gpt-oss-20b vs MiniMax M1
MiniMax M1 leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 11.7 to 10.0, and gpt-oss-20b costs 14.7x less per output token ($0.15 vs $2.20 per million). Updated October 22, 2026; 28 benchmarks have a result for both.
gpt-oss-20b or MiniMax M1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick gpt-oss-20b for output tokens 14.7x cheaper ($0.15 vs $2.20 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 28
- gpt-oss-20b only
- 34
- MiniMax M1 only
- 1
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M1
MiniMax M1 leads, 11.7 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
Long documents
Listed context window
MiniMax M1
MiniMax M1 takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-20b
gpt-oss-20b $0.0001, MiniMax M1 $0.0015 per turn.
List prices
At a glance
- Coding index
- gpt-oss-20b not benchmarked, MiniMax M1 not benchmarked.
- Widest category
- General, 10.9 points apart on average over 16 shared benchmarks.
- Widest single gap
- LMArena Text: creative writing: gpt-oss-20b 1201 against MiniMax M1 1297, 16.0 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-20b $0.15 against MiniMax M1 $2.20 per million output tokens, 14.7x apart.
- Context window
- gpt-oss-20b takes 131K tokens, MiniMax M1 1M.
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 | MiniMax M1 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 1 | 15 | ||
| All shared boards | 1 | 27 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | gpt-oss-20b | MiniMax M1 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 80.4% | Not measured | Only gpt-oss-20b measured |
| LiveCodeBench (Artificial Analysis run) | 77.7% | Not measured | Only gpt-oss-20b measured |
| SciCode | 38.9% | Not measured | Only gpt-oss-20b measured |
| 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 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: coding | 1307 | 1359 | MiniMax M1 |
| LMArena Text: software and IT | 1311 | 1359 | MiniMax M1 |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-20b | MiniMax M1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.0 | 11.7 | MiniMax M1 |
| Epoch Capabilities Index | 137.7 | Not measured | Only gpt-oss-20b measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | gpt-oss-20b | MiniMax M1 | Leader |
|---|---|---|---|
| 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 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | gpt-oss-20b | MiniMax M1 | Leader |
|---|---|---|---|
| GPQA Diamond | 68.9% | Not measured | Only gpt-oss-20b measured |
| GPQA Diamond (Artificial Analysis run) | 68.8% | Not measured | Only gpt-oss-20b measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.0% | Not measured | Only gpt-oss-20b measured |
| GPQA Diamond (Epoch AI run) | 60.8% | Not measured | Only gpt-oss-20b measured |
| LMArena Text: hard prompts | 1274 | 1339 | MiniMax M1 |
| LMArena Text: expert | 1258 | 1317 | MiniMax M1 |
| LMArena Text: hard prompts in English | 1292 | 1353 | MiniMax M1 |
| Kagi LLM Benchmark | 53.2% | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-20b | MiniMax M1 | 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 |
| LMArena Text: math | 1317 | 1361 | MiniMax M1 |
| LMArena Text: mathematical work | 1305 | 1363 | MiniMax M1 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-20b | MiniMax M1 | 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 |
| MMLU Pro (Artificial Analysis run) | 74.8% | Not measured | Only gpt-oss-20b measured |
| LMArena Text: science | 1296 | 1354 | MiniMax M1 |
| LMArena Text: medicine and healthcare | 1310 | 1355 | MiniMax M1 |
| LMArena Text: legal and government | 1280 | 1337 | MiniMax M1 |
| LMArena Text: business and finance | 1284 | 1319 | MiniMax M1 |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | gpt-oss-20b | MiniMax M1 | 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 index115
| Benchmark | gpt-oss-20b | MiniMax M1 | Leader |
|---|---|---|---|
| IFBench | 65.1% | Not measured | Only gpt-oss-20b measured |
| Long context reasoning (AA-LCR) | 34.7% | Not measured | Only gpt-oss-20b measured |
| DTBench | 68.0% | Not measured | Only gpt-oss-20b measured |
| LMCA | 14.5% | Not measured | Only gpt-oss-20b measured |
| LMArena Text | 1288 | 1343 | MiniMax M1 |
| LMArena Text: instruction following | 1236 | 1312 | MiniMax M1 |
| LMArena Text: creative writing | 1201 | 1297 | MiniMax M1 |
| LMArena Text: English | 1303 | 1363 | MiniMax M1 |
| LMArena Text: non-English | 1269 | 1319 | MiniMax M1 |
| LMArena Text: Chinese | 1315 | 1360 | MiniMax M1 |
| LMArena Text: German | 1255 | 1350 | MiniMax M1 |
| LMArena Text: Japanese | 1244 | 1217 | gpt-oss-20b |
| LMArena Text: Korean | 1236 | 1266 | MiniMax M1 |
| LMArena Text: French | Not measured | 1370 | Only MiniMax M1 measured |
| LMArena Text: Spanish | 1267 | 1353 | MiniMax M1 |
| LMArena Text: Russian | 1278 | 1329 | MiniMax M1 |
| LMArena Text: Polish | 1252 | 1329 | MiniMax M1 |
| LMArena Text: multi-turn | 1268 | 1335 | MiniMax M1 |
| LMArena Text: longer queries | 1250 | 1326 | MiniMax M1 |
| LMArena Text: writing and language | 1238 | 1311 | MiniMax M1 |
| LMArena Text: entertainment and media | 1216 | 1303 | MiniMax M1 |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-20b | MiniMax M1 | 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 | MiniMax M1 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | Open weights | No public weights listed |
| Released | August 5, 2025 | June 17, 2025 |
| Context window | 131K | 1M |
| Input $/Mtok | $0.03 | $0.40 |
| Output $/Mtok | $0.15 | $2.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-20b better than MiniMax M1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick gpt-oss-20b for output tokens 14.7x cheaper ($0.15 vs $2.20 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, gpt-oss-20b or MiniMax M1?
gpt-oss-20b costs $0.03 per million input tokens and $0.15 per million output tokens; MiniMax M1 costs $0.40 and $2.20. Cost per solved task is known for neither of them.
Which has the bigger context window, gpt-oss-20b or MiniMax M1?
MiniMax M1, with 1M tokens against 131K.
How many benchmarks is the gpt-oss-20b vs MiniMax M1 comparison based on?
28 benchmarks have a result for both models as of October 22, 2026. gpt-oss-20b's coding index rests on 0 independent benchmarks and MiniMax M1's on 0. Where only one model has a result, the page says so instead of naming a winner.