MiniMax M2.5 vs o3
MiniMax M2.5 leads o3 on the Artificial Analysis Intelligence Index, 22.8 to 20.2, and MiniMax M2.5 costs 6.7x less per output token ($1.20 vs $8.00 per million). Updated October 21, 2026; 55 benchmarks have a result for both.
MiniMax M2.5 or o3: which to pick
Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; o3 has none, so the two cannot be ranked on coding.
Pick o3 for a lower cost per solved task ($0.571 against $0.62) and work measured by LiveCodeBench (Vals AI) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 55
- MiniMax M2.5 only
- 13
- o3 only
- 47
- 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
Only MiniMax M2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M2.5
MiniMax M2.5 leads, 22.8 against 20.2.
Same board, both measured
Reasoning
GPQA Diamond
o3
o3 leads, 84.1% against 82.1%.
Same board, both measured
Math
AIME
MiniMax M2.5
MiniMax M2.5 leads, 88.8% against 85.3%.
Same board, both measured
Knowledge
MMLU Pro
o3
o3 leads, 85.6% against 80.1%.
Same board, both measured
Web design
Design Arena: websites
MiniMax M2.5
MiniMax M2.5 leads, 1222 against 1036.
Same board, both measured
Long documents
Listed context window
MiniMax M2.5
MiniMax M2.5 takes 205K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.5
MiniMax M2.5 $0.0009, o3 $0.0060 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
o3
MiniMax M2.5 $0.62, o3 $0.571.
Published attempt cost and pass rate
At a glance
- Coding index
- MiniMax M2.5 37.2 from 3 benchmarks, o3 not benchmarked.
- Widest category
- Web design, 17.5 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena Text: Japanese: MiniMax M2.5 1171 against o3 1403, 38.7 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2.5 $1.20 against o3 $8.00 per million output tokens, 6.7x apart.
- Context window
- MiniMax M2.5 takes 205K tokens, o3 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 M2.5 | Bars | o3 | Ties |
|---|---|---|---|---|
| Coding | 1 | 5 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 6 | ||
| Math | 1 | 2 | ||
| Knowledge | 0 | 9 | ||
| Web design | 4 | 1 | ||
| General | 1 | 19 | ||
| All shared boards | 12 | 43 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index15
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 81.3% | Only o3 measured |
| SWE-bench Verified | 75.8% | 58.4% | MiniMax M2.5 |
| SWE-bench Multimodal | Not measured | 36.0% | Only o3 measured |
| SWE-bench Multilingual | 68.3% | Not measured | Only MiniMax M2.5 measured |
| LMArena WebDev | 1386 | Not measured | Only MiniMax M2.5 measured |
| LiveCodeBench (Vals AI) | 79.2% | 83.9% | o3 |
| SWE-bench Verified (Vals AI) | 74.2% | Not measured | Only MiniMax M2.5 measured |
| Vibe Code Bench (Vals AI) | 14.8% | Not measured | Only MiniMax M2.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 80.8% | Only o3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | 37.1% | o3 |
| Terminal-Bench | 42.7% | Not measured | Only MiniMax M2.5 measured |
| GSO-Bench | Not measured | 8.8% | Only o3 measured |
| WeirdML | Not measured | 52.4% | Only o3 measured |
| ALE-Bench | 618.2 | 933.5 | o3 |
| LMArena Text: coding | 1380 | 1407 | o3 |
| LMArena Text: software and IT | 1383 | 1415 | o3 |
| LMArena WebDev: React | 1374 | Not measured | Only MiniMax M2.5 measured |
| LMArena WebDev: HTML | 1414 | Not measured | Only MiniMax M2.5 measured |
| SciCode | Not measured | 9.2% | Only o3 measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.8 | 20.2 | MiniMax M2.5 |
| Epoch Capabilities Index | 146.6 | 146.7 | o3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 95.3% | 80.7% | MiniMax M2.5 |
