MiniMax M2.1 vs o4 Mini
MiniMax M2.1 leads o4 Mini on the Artificial Analysis Intelligence Index, 20.9 to 16.7, and MiniMax M2.1 costs 3.7x less per output token ($1.20 vs $4.40 per million). Updated October 21, 2026; 29 benchmarks have a result for both.
MiniMax M2.1 or o4 Mini: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick MiniMax M2.1 for output tokens 3.7x cheaper ($1.20 vs $4.40 per million) and a larger context window (205K against 200K tokens).
- Shared results
- 29
- MiniMax M2.1 only
- 5
- o4 Mini only
- 69
- Like-for-like categories
- 8 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 M2.1
MiniMax M2.1 leads, 20.9 against 16.7.
Same board, both measured
Reasoning
GPQA Diamond
MiniMax M2.1
MiniMax M2.1 leads, 78.5% against 74.5%.
Same board, both measured
Math
AIME
o4 Mini
o4 Mini leads, 83.7% against 77.9%.
Same board, both measured
Knowledge
MMLU Pro
MiniMax M2.1
MiniMax M2.1 leads, 87.0% against 80.6%.
Same board, both measured
Web design
Design Arena: websites
MiniMax M2.1
MiniMax M2.1 leads, 1201 against 985.
Same board, both measured
Long documents
Listed context window
MiniMax M2.1
MiniMax M2.1 takes 205K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.1
MiniMax M2.1 $0.0009, o4 Mini $0.0033 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.1 has the number, $0.59.
Directional only
At a glance
- Coding index
- MiniMax M2.1 not benchmarked, o4 Mini not benchmarked.
- Widest category
- Agentic work, 29.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: 3D: MiniMax M2.1 1165 against o4 Mini 854, 38.9 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2.1 $1.20 against o4 Mini $4.40 per million output tokens, 3.7x apart.
- Context window
- MiniMax M2.1 takes 205K tokens, o4 Mini 200K.
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 | MiniMax M2.1 | Bars | o4 Mini | Ties |
|---|---|---|---|---|
| Coding | 1 | 2 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 0 | 5 | ||
| Knowledge | 3 | 4 | ||
| Web design | 6 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 18 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 72.0% | Only o4 Mini measured |
| SWE-bench Verified | Not measured | 64.6% | Only o4 Mini measured |
| SWE-bench Multimodal | Not measured | 33.9% | Only o4 Mini measured |
| LiveCodeBench (Vals AI) | 81.8% | 82.2% | o4 Mini |
| SWE-bench Verified (Vals AI) | 74.8% | Not measured | Only MiniMax M2.1 measured |
| LiveCodeBench (Artificial Analysis run) | 81.0% | 85.9% | o4 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 28.8% | 15.2% | MiniMax M2.1 |
| Terminal-Bench | 36.6% | Not measured | Only MiniMax M2.1 measured |
| GSO-Bench | Not measured | 3.6% | Only o4 Mini measured |
| WeirdML | Not measured | 52.6% | Only o4 Mini measured |
| ALE-Bench | 623.8 | Not measured | Only MiniMax M2.1 measured |
| LMArena Text: coding | Not measured | 1368 | Only o4 Mini measured |
| LMArena Text: software and IT | Not measured | 1367 | Only o4 Mini measured |
| SciCode | Not measured | 10.8% | Only o4 Mini measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.9 | 16.7 | MiniMax M2.1 |
| Epoch Capabilities Index | Not measured | 145.5 | Only o4 Mini measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 85.4% | 55.6% | MiniMax M2.1 |
| METR time horizons | Not measured | 63.9% | Only o4 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 53.2% | Only o4 Mini measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | 74.5% | MiniMax M2.1 |
| MMMU Pro (Vals AI) | Not measured | 79.7% | Only o4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 83.0% | 78.4% | MiniMax M2.1 |
