 566.05 | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.3 (#154), Mercury: —
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| Terminal-Bench | 3.4% | — |
Reasoning gpt-oss-20b leads
gpt-oss-20b: 19.3 (#261), Mercury: 17.5 (#293)
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 21.6% |
| LMArena Hard Prompts | 1274 | 1285 |
| CritPt | 1.4% | — |
| Chess Puzzles | 4% | — |
| DTBench | 68% | — |
| LMCA | 14.5% | — |
| Epoch Capabilities Index | 137.82 | — |
Math Not comparable
gpt-oss-20b: 39.4 (#103), Mercury: —
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 65.3% | — |
| Omni-MATH | 56.5% | — |
| LMArena Math | 1317 | — |
Knowledge Not comparable
gpt-oss-20b: 34.6 (#195), Mercury: —
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| GPQA Diamond | 60.8% | — |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |
| LMArena Expert | 1258 | — |
Multilingual Too close to call
gpt-oss-20b: 42.2 (#197), Mercury: 41.6 (#206)
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| LMArena Non-English | 1268 | 1260 |
| LMArena Chinese | 1314 | — |
| LMArena German | 1255 | — |
| LMArena Japanese | 1244 | — |
| LMArena Korean | 1236 | — |
| LMArena Russian | 1278 | — |
| LMArena Spanish | 1267 | — |
Instruction Following Mercury leads
gpt-oss-20b: 61.8 (#240), Mercury: 65.2 (#224)
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| LMArena Instruction Following | 1236 | 1239 |
| IFEval | 73.2% | — |
Long Context Too close to call
gpt-oss-20b: 37.9 (#209), Mercury: 38.4 (#198)
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| LMArena Longer Query | 1250 | 1266 |
Writing & Preference Mercury leads
gpt-oss-20b: 35.5 (#265), Mercury: 46.2 (#221)
| Benchmark | gpt-oss-20b | Mercury |
|---|---|---|
| LMArena Text | 1287 | 1282 |
| LMArena Creative Writing | 1201 | 1191 |
| LMArena Multi-Turn | 1268 | 1282 |
| EQ-Bench Creative Writing | 666 | — |
| WildBench | 73.7% | — |
Frequently asked questions
Is gpt-oss-20b better than Mercury?
Mercury is the stronger model overall, scoring 37.6 to 32.5 on the Noometry Index.
Is gpt-oss-20b or Mercury better for coding?
Mercury scores higher on coding benchmarks: 38.7 versus 37.6 in the Noometry coding category.
How many benchmarks do gpt-oss-20b and Mercury share?
9 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Mercury has 9.