gpt-oss-20b vs MiMo-V2.6-Flash
MiMo-V2.6-Flash leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 37.9 to 10.0, and gpt-oss-20b costs 1.9x less per output token ($0.15 vs $0.28 per million). Updated October 21, 2026; 32 benchmarks have a result for both.
gpt-oss-20b or MiMo-V2.6-Flash: which to pick
Only MiMo-V2.6-Flash has a coding score, 54.7 on the Vibe Coding Index; gpt-oss-20b has none, so the two cannot be ranked on coding.
Pick gpt-oss-20b for output tokens 1.9x cheaper ($0.15 vs $0.28 per million).
- Shared results
- 32
- gpt-oss-20b only
- 30
- MiMo-V2.6-Flash only
- 34
- Like-for-like categories
- 6 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only MiMo-V2.6-Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiMo-V2.6-Flash
MiMo-V2.6-Flash leads, 37.9 against 10.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only gpt-oss-20b has a GPQA Diamond result, 68.9%.
Directional only
Math
AIME
No call
Only gpt-oss-20b has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
No call
Only gpt-oss-20b has a MMLU Pro result, 71.6%.
Directional only
Web design
Design Arena: websites
No call
Only gpt-oss-20b has a Design Arena: websites result, 852.
Directional only
General
Vals Index
No call
Only MiMo-V2.6-Flash has a Vals Index result, 54.8%.
Directional only
Long documents
Listed context window
MiMo-V2.6-Flash
MiMo-V2.6-Flash takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-20b
gpt-oss-20b $0.0001, MiMo-V2.6-Flash $0.0003 per turn.
List prices
At a glance
- Coding index
- gpt-oss-20b not benchmarked, MiMo-V2.6-Flash 54.7 from 3 benchmarks.
- Widest category
- Reasoning, 32.7 points apart on average over 4 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): gpt-oss-20b 34.7% against MiMo-V2.6-Flash 74.3%, 39.7 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-20b $0.15 against MiMo-V2.6-Flash $0.28 per million output tokens, 1.9x apart.
- Context window
- gpt-oss-20b takes 131K tokens, MiMo-V2.6-Flash 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | gpt-oss-20b | Bars | MiMo-V2.6-Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 32 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1634 | Only MiMo-V2.6-Flash measured |
| LiveCodeBench (Vals AI) | 80.4% | Not measured | Only gpt-oss-20b measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 24.2% | Only MiMo-V2.6-Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 79.0% | Only MiMo-V2.6-Flash measured |
| Code migration (Vals AI) | Not measured | 40.9% | Only MiMo-V2.6-Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only MiMo-V2.6-Flash measured |
| IOI (Vals AI) | Not measured | 47.7% | Only MiMo-V2.6-Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 76.4% | Only MiMo-V2.6-Flash measured |
| CyberBench (Vals AI) | Not measured | 75.4% | Only MiMo-V2.6-Flash measured |
| LiveCodeBench (Artificial Analysis run) | 77.7% | Not measured | Only gpt-oss-20b measured |
| SciCode | 38.9% | 51.3% | MiMo-V2.6-Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 10.6% | Not measured | Only gpt-oss-20b measured |
| Terminal-Bench | 3.4% | Not measured | Only gpt-oss-20b measured |
| WeirdML | 40.9% | Not measured | Only gpt-oss-20b measured |
| ALE-Bench | 566.0 | 1244.2 | MiMo-V2.6-Flash |
| LMArena Text: coding | 1307 | 1499 | MiMo-V2.6-Flash |
| LMArena Text: software and IT | 1311 | 1497 | MiMo-V2.6-Flash |
| LMArena WebDev: React | Not measured | 1648 | Only MiMo-V2.6-Flash measured |
| LMArena WebDev: HTML | Not measured | 1641 | Only MiMo-V2.6-Flash measured |
