Model comparison
gpt-oss-20b vs MiMo-V2.5-Pro
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 32.5 on the Noometry Index. gpt-oss-20b costs 15× less per token, which makes it the better buy when MiMo-V2.5-Pro's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. gpt-oss-20b scores higher in 0 categories and MiMo-V2.5-Pro in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2.5-Pro leads 65.3 to 35.5.
- The biggest single-benchmark swing is DTBench: 68% for gpt-oss-20b and 84.5% for MiMo-V2.5-Pro.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2.5-Pro.
- MiMo-V2.5-Pro accepts more context: 1.05M tokens versus 131K.
Side by side
| gpt-oss-20b | MiMo-V2.5-Pro | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 32.5 | 45.2 |
| Released | 2025-08-05 | 2026-04-22 |
| Weights | Open | Open |
| Context window | 131K | 1.05M |
| Max output | 16K | 131K |
| Input $ / M tokens | $0.018 | $0.43 |
| Output $ / M tokens | $0.09 | $0.87 |
| Results tracked | 34 | 27 |
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Category by category
Coding MiMo-V2.5-Pro leads
gpt-oss-20b: 37.6 (#192), MiMo-V2.5-Pro: 47.4 (#60)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| SciCode | 34.4% | 50.2% |
| LMArena Coding | 1306 | 1503 |
| ALE-Bench | 566.05 | 899.8 |
| LMArena WebDev | — | 1479 |
| WeirdML | 40.9% | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.3 (#154), MiMo-V2.5-Pro: —
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| Terminal-Bench | 3.4% | — |
Reasoning MiMo-V2.5-Pro leads
gpt-oss-20b: 19.3 (#261), MiMo-V2.5-Pro: 26.8 (#130)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| CritPt | 1.4% | 4% |
| LMArena Hard Prompts | 1274 | 1488 |
| DTBench | 68% | 84.5% |
| LMCA | 14.5% | 29.5% |
| Kagi LLM Benchmark | 53.2% | — |
| NYT Connections (extended) | — | 34.4% |
| Chess Puzzles | 4% | — |
| Epoch Capabilities Index | 137.82 | — |
Math Too close to call
gpt-oss-20b: 39.4 (#103), MiMo-V2.5-Pro: 40.0 (#96)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Math | 1317 | 1481 |
| OTIS Mock AIME 2024-2025 | 65.3% | — |
| ProofBench | — | 22% |
| Omni-MATH | 56.5% | — |
Knowledge MiMo-V2.5-Pro leads
gpt-oss-20b: 34.6 (#195), MiMo-V2.5-Pro: 42.2 (#98)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Expert | 1258 | 1503 |
| GPQA Diamond | 60.8% | — |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual MiMo-V2.5-Pro leads
gpt-oss-20b: 42.2 (#197), MiMo-V2.5-Pro: 55.1 (#34)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Non-English | 1268 | 1449 |
| LMArena Chinese | 1314 | 1507 |
| LMArena German | 1255 | 1458 |
| LMArena Japanese | 1244 | 1412 |
| LMArena Korean | 1236 | 1437 |
| LMArena Russian | 1278 | 1450 |
| LMArena Spanish | 1267 | 1471 |
| LMArena French | — | 1488 |
Instruction Following MiMo-V2.5-Pro leads
gpt-oss-20b: 61.8 (#240), MiMo-V2.5-Pro: 77.5 (#21)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Instruction Following | 1236 | 1477 |
| IFEval | 73.2% | — |
Long Context MiMo-V2.5-Pro leads
gpt-oss-20b: 37.9 (#209), MiMo-V2.5-Pro: 45.4 (#37)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Longer Query | 1250 | 1483 |
Writing & Preference MiMo-V2.5-Pro leads
gpt-oss-20b: 35.5 (#265), MiMo-V2.5-Pro: 65.3 (#49)
| Benchmark | gpt-oss-20b | MiMo-V2.5-Pro |
|---|---|---|
| LMArena Text | 1287 | 1465 |
| LMArena Creative Writing | 1201 | 1440 |
| EQ-Bench Creative Writing | 666 | 1493 |
| LMArena Multi-Turn | 1268 | 1477 |
| WildBench | 73.7% | — |
| EQ-Bench 4 | — | 1208 |
Frequently asked questions
Is gpt-oss-20b better than MiMo-V2.5-Pro?
MiMo-V2.5-Pro is the stronger model overall, scoring 45.2 to 32.5 on the Noometry Index. gpt-oss-20b costs 15× less per token, which makes it the better buy when MiMo-V2.5-Pro's lead doesn't matter for your workload.
Which is cheaper, gpt-oss-20b or MiMo-V2.5-Pro?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; MiMo-V2.5-Pro lists at $0.43 and $0.87.
Is gpt-oss-20b or MiMo-V2.5-Pro better for coding?
MiMo-V2.5-Pro scores higher on coding benchmarks: 47.4 versus 37.6 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2.5-Pro does, with 1.05M tokens against 131K.
How many benchmarks do gpt-oss-20b and MiMo-V2.5-Pro share?
22 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and MiMo-V2.5-Pro has 27.