MiniMax M2 vs o4 Mini
MiniMax M2 leads o4 Mini on the Artificial Analysis Intelligence Index, 18.6 to 16.7, and MiniMax M2 costs 4.3x less per output token ($1.02 vs $4.40 per million). Updated October 21, 2026; 45 benchmarks have a result for both.
MiniMax M2 or o4 Mini: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick MiniMax M2 for output tokens 4.3x cheaper ($1.02 vs $4.40 per million) and a larger context window (205K against 200K tokens).
- Shared results
- 45
- MiniMax M2 only
- 5
- o4 Mini only
- 53
- 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
MiniMax M2 leads, 18.6 against 16.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only o4 Mini has a GPQA Diamond result, 74.5%.
Directional only
Math
AIME
No call
Only o4 Mini has a AIME result, 83.7%.
Directional only
Knowledge
MMLU Pro
No call
Only o4 Mini has a MMLU Pro result, 80.6%.
Directional only
Web design
Design Arena: websites
MiniMax M2
MiniMax M2 leads, 1143 against 985.
Same board, both measured
Long documents
Listed context window
MiniMax M2
MiniMax M2 takes 205K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2
MiniMax M2 $0.0008, o4 Mini $0.0033 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2 has the number, $0.702.
Directional only
At a glance
- Coding index
- MiniMax M2 not benchmarked, o4 Mini not benchmarked.
- Widest category
- Agentic work, 31.3 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: MiniMax M2 86.8% against o4 Mini 55.6%, 31.3 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2 $1.02 against o4 Mini $4.40 per million output tokens, 4.3x apart.
- Context window
- MiniMax M2 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 | Bars | o4 Mini | Ties |
|---|---|---|---|---|
| Coding | 3 | 2 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 4 | ||
| Math | 0 | 4 | ||
| Knowledge | 2 | 3 | ||
| Web design | 6 | 0 | ||
| General | 7 | 10 | ||
| All shared boards | 22 | 23 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
| Benchmark | MiniMax M2 | o4 Mini | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 72.0% | Only o4 Mini measured |
| SWE-bench Verified | 61.0% | 64.6% | o4 Mini |
| SWE-bench Multimodal | Not measured | 33.9% | Only o4 Mini measured |
| LMArena WebDev | 1297 | Not measured | Only MiniMax M2 measured |
| LiveCodeBench (Vals AI) | Not measured | 82.2% | Only o4 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 82.6% | 85.9% | o4 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 25.8% | 15.2% | MiniMax M2 |
| Terminal-Bench | 30.0% | Not measured | Only MiniMax M2 measured |
| GSO-Bench | Not measured | 3.6% | Only o4 Mini measured |
| WeirdML | Not measured | 52.6% | Only o4 Mini measured |
| LMArena Text: coding | 1371 | 1368 | MiniMax M2 |
| LMArena Text: software and IT | 1373 | 1367 | MiniMax M2 |
| LMArena WebDev: HTML | 1306 | Not measured | Only MiniMax M2 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 | o4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 18.6 | 16.7 | MiniMax M2 |
| 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 | o4 Mini | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 86.8% | 55.6% | MiniMax M2 |
| METR time horizons | Not measured | 63.9% | Only o4 Mini measured |
| Vending-Bench 2 | $161 | Not measured | Only MiniMax M2 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 53.2% | Only o4 Mini measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | MiniMax M2 | o4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 74.5% | Only o4 Mini measured |
| MMMU Pro (Vals AI) | Not measured | 79.7% | Only o4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 77.7% | 78.4% | o4 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 13.7% | 16.5% | o4 Mini |
| 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 | 1357 | 1351 | MiniMax M2 |
| LMArena Text: expert | 1338 | 1343 | o4 Mini |
| LMArena Text: hard prompts in English | 1376 | 1366 | MiniMax M2 |
| LMArena Vision: diagrams | Not measured | 1197 | Only o4 Mini measured |
| LMArena Vision: homework | Not measured | 1234 | Only o4 Mini measured |
| Kagi LLM Benchmark | 57.8% | 67.6% | o4 Mini |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | MiniMax M2 | o4 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 83.7% | Only o4 Mini measured |
| MATH 500 (Vals AI) | Not measured | 94.2% | Only o4 Mini measured |
| MGSM (Vals AI) | Not measured | 93.4% | Only o4 Mini measured |
| AA Math Index | 78.3 | 90.7 | o4 Mini |
