Model comparison
gpt-oss-20b vs MiMo-V2-Omni
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 32.5 on the Noometry Index. gpt-oss-20b costs 4.9× less per token, which makes it the better buy when MiMo-V2-Omni's lead doesn't matter for your workload.
Last verified . 16 shared benchmarks.
Summary
- They share 16 benchmarks with published results for both. gpt-oss-20b scores higher in 1 category and MiMo-V2-Omni in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where MiMo-V2-Omni leads 61.4 to 35.5.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.14 / $0.28 for MiMo-V2-Omni.
- MiMo-V2-Omni accepts more context: 262K tokens versus 131K.
- gpt-oss-20b has downloadable open weights; the other is API-only.
Side by side
| gpt-oss-20b | MiMo-V2-Omni | |
|---|---|---|
| Provider | OpenAI | Xiaomi |
| Noometry Index | 32.5 | 43.6 |
| Released | 2025-08-05 | 2026-03-18 |
| Weights | Open | Proprietary |
| Context window | 131K | 262K |
| Max output | 16K | 131K |
| Input $ / M tokens | $0.018 | $0.14 |
| Output $ / M tokens | $0.09 | $0.28 |
| Results tracked | 34 | 18 |
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Category by category
Coding MiMo-V2-Omni leads
gpt-oss-20b: 37.6 (#192), MiMo-V2-Omni: 43.3 (#89)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Coding | 1306 | 1466 |
| SciCode | 34.4% | — |
| WeirdML | 40.9% | — |
| ALE-Bench | 566.05 | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.3 (#154), MiMo-V2-Omni: —
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| Terminal-Bench | 3.4% | — |
Reasoning MiMo-V2-Omni leads
gpt-oss-20b: 19.3 (#261), MiMo-V2-Omni: 29.7 (#88)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Hard Prompts | 1274 | 1445 |
| Kagi LLM Benchmark | 53.2% | — |
| CritPt | 1.4% | — |
| Chess Puzzles | 4% | — |
| DTBench | 68% | — |
| LMCA | 14.5% | — |
| Epoch Capabilities Index | 137.82 | — |
Math Too close to call
gpt-oss-20b: 39.4 (#103), MiMo-V2-Omni: 39.1 (#115)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Math | 1317 | 1430 |
| OTIS Mock AIME 2024-2025 | 65.3% | — |
| Omni-MATH | 56.5% | — |
Knowledge MiMo-V2-Omni leads
gpt-oss-20b: 34.6 (#195), MiMo-V2-Omni: 40.5 (#118)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Expert | 1258 | 1449 |
| GPQA Diamond | 60.8% | — |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |
Multimodal Not comparable
gpt-oss-20b: —, MiMo-V2-Omni: 38.6 (#63)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Vision | — | 1228 |
Multilingual MiMo-V2-Omni leads
gpt-oss-20b: 42.2 (#197), MiMo-V2-Omni: 51.8 (#102)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Non-English | 1268 | 1404 |
| LMArena Chinese | 1314 | 1465 |
| LMArena German | 1255 | 1399 |
| LMArena Japanese | 1244 | 1317 |
| LMArena Korean | 1236 | 1355 |
| LMArena Russian | 1278 | 1412 |
| LMArena Spanish | 1267 | 1434 |
| LMArena French | — | 1447 |
Instruction Following MiMo-V2-Omni leads
gpt-oss-20b: 61.8 (#240), MiMo-V2-Omni: 75.2 (#66)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Instruction Following | 1236 | 1428 |
| IFEval | 73.2% | — |
Long Context MiMo-V2-Omni leads
gpt-oss-20b: 37.9 (#209), MiMo-V2-Omni: 44.1 (#76)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Longer Query | 1250 | 1442 |
Writing & Preference MiMo-V2-Omni leads
gpt-oss-20b: 35.5 (#265), MiMo-V2-Omni: 61.4 (#87)
| Benchmark | gpt-oss-20b | MiMo-V2-Omni |
|---|---|---|
| LMArena Text | 1287 | 1423 |
| LMArena Creative Writing | 1201 | 1392 |
| LMArena Multi-Turn | 1268 | 1445 |
| EQ-Bench Creative Writing | 666 | — |
| WildBench | 73.7% | — |
Frequently asked questions
Is gpt-oss-20b better than MiMo-V2-Omni?
MiMo-V2-Omni is the stronger model overall, scoring 43.6 to 32.5 on the Noometry Index. gpt-oss-20b costs 4.9× less per token, which makes it the better buy when MiMo-V2-Omni's lead doesn't matter for your workload.
Which is cheaper, gpt-oss-20b or MiMo-V2-Omni?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; MiMo-V2-Omni lists at $0.14 and $0.28.
Is gpt-oss-20b or MiMo-V2-Omni better for coding?
MiMo-V2-Omni scores higher on coding benchmarks: 43.3 versus 37.6 in the Noometry coding category.
Which has the bigger context window?
MiMo-V2-Omni does, with 262K tokens against 131K.
How many benchmarks do gpt-oss-20b and MiMo-V2-Omni share?
16 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and MiMo-V2-Omni has 18.