| Humanity's Last Exam (Artificial Analysis run) | 23.2% | 16.5% | MiniMax M2.1 |
| GPQA Diamond (Epoch AI run) | Not measured | 79.6% | Only o4 Mini measured |
| ARC-AGI | Not measured | 58.7% | Only o4 Mini measured |
| ARC-AGI-2 | Not measured | 6.1% | Only o4 Mini measured |
| SimpleBench | Not measured | 38.7% | Only o4 Mini measured |
| Chess puzzles | Not measured | 22.0% | Only o4 Mini measured |
| Mystery game puzzles | Not measured | 5.0% | Only o4 Mini measured |
| VPCT | Not measured | 57.5% | Only o4 Mini measured |
| LMArena Text: hard prompts | Not measured | 1351 | Only o4 Mini measured |
| LMArena Text: expert | Not measured | 1343 | Only o4 Mini measured |
| LMArena Text: hard prompts in English | Not measured | 1366 | Only o4 Mini measured |
| LMArena Vision: diagrams | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: homework | Not measured | 1234 | Only o4 Mini measured |
| Kagi LLM Benchmark | Not measured | 67.6% | Only o4 Mini measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| AIME | 77.9% | 83.7% | o4 Mini |
| MATH 500 (Vals AI) | 89.0% | 94.2% | o4 Mini |
| MGSM (Vals AI) | 87.8% | 93.4% | o4 Mini |
| AA Math Index | 82.7 | 90.7 | o4 Mini |
| AIME 2025 (Artificial Analysis run) | 82.7% | 90.7% | o4 Mini |
| OTIS Mock AIME | Not measured | 81.7% | Only o4 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 36.1% | Only o4 Mini measured |
| FrontierMath, tier 4 | Not measured | 4.9% | Only o4 Mini measured |
| MATH level 5 | Not measured | 97.8% | Only o4 Mini measured |
| LMArena Text: math | Not measured | 1389 | Only o4 Mini measured |
| LMArena Text: mathematical work | Not measured | 1379 | Only o4 Mini measured |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index34
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | 80.6% | MiniMax M2.1 |
| LegalBench (Vals AI) | 75.5% | 79.2% | o4 Mini |
| CaseLaw (Vals AI) | 55.8% | Not measured | Only MiniMax M2.1 measured |
| CorpFin (Vals AI) | 58.9% | 59.0% | o4 Mini |
| TaxEval (Vals AI) | 66.3% | 74.8% | o4 Mini |
| MortgageTax (Vals AI) | Not measured | 64.8% | Only o4 Mini measured |
| MedQA (Vals AI) | 91.2% | 96.0% | o4 Mini |
| MedCode (Vals AI) | 34.1% | 33.8% | MiniMax M2.1 |
| MMLU Pro (Artificial Analysis run) | 87.5% | 83.2% | MiniMax M2.1 |
| SimpleQA Verified | Not measured | 19.6% | Only o4 Mini measured |
| GeoBench | Not measured | 64.0% | Only o4 Mini measured |
| LMArena Text: science | Not measured | 1354 | Only o4 Mini measured |
| LMArena Text: medicine and healthcare | Not measured | 1361 | Only o4 Mini measured |
| LMArena Text: legal and government | Not measured | 1350 | Only o4 Mini measured |
| LMArena Text: business and finance | Not measured | 1325 | Only o4 Mini measured |
| FACTS Benchmark Suite | Not measured | 28.1% | Only o4 Mini measured |
| Neither model has a result on the other 2 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 1201 | 985 | MiniMax M2.1 |
| Design Arena: UI components | 1223 | 983 | MiniMax M2.1 |
| Design Arena: game dev | 1134 | 1003 | MiniMax M2.1 |
| Design Arena: data viz | 1206 | 990 | MiniMax M2.1 |
| Design Arena: 3D | 1165 | 854 | MiniMax M2.1 |
| Design Arena: all code categories | 1190 | 976 | MiniMax M2.1 |
| Design Arena: SVG | 1132 | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | MiniMax M2.1 | o4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.1% | Only o4 Mini measured |
| MedScribe (Vals AI) | 80.8% | 69.1% | MiniMax M2.1 |
| IFBench | 69.9% | 68.7% | MiniMax M2.1 |
| Long context reasoning (AA-LCR) | 67.7% | 61.0% | MiniMax M2.1 |