| METR time horizons | Not measured | 65.4% | Only o3 measured |
| GDPval | Not measured | 30.8% | Only o3 measured |
| DeepResearch Bench | Not measured | 45.2% | Only o3 measured |
| OSWorld | Not measured | 23.0% | Only o3 measured |
| Vending-Bench 2 | -$23 | Not measured | Only MiniMax M2.5 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 63.0% | Only o3 measured |
| BrowseComp-Plus | Not measured | 65.9% | Only o3 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index36
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| GPQA Diamond | 82.1% | 84.1% | o3 |
| MMMU Pro (Vals AI) | Not measured | 80.4% | Only o3 measured |
| GPQA Diamond (Artificial Analysis run) | 84.8% | 82.7% | MiniMax M2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 20.5% | 20.1% | MiniMax M2.5 |
| GPQA Diamond (Epoch AI run) | Not measured | 81.8% | Only o3 measured |
| ARC-AGI | 63.7% | 60.8% | MiniMax M2.5 |
| ARC-AGI-2 | 4.9% | 6.5% | o3 |
| SimpleBench | Not measured | 53.1% | Only o3 measured |
| Chess puzzles | Not measured | 37.0% | Only o3 measured |
| Mystery game puzzles | Not measured | 29.0% | Only o3 measured |
| VPCT | Not measured | 52.0% | Only o3 measured |
| LMArena Text: hard prompts | 1372 | 1402 | o3 |
| LMArena Text: expert | 1378 | 1402 | o3 |
| LMArena Text: hard prompts in English | 1384 | 1411 | o3 |
| LMArena Vision: diagrams | Not measured | 1220 | Only o3 measured |
| LMArena Vision: homework | Not measured | 1234 | Only o3 measured |
| Kagi LLM Benchmark | 55.2% | 67.6% | o3 |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| AIME | 88.8% | 85.3% | MiniMax M2.5 |
| MATH 500 (Vals AI) | Not measured | 94.6% | Only o3 measured |
| MGSM (Vals AI) | Not measured | 91.8% | Only o3 measured |
| AA Math Index | Not measured | 88.3 | Only o3 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 88.3% | Only o3 measured |
| OTIS Mock AIME | Not measured | 84.4% | Only o3 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 33.3% | Only o3 measured |
| ProofBench | 4.0% | Not measured | Only MiniMax M2.5 measured |
| MATH level 5 | Not measured | 97.8% | Only o3 measured |
| LMArena Text: math | 1378 | 1426 | o3 |
| LMArena Text: mathematical work | 1378 | 1423 | o3 |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index09
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| MMLU Pro | 80.1% | 85.6% | o3 |
| LegalBench (Vals AI) | 80.0% | 83.8% | o3 |
| CaseLaw (Vals AI) | 53.5% | Not measured | Only MiniMax M2.5 measured |
| CorpFin (Vals AI) | 59.6% | 59.7% | o3 |
| TaxEval (Vals AI) | 68.2% | 74.6% | o3 |
| MortgageTax (Vals AI) | Not measured | 65.7% | Only o3 measured |
| MedQA (Vals AI) | 92.5% | 96.1% | o3 |
| MedCode (Vals AI) | Not measured | 47.3% | Only o3 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 85.3% | Only o3 measured |
| SimpleQA Verified | Not measured | 49.4% | Only o3 measured |
| GeoBench | Not measured | 74.0% | Only o3 measured |
| LMArena Text: science | 1369 | 1429 | o3 |
| LMArena Text: medicine and healthcare | 1357 | 1448 | o3 |
| LMArena Text: legal and government | 1366 | 1428 | o3 |
| LMArena Text: business and finance | 1356 | 1393 | o3 |
| FACTS Benchmark Suite | Not measured | 44.4% | Only o3 measured |
| Neither model has a result on the other 2 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1222 | 1036 | MiniMax M2.5 |
| Design Arena: UI components | 1173 | 1017 | MiniMax M2.5 |
| Design Arena: game dev | 1176 | 1034 | MiniMax M2.5 |
| Design Arena: data viz | 1171 | 1200 | o3 |
| Design Arena: 3D | 1170 | Not measured | Only MiniMax M2.5 measured |
| Design Arena: all code categories | 1207 | 1020 | MiniMax M2.5 |