| AIME 2025 (Artificial Analysis run) | 78.3% | 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 | 1351 | 1389 | o4 Mini |
| LMArena Text: mathematical work | 1368 | 1379 | o4 Mini |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | MiniMax M2 | o4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 80.6% | Only o4 Mini measured |
| LegalBench (Vals AI) | Not measured | 79.2% | Only o4 Mini measured |
| CorpFin (Vals AI) | Not measured | 59.0% | Only o4 Mini measured |
| TaxEval (Vals AI) | Not measured | 74.8% | Only o4 Mini measured |
| MortgageTax (Vals AI) | Not measured | 64.8% | Only o4 Mini measured |
| MedQA (Vals AI) | Not measured | 96.0% | Only o4 Mini measured |
| MedCode (Vals AI) | Not measured | 33.8% | Only o4 Mini measured |
| MMLU Pro (Artificial Analysis run) | 82.0% | 83.2% | o4 Mini |
| SimpleQA Verified | Not measured | 19.6% | Only o4 Mini measured |
| GeoBench | Not measured | 64.0% | Only o4 Mini measured |
| LMArena Text: science | 1348 | 1354 | o4 Mini |
| LMArena Text: medicine and healthcare | 1367 | 1361 | MiniMax M2 |
| LMArena Text: legal and government | 1349 | 1350 | o4 Mini |
| LMArena Text: business and finance | 1336 | 1325 | MiniMax M2 |
| FACTS Benchmark Suite | Not measured | 28.1% | Only o4 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | MiniMax M2 | o4 Mini | Leader |
|---|---|---|---|
| Design Arena: websites | 1143 | 985 | MiniMax M2 |
| Design Arena: UI components | 1136 | 983 | MiniMax M2 |
| Design Arena: game dev | 1118 | 1003 | MiniMax M2 |
| Design Arena: data viz | 1140 | 990 | MiniMax M2 |
| Design Arena: 3D | 1098 | 854 | MiniMax M2 |
| Design Arena: all code categories | 1135 | 976 | MiniMax M2 |
| Design Arena: SVG | 1100 | Not measured | Only MiniMax M2 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index710
| Benchmark | MiniMax M2 | o4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.1% | Only o4 Mini measured |
| MedScribe (Vals AI) | Not measured | 69.1% | Only o4 Mini measured |
| IFBench | 72.3% | 68.7% | MiniMax M2 |
| Long context reasoning (AA-LCR) | 64.3% | 61.0% | MiniMax M2 |
| 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 | 1340 | 1353 | o4 Mini |
| LMArena Text: instruction following | 1329 | 1320 | MiniMax M2 |
| LMArena Text: creative writing | 1286 | 1294 | o4 Mini |
| LMArena Vision | Not measured | 1194 | Only o4 Mini measured |
| LMArena Text: English | 1364 | 1367 | o4 Mini |
| LMArena Text: non-English | 1313 | 1337 | o4 Mini |
| LMArena Text: Chinese | 1366 | 1354 | MiniMax M2 |
| LMArena Text: German | 1357 | 1336 | MiniMax M2 |
| LMArena Text: Japanese | Not measured | 1308 | Only o4 Mini measured |
| LMArena Text: Korean | Not measured | 1312 | Only o4 Mini measured |
| LMArena Text: French | 1336 | 1364 | o4 Mini |
| LMArena Text: Spanish | 1326 | 1346 | o4 Mini |
| LMArena Text: Russian | 1330 | 1334 | o4 Mini |
| LMArena Text: Polish | 1312 | 1358 | o4 Mini |
| LMArena Text: multi-turn | 1361 | 1350 | MiniMax M2 |
| LMArena Text: longer queries | 1331 | 1315 | MiniMax M2 |
| LMArena Text: writing and language | 1295 | 1316 | o4 Mini |
| LMArena Text: entertainment and media | 1298 | 1308 | o4 Mini |
| 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 | 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 costs less
Repository review
50K input + 3K output tokens
MiniMax M2 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2 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 | OpenAI o4 Mini |
|---|---|---|
| Maker | MiniMax | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | October 23, 2025 | April 16, 2025 |
| Context window | 205K | 200K |
| Input $/Mtok | $0.255 | $1.10 |
| Output $/Mtok | $1.02 | $4.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.702 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2 better than o4 Mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M2 for output tokens 4.3x cheaper ($1.02 vs $4.40 per million) and a larger context window (205K against 200K tokens).
Which is cheaper, MiniMax M2 or o4 Mini?
MiniMax M2 costs $0.255 per million input tokens and $1.02 per million output tokens; o4 Mini costs $1.10 and $4.40. Cost per solved task is known for MiniMax M2 only.
Which has the bigger context window, MiniMax M2 or o4 Mini?
MiniMax M2, with 205K tokens against 200K.
How many benchmarks is the MiniMax M2 vs o4 Mini comparison based on?
45 benchmarks have a result for both models as of October 21, 2026. MiniMax M2'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.