Model comparison
gpt-oss-20b vs Yi-1.5-34B
gpt-oss-20b is the stronger model overall, scoring 32.5 to 30.6 on the Noometry Index.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. gpt-oss-20b scores higher in 6 categories and Yi-1.5-34B in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where gpt-oss-20b leads 34.6 to 14.8.
- The biggest single-benchmark swing is GPQA Diamond: 60.8% for gpt-oss-20b and 32% for Yi-1.5-34B.
Side by side
| gpt-oss-20b | Yi-1.5-34B | |
|---|---|---|
| Provider | OpenAI | 01.AI |
| Noometry Index | 32.5 | 30.6 |
| Released | 2025-08-05 | 2024-05-13 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.018 | — |
| Output $ / M tokens | $0.09 | — |
| Results tracked | 34 | 21 |
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Category by category
Coding gpt-oss-20b leads
gpt-oss-20b: 37.6 (#192), Yi-1.5-34B: 32.4 (#272)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| LMArena Coding | 1306 | 1169 |
| SciCode | 34.4% | — |
| WeirdML | 40.9% | — |
| BigCodeBench Instruct | — | 33.9% |
| BigCodeBench Complete | — | 43.8% |
| ALE-Bench | 566.05 | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.3 (#154), Yi-1.5-34B: —
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| Terminal-Bench | 3.4% | — |
Reasoning Yi-1.5-34B leads
gpt-oss-20b: 19.3 (#261), Yi-1.5-34B: 22.5 (#191)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| LMArena Hard Prompts | 1274 | 1160 |
| Kagi LLM Benchmark | 53.2% | — |
| CritPt | 1.4% | — |
| Chess Puzzles | 4% | — |
| DTBench | 68% | — |
| LMCA | 14.5% | — |
| Epoch Capabilities Index | 137.82 | — |
Math gpt-oss-20b leads
gpt-oss-20b: 39.4 (#103), Yi-1.5-34B: 27.5 (#249)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| LMArena Math | 1317 | 1182 |
| OTIS Mock AIME 2024-2025 | 65.3% | — |
| Omni-MATH | 56.5% | — |
| MATH Level 5 | — | 25.5% |
Knowledge gpt-oss-20b leads
gpt-oss-20b: 34.6 (#195), Yi-1.5-34B: 14.8 (#295)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| GPQA Diamond | 60.8% | 32% |
| LMArena Expert | 1258 | 1144 |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual gpt-oss-20b leads
gpt-oss-20b: 42.2 (#197), Yi-1.5-34B: 32.3 (#256)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| LMArena Non-English | 1268 | 1121 |
| LMArena Chinese | 1314 | 1213 |
| LMArena German | 1255 | 1111 |
| LMArena Japanese | 1244 | 1021 |
| LMArena Korean | 1236 | 1005 |
| LMArena Russian | 1278 | 1091 |
| LMArena Spanish | 1267 | 1121 |
| LMArena French | — | 1156 |
Instruction Following gpt-oss-20b leads
gpt-oss-20b: 61.8 (#240), Yi-1.5-34B: 59.2 (#257)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| LMArena Instruction Following | 1236 | 1139 |
| IFEval | 73.2% | — |
Long Context gpt-oss-20b leads
gpt-oss-20b: 37.9 (#209), Yi-1.5-34B: 34.6 (#248)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| LMArena Longer Query | 1250 | 1143 |
Writing & Preference Yi-1.5-34B leads
gpt-oss-20b: 35.5 (#265), Yi-1.5-34B: 37.4 (#257)
| Benchmark | gpt-oss-20b | Yi-1.5-34B |
|---|---|---|
| LMArena Text | 1287 | 1173 |
| LMArena Creative Writing | 1201 | 1135 |
| LMArena Multi-Turn | 1268 | 1153 |
| EQ-Bench Creative Writing | 666 | — |
| WildBench | 73.7% | — |
Frequently asked questions
Is gpt-oss-20b better than Yi-1.5-34B?
gpt-oss-20b is the stronger model overall, scoring 32.5 to 30.6 on the Noometry Index.
Is gpt-oss-20b or Yi-1.5-34B better for coding?
gpt-oss-20b scores higher on coding benchmarks: 37.6 versus 32.4 in the Noometry coding category.
How many benchmarks do gpt-oss-20b and Yi-1.5-34B share?
17 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Yi-1.5-34B has 21.