| Design Arena: SVG | 1149 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index119
| Benchmark | MiniMax M2.5 | o3 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.8% | Only o3 measured |
| MedScribe (Vals AI) | Not measured | 76.7% | Only o3 measured |
| IFBench | 71.6% | 71.4% | MiniMax M2.5 |
| Long context reasoning (AA-LCR) | 73.3% | 74.7% | o3 |
| DTBench | Not measured | 84.8% | Only o3 measured |
| LMCA | Not measured | 39.7% | Only o3 measured |
| Fiction.LiveBench | Not measured | 88.9% | Only o3 measured |
| Creative writing (Lech Mazur) | Not measured | 83.9% | Only o3 measured |
| CL-bench | 11.4% | 17.8% | o3 |
| CL-bench Life | 6.3% | Not measured | Only MiniMax M2.5 measured |
| LMArena Text | 1359 | 1410 | o3 |
| LMArena Text: instruction following | 1353 | 1368 | o3 |
| LMArena Text: creative writing | 1331 | 1359 | o3 |
| LMArena Vision | Not measured | 1214 | Only o3 measured |
| LMArena Text: English | 1380 | 1417 | o3 |
| LMArena Text: non-English | 1338 | 1401 | o3 |
| LMArena Text: Chinese | 1393 | 1437 | o3 |
| LMArena Text: German | 1361 | 1420 | o3 |
| LMArena Text: Japanese | 1171 | 1403 | o3 |
| LMArena Text: Korean | 1233 | 1370 | o3 |
| LMArena Text: French | 1363 | 1430 | o3 |
| LMArena Text: Spanish | 1353 | 1395 | o3 |
| LMArena Text: Russian | 1359 | 1406 | o3 |
| LMArena Text: Polish | 1334 | 1438 | o3 |
| LMArena Text: multi-turn | 1364 | 1405 | o3 |
| LMArena Text: longer queries | 1366 | 1372 | o3 |
| LMArena Text: writing and language | 1345 | 1372 | o3 |
| LMArena Text: entertainment and media | 1329 | 1373 | o3 |
| LMArena Vision: English | Not measured | 1221 | Only o3 measured |
| LMArena Vision: Chinese | Not measured | 1237 | Only o3 measured |
| LMArena Vision: reading text | Not measured | 1218 | Only o3 measured |
| LMArena Vision: humor | Not measured | 1222 | Only o3 measured |
| LMArena Vision: captioning | Not measured | 1210 | Only o3 measured |
| LMArena Vision: recognizing things | Not measured | 1234 | Only o3 measured |
| LMArena Vision: creative writing | Not measured | 1201 | Only o3 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M2.5 | o3 | 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 M2.5 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.5 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.5 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 M2.5 | OpenAI o3 |
|---|---|---|
| Maker | MiniMax | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | February 12, 2026 | April 16, 2025 |
| Context window | 205K | 200K |
| Input $/Mtok | $0.30 | $2.00 |
| Output $/Mtok | $1.20 | $8.00 |
| Coding index | 37.2 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $0.62 | $0.571 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.5 better than o3 for coding?
Only MiniMax M2.5 has a coding score, 37.2 on the Vibe Coding Index; o3 has none, so the two cannot be ranked on coding. Pick o3 for a lower cost per solved task ($0.571 against $0.62) and work measured by LiveCodeBench (Vals AI) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, MiniMax M2.5 or o3?
MiniMax M2.5 costs $0.30 per million input tokens and $1.20 per million output tokens; o3 costs $2.00 and $8.00. Per solved SWE-bench Verified task, MiniMax M2.5 costs $0.62 and o3 $0.571.
Which has the bigger context window, MiniMax M2.5 or o3?
MiniMax M2.5, with 205K tokens against 200K.
How many benchmarks is the MiniMax M2.5 vs o3 comparison based on?
55 benchmarks have a result for both models as of October 21, 2026. MiniMax M2.5's coding index rests on 3 independent benchmarks and o3's on 0. Where only one model has a result, the page says so instead of naming a winner.