gpt-oss-120b vs MiniMax M1
MiniMax M1 leads gpt-oss-120b on the Artificial Analysis Intelligence Index, 11.7 to 11.6, and gpt-oss-120b costs 4.4x less per output token ($0.50 vs $2.20 per million). Updated October 22, 2026; 29 benchmarks have a result for both.
gpt-oss-120b or MiniMax M1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick gpt-oss-120b for output tokens 4.4x cheaper ($0.50 vs $2.20 per million) and work measured by AA Intelligence Index or LMArena Text: creative writing, where it leads.
- Shared results
- 29
- gpt-oss-120b only
- 56
- MiniMax M1 only
- 0
- 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 11.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only gpt-oss-120b has a AA Agentic Index result, 3.7.
Directional only
Reasoning
GPQA Diamond
No call
Only gpt-oss-120b has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
No call
Only gpt-oss-120b has a MMLU Pro result, 79.2%.
Directional only
Web design
Design Arena: websites
No call
Only gpt-oss-120b has a Design Arena: websites result, 968.
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-120b
gpt-oss-120b $0.0003, MiniMax M1 $0.0015 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only gpt-oss-120b has the number, $0.51.
Directional only
At a glance
- Coding index
- gpt-oss-120b not benchmarked, MiniMax M1 not benchmarked.
- Widest category
- Knowledge, 4.9 points apart on average over 4 shared benchmarks.
- Widest single gap
- LMArena Text: Japanese: gpt-oss-120b 1331 against MiniMax M1 1217, 19.0 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-120b $0.50 against MiniMax M1 $2.20 per million output tokens, 4.4x apart.
- Context window
- gpt-oss-120b 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-120b | Bars | MiniMax M1 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 12 | 5 | ||
| All shared boards | 23 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| Aider polyglot | 41.8% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified | 26.0% | Not measured | Only gpt-oss-120b measured |
| AA Coding Index | 30.4 | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Vals AI) | 83.2% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified (Vals AI) | 33.6% | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Artificial Analysis run) | 87.8% | Not measured | Only gpt-oss-120b measured |
| SciCode | 34.0% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench | 18.7% | Not measured | Only gpt-oss-120b measured |
| WeirdML | 48.2% | Not measured | Only gpt-oss-120b measured |
| ALE-Bench | 575.6 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: coding | 1379 | 1359 | gpt-oss-120b |
| LMArena Text: software and IT | 1387 | 1359 | gpt-oss-120b |
| SciCode | 7.7% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.6 | 11.7 | MiniMax M1 |
| Epoch Capabilities Index | 139.8 | Not measured | Only gpt-oss-120b measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| AA Agentic Index | 3.7 | Not measured | Only gpt-oss-120b measured |
| τ²-Bench Telecom | 65.8% | Not measured | Only gpt-oss-120b measured |
| APEX-Agents | 4.4% | Not measured | Only gpt-oss-120b measured |
| METR time horizons | 56.6% | Not measured | Only gpt-oss-120b measured |
| Vending-Bench 2 | -$22 | Not measured | Only gpt-oss-120b measured |
| BrowseComp-Plus | 67.0% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | Not measured | Only gpt-oss-120b measured |
| GPQA Diamond (Artificial Analysis run) | 78.2% | Not measured | Only gpt-oss-120b measured |
| Humanity's Last Exam (Artificial Analysis run) | 19.6% | Not measured | Only gpt-oss-120b measured |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only gpt-oss-120b measured |
| SimpleBench | 22.1% | Not measured | Only gpt-oss-120b measured |
| Mystery game puzzles | 2.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: hard prompts | 1364 | 1339 | gpt-oss-120b |
| LMArena Text: expert | 1356 | 1317 | gpt-oss-120b |
| LMArena Text: hard prompts in English | 1368 | 1353 | gpt-oss-120b |
| Kagi LLM Benchmark | 58.6% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| AIME | 92.6% | Not measured | Only gpt-oss-120b measured |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only gpt-oss-120b measured |
| MGSM (Vals AI) | 92.0% | Not measured | Only gpt-oss-120b measured |
| AA Math Index | 93.4 | Not measured | Only gpt-oss-120b measured |
| AIME 2025 (Artificial Analysis run) | 93.4% | Not measured | Only gpt-oss-120b measured |
| OTIS Mock AIME | 88.9% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: math | 1389 | 1361 | gpt-oss-120b |