| DTBench | Not measured | 77.6% | Only o4 Mini measured |
| LMCA | Not measured | 26.5% | Only o4 Mini measured |
| Fiction.LiveBench | Not measured | 77.8% | Only o4 Mini measured |
| Creative writing (Lech Mazur) | Not measured | 75.0% | Only o4 Mini measured |
| LMArena Text | Not measured | 1353 | Only o4 Mini measured |
| LMArena Text: instruction following | Not measured | 1320 | Only o4 Mini measured |
| LMArena Text: creative writing | Not measured | 1294 | Only o4 Mini measured |
| LMArena Vision | Not measured | 1194 | Only o4 Mini measured |
| LMArena Text: English | Not measured | 1367 | Only o4 Mini measured |
| LMArena Text: non-English | Not measured | 1337 | Only o4 Mini measured |
| LMArena Text: Chinese | Not measured | 1354 | Only o4 Mini measured |
| LMArena Text: German | Not measured | 1336 | Only o4 Mini measured |
| LMArena Text: Japanese | Not measured | 1308 | Only o4 Mini measured |
| LMArena Text: Korean | Not measured | 1312 | Only o4 Mini measured |
| LMArena Text: French | Not measured | 1364 | Only o4 Mini measured |
| LMArena Text: Spanish | Not measured | 1346 | Only o4 Mini measured |
| LMArena Text: Russian | Not measured | 1334 | Only o4 Mini measured |
| LMArena Text: Polish | Not measured | 1358 | Only o4 Mini measured |
| LMArena Text: multi-turn | Not measured | 1350 | Only o4 Mini measured |
| LMArena Text: longer queries | Not measured | 1315 | Only o4 Mini measured |
| LMArena Text: writing and language | Not measured | 1316 | Only o4 Mini measured |
| LMArena Text: entertainment and media | Not measured | 1308 | Only o4 Mini measured |
| LMArena Vision: English | Not measured | 1200 | Only o4 Mini measured |
| LMArena Vision: Chinese | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: reading text | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: humor | Not measured | 1199 | Only o4 Mini measured |
| LMArena Vision: captioning | Not measured | 1204 | Only o4 Mini measured |
| LMArena Vision: recognizing things | Not measured | 1218 | Only o4 Mini measured |
| LMArena Vision: creative writing | Not measured | 1166 | Only o4 Mini measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M2.1 | o4 Mini | 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
MiniMax M2.1 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.1 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.1 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 | MiniMax M2.1 | OpenAI o4 Mini |
|---|---|---|
| Maker | MiniMax | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | December 23, 2025 | April 16, 2025 |
| Context window | 205K | 200K |
| Input $/Mtok | $0.30 | $1.10 |
| Output $/Mtok | $1.20 | $4.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.59 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.1 better than o4 Mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M2.1 for output tokens 3.7x cheaper ($1.20 vs $4.40 per million) and a larger context window (205K against 200K tokens).
Which is cheaper, MiniMax M2.1 or o4 Mini?
MiniMax M2.1 costs $0.30 per million input tokens and $1.20 per million output tokens; o4 Mini costs $1.10 and $4.40. Cost per solved task is known for MiniMax M2.1 only.
Which has the bigger context window, MiniMax M2.1 or o4 Mini?
MiniMax M2.1, with 205K tokens against 200K.
How many benchmarks is the MiniMax M2.1 vs o4 Mini comparison based on?
29 benchmarks have a result for both models as of October 21, 2026. MiniMax M2.1's coding index rests on 1 independent benchmark and o4 Mini's on 0. Where only one model has a result, the page says so instead of naming a winner.