| LMArena WebDev: from an image | Not measured | 1596 | Only MiMo-V2.6-Flash measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.0 | 37.9 | MiMo-V2.6-Flash |
| Epoch Capabilities Index | 137.7 | Not measured | Only gpt-oss-20b measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| SREBench (Vals AI) | Not measured | 4.2% | Only MiMo-V2.6-Flash measured |
| Finance Agent (Vals AI) | Not measured | 56.3% | Only MiMo-V2.6-Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 28.5% | Only MiMo-V2.6-Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 38.0% | Only MiMo-V2.6-Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.3% | Only MiMo-V2.6-Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 65.5% | Only MiMo-V2.6-Flash measured |
| BioMysteryBench (Vals AI) | Not measured | 69.3% | Only MiMo-V2.6-Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 4.3% | Only MiMo-V2.6-Flash measured |
| Vals Science Index | Not measured | 31.7% | Only MiMo-V2.6-Flash measured |
| τ²-Bench Telecom | 60.2% | Not measured | Only gpt-oss-20b measured |
| BrowseComp-Plus | 50.6% | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 68.9% | Not measured | Only gpt-oss-20b measured |
| MysteryMechanism (Vals AI) | Not measured | 21.6% | Only MiMo-V2.6-Flash measured |
| GPQA Diamond (Artificial Analysis run) | 68.8% | Not measured | Only gpt-oss-20b measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.0% | 35.1% | MiMo-V2.6-Flash |
| GPQA Diamond (Epoch AI run) | 60.8% | Not measured | Only gpt-oss-20b measured |
| LMArena Text: hard prompts | 1274 | 1475 | MiMo-V2.6-Flash |
| LMArena Text: expert | 1258 | 1496 | MiMo-V2.6-Flash |
| LMArena Text: hard prompts in English | 1292 | 1493 | MiMo-V2.6-Flash |
| LMArena Vision: diagrams | Not measured | 1276 | Only MiMo-V2.6-Flash measured |
| LMArena Vision: homework | Not measured | 1283 | Only MiMo-V2.6-Flash measured |
| Kagi LLM Benchmark | 53.2% | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| AIME | 86.0% | Not measured | Only gpt-oss-20b measured |
| MATH 500 (Vals AI) | 94.2% | Not measured | Only gpt-oss-20b measured |
| MGSM (Vals AI) | 89.0% | Not measured | Only gpt-oss-20b measured |
| AA Math Index | 89.3 | Not measured | Only gpt-oss-20b measured |
| AIME 2025 (Artificial Analysis run) | 89.3% | Not measured | Only gpt-oss-20b measured |
| OTIS Mock AIME | 65.3% | Not measured | Only gpt-oss-20b measured |
| ProofBench | Not measured | 63.0% | Only MiMo-V2.6-Flash measured |
| LMArena Text: math | 1317 | 1476 | MiMo-V2.6-Flash |
| LMArena Text: mathematical work | 1305 | 1478 | MiMo-V2.6-Flash |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| MMLU Pro | 71.6% | Not measured | Only gpt-oss-20b measured |
| LegalBench (Vals AI) | 70.8% | Not measured | Only gpt-oss-20b measured |
| CaseLaw (Vals AI) | 43.8% | Not measured | Only gpt-oss-20b measured |
| CorpFin (Vals AI) | 53.1% | Not measured | Only gpt-oss-20b measured |
| TaxEval (Vals AI) | 63.7% | Not measured | Only gpt-oss-20b measured |
| MedQA (Vals AI) | 82.9% | Not measured | Only gpt-oss-20b measured |
| MedCode (Vals AI) | Not measured | 41.1% | Only MiMo-V2.6-Flash measured |
| MMLU Pro (Artificial Analysis run) | 74.8% | Not measured | Only gpt-oss-20b measured |
| LMArena Text: science | 1296 | 1462 | MiMo-V2.6-Flash |
| LMArena Text: medicine and healthcare | 1310 | 1439 | MiMo-V2.6-Flash |
| LMArena Text: legal and government | 1280 | 1441 | MiMo-V2.6-Flash |
| LMArena Text: business and finance | 1284 | 1454 | MiMo-V2.6-Flash |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 852 | Not measured | Only gpt-oss-20b measured |