| LMArena Text: mathematical work | 1386 | 1363 | gpt-oss-120b |
| MathArena | 15.1% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| MMLU Pro | 79.2% | Not measured | Only gpt-oss-120b measured |
| LegalBench (Vals AI) | 75.9% | Not measured | Only gpt-oss-120b measured |
| CaseLaw (Vals AI) | 48.8% | Not measured | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 58.2% | Not measured | Only gpt-oss-120b measured |
| TaxEval (Vals AI) | 71.6% | Not measured | Only gpt-oss-120b measured |
| MedQA (Vals AI) | 91.4% | Not measured | Only gpt-oss-120b measured |
| MMLU Pro (Artificial Analysis run) | 80.8% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: science | 1382 | 1354 | gpt-oss-120b |
| LMArena Text: medicine and healthcare | 1388 | 1355 | gpt-oss-120b |
| LMArena Text: legal and government | 1355 | 1337 | gpt-oss-120b |
| LMArena Text: business and finance | 1359 | 1319 | gpt-oss-120b |
| PRBench Finance | 43.8% | Not measured | Only gpt-oss-120b measured |
| PRBench Legal | 40.2% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| Design Arena: websites | 968 | Not measured | Only gpt-oss-120b measured |
| Design Arena: UI components | 924 | Not measured | Only gpt-oss-120b measured |
| Design Arena: game dev | 991 | Not measured | Only gpt-oss-120b measured |
| Design Arena: data viz | 987 | Not measured | Only gpt-oss-120b measured |
| Design Arena: 3D | 901 | Not measured | Only gpt-oss-120b measured |
| Design Arena: all code categories | 962 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index125
| Benchmark | gpt-oss-120b | MiniMax M1 | Leader |
|---|---|---|---|
| IFBench | 69.0% | Not measured | Only gpt-oss-120b measured |
| Long context reasoning (AA-LCR) | 52.0% | Not measured | Only gpt-oss-120b measured |
| DTBench | 76.3% | Not measured | Only gpt-oss-120b measured |
| LMCA | 22.1% | Not measured | Only gpt-oss-120b measured |
| Fiction.LiveBench | 44.4% | Not measured | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | 77.1% | Not measured | Only gpt-oss-120b measured |
| Surface Evolver Bench | 25.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text | 1366 | 1343 | gpt-oss-120b |
| LMArena Text: instruction following | 1318 | 1312 | gpt-oss-120b |
| LMArena Text: creative writing | 1274 | 1297 | MiniMax M1 |
| LMArena Text: English | 1375 | 1363 | gpt-oss-120b |
| LMArena Text: non-English | 1351 | 1319 | gpt-oss-120b |
| LMArena Text: Chinese | 1385 | 1360 | gpt-oss-120b |
| LMArena Text: German | 1353 | 1350 | gpt-oss-120b |
| LMArena Text: Japanese | 1331 | 1217 | gpt-oss-120b |
| LMArena Text: Korean | 1282 | 1266 | gpt-oss-120b |
| LMArena Text: French | 1370 | 1370 | MiniMax M1 |
| LMArena Text: Spanish | 1389 | 1353 | gpt-oss-120b |
| LMArena Text: Russian | 1343 | 1329 | gpt-oss-120b |
| LMArena Text: Polish | 1353 | 1329 | gpt-oss-120b |
| LMArena Text: multi-turn | 1340 | 1335 | gpt-oss-120b |
| LMArena Text: longer queries | 1319 | 1326 | MiniMax M1 |
| LMArena Text: writing and language | 1306 | 1311 | MiniMax M1 |
| LMArena Text: entertainment and media | 1292 | 1303 | MiniMax M1 |
| MultiChallenge | 45.3% | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-120b | 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-120b costs less
Repository review
50K input + 3K output tokens
gpt-oss-120b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-120b 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-120b | 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 | $0.10 | $0.40 |
| Output $/Mtok | $0.50 | $2.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.51 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-120b better than MiniMax M1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick gpt-oss-120b for output tokens 4.4x cheaper ($0.50 vs $2.20 per million) and work measured by AA Intelligence Index or LMArena Text: creative writing, where it leads.
Which is cheaper, gpt-oss-120b or MiniMax M1?
gpt-oss-120b costs $0.10 per million input tokens and $0.50 per million output tokens; MiniMax M1 costs $0.40 and $2.20. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, gpt-oss-120b or MiniMax M1?
MiniMax M1, with 1M tokens against 131K.
How many benchmarks is the gpt-oss-120b vs MiniMax M1 comparison based on?
29 benchmarks have a result for both models as of October 22, 2026. gpt-oss-120b's coding index rests on 1 independent benchmark and MiniMax M1's on 0. Where only one model has a result, the page says so instead of naming a winner.