| Design Arena: data viz | 933 | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 7 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 54.8% | Only MiMo-V2.6-Flash measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.6% | Only MiMo-V2.6-Flash measured |
| SAGE (Vals AI) | Not measured | 43.5% | Only MiMo-V2.6-Flash measured |
| MedScribe (Vals AI) | Not measured | 85.3% | Only MiMo-V2.6-Flash measured |
| IFBench | 65.1% | Not measured | Only gpt-oss-20b measured |
| Long context reasoning (AA-LCR) | 34.7% | 74.3% | MiMo-V2.6-Flash |
| DTBench | 68.0% | Not measured | Only gpt-oss-20b measured |
| LMCA | 14.5% | Not measured | Only gpt-oss-20b measured |
| LMArena Text | 1288 | 1453 | MiMo-V2.6-Flash |
| LMArena Text: instruction following | 1236 | 1452 | MiMo-V2.6-Flash |
| LMArena Text: creative writing | 1201 | 1403 | MiMo-V2.6-Flash |
| LMArena Vision | Not measured | 1256 | Only MiMo-V2.6-Flash measured |
| LMArena Text: English | 1303 | 1476 | MiMo-V2.6-Flash |
| LMArena Text: non-English | 1269 | 1431 | MiMo-V2.6-Flash |
| LMArena Text: Chinese | 1315 | 1509 | MiMo-V2.6-Flash |
| LMArena Text: German | 1255 | 1458 | MiMo-V2.6-Flash |
| LMArena Text: Japanese | 1244 | 1359 | MiMo-V2.6-Flash |
| LMArena Text: Korean | 1236 | 1425 | MiMo-V2.6-Flash |
| LMArena Text: French | Not measured | 1480 | Only MiMo-V2.6-Flash measured |
| LMArena Text: Spanish | 1267 | 1453 | MiMo-V2.6-Flash |
| LMArena Text: Russian | 1278 | 1409 | MiMo-V2.6-Flash |
| LMArena Text: Polish | 1252 | 1455 | MiMo-V2.6-Flash |
| LMArena Text: multi-turn | 1268 | 1447 | MiMo-V2.6-Flash |
| LMArena Text: longer queries | 1250 | 1459 | MiMo-V2.6-Flash |
| LMArena Text: writing and language | 1238 | 1424 | MiMo-V2.6-Flash |
| LMArena Text: entertainment and media | 1216 | 1415 | MiMo-V2.6-Flash |
| LMArena Vision: English | Not measured | 1269 | Only MiMo-V2.6-Flash measured |
| LMArena Vision: reading text | Not measured | 1270 | Only MiMo-V2.6-Flash measured |
| LMArena Vision: creative writing | Not measured | 1231 | Only MiMo-V2.6-Flash measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-20b | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
gpt-oss-20b costs less
Repository review
50K input + 3K output tokens
gpt-oss-20b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-20b costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI gpt-oss-20b | Xiaomi MiMo-V2.6-Flash |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | Open weights | Open weights |
| Released | August 5, 2025 | September 21, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.03 | $0.14 |
| Output $/Mtok | $0.15 | $0.28 |
| Coding index | Not benchmarked | 54.7 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-20b better than MiMo-V2.6-Flash for coding?
Only MiMo-V2.6-Flash has a coding score, 54.7 on the Vibe Coding Index; gpt-oss-20b has none, so the two cannot be ranked on coding. Pick gpt-oss-20b for output tokens 1.9x cheaper ($0.15 vs $0.28 per million).
Which is cheaper, gpt-oss-20b or MiMo-V2.6-Flash?
gpt-oss-20b costs $0.03 per million input tokens and $0.15 per million output tokens; MiMo-V2.6-Flash costs $0.14 and $0.28. Cost per solved task is known for neither of them.
Which has the bigger context window, gpt-oss-20b or MiMo-V2.6-Flash?
MiMo-V2.6-Flash, with 1.05M tokens against 131K.
How many benchmarks is the gpt-oss-20b vs MiMo-V2.6-Flash comparison based on?
32 benchmarks have a result for both models as of October 21, 2026. gpt-oss-20b's coding index rests on 0 independent benchmarks and MiMo-V2.6-Flash's on 3. Where only one model has a result, the page says so instead of naming a winner.