MiniMax M2.5 vs o3 Pro
Updated October 21, 2026. 5 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
MiniMax M2.5 scores 59.4 and o3 Pro 84.9 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking.
Pick MiniMax M2.5 when output tokens cost 84.2x less, or when the context window is larger, 205K against 200K tokens; pick o3 Pro when the benchmark that matters is Epoch Capabilities Index, where it leads.
- Shared results
- 5
- MiniMax M2.5 only
- 62
- o3 Pro only
- 6
- Like-for-like categories
- 2 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
No call
59.4 against 84.9, from different benchmarks with none in common.
Directional only
Intelligence
AA Intelligence Index
MiniMax M2.5
MiniMax M2.5 leads, 22.8 against 21.9.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only MiniMax M2.5 has a GPQA Diamond result, 82.1%.
Directional only
Math
AIME
No call
Only MiniMax M2.5 has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.5 has a MMLU Pro result, 80.1%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2.5 has a Design Arena: websites result, 1222.
Directional only
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 $0.0007, o3 Pro $0.060 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.5 has the number, $0.62.
Directional only
At a glance
- Coding index
- MiniMax M2.5 59.4 from 2 benchmarks, o3 Pro 84.9 from 1 benchmark.
- Widest category
- Reasoning, 1.5 points apart on average over 3 shared benchmarks.
- Widest single gap
- ARC-AGI: MiniMax M2.5 63.7% against o3 Pro 59.3%, 4.3 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2.5 $0.95 against o3 Pro $80.00 per million output tokens, 84.2x apart.
- Context window
- MiniMax M2.5 takes 205K tokens, o3 Pro 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 Pro | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 1 | ||
| Reasoning | 2 | 0 | 1 tie | |
| All shared boards | 3 | 1 | 1 tie |
CodingDirectional onlyFour of these boards feed the Vibe Coding Index15 boards, none shared
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 84.9% | Only o3 Pro measured |
| SWE-bench Verified | 75.8% | Not measured | Only MiniMax M2.5 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% | Not measured | Only MiniMax M2.5 measured |
| 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 |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | Not measured | Only MiniMax M2.5 measured |
| Terminal-Bench | 42.7% | Not measured | Only MiniMax M2.5 measured |
| WeirdML | Not measured | 58.2% | Only o3 Pro measured |
| ALE-Bench | 618.2 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: coding | 1380 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: software and IT | 1383 | Not measured | Only MiniMax M2.5 measured |
| LMArena WebDev: React | 1374 | Not measured | Only MiniMax M2.5 measured |
| LMArena WebDev: HTML | 1414 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.8 | 21.9 | MiniMax M2.5 |
| Epoch Capabilities Index | 146.6 | 147.3 | o3 Pro |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 95.3% | Not measured | Only MiniMax M2.5 measured |
| Vending-Bench 2 | -$23 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 82.1% | Not measured | Only MiniMax M2.5 measured |
| GPQA Diamond (Artificial Analysis run) | 84.8% | 84.5% | MiniMax M2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 20.5% | Not measured | Only MiniMax M2.5 measured |
| ARC-AGI | 63.7% | 59.3% | MiniMax M2.5 |
| ARC-AGI-2 | 4.9% | 4.9% | Tie |
| LMArena Text: hard prompts | 1372 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: expert | 1378 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: hard prompts in English | 1384 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only MiniMax M2.5 measured |
| ProofBench | 4.0% | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: math | 1378 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: mathematical work | 1378 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| MMLU Pro | 80.1% | Not measured | Only MiniMax M2.5 measured |
| LegalBench (Vals AI) | 80.0% | Not measured | Only MiniMax M2.5 measured |
| CaseLaw (Vals AI) | 53.5% | Not measured | Only MiniMax M2.5 measured |
| CorpFin (Vals AI) | 59.6% | Not measured | Only MiniMax M2.5 measured |
| TaxEval (Vals AI) | 68.2% | Not measured | Only MiniMax M2.5 measured |
| MedQA (Vals AI) | 92.5% | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: science | 1369 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: medicine and healthcare | 1357 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: legal and government | 1366 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: business and finance | 1356 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1222 | Not measured | Only MiniMax M2.5 measured |
| Design Arena: UI components | 1172 | Not measured | Only MiniMax M2.5 measured |
| Design Arena: game dev | 1176 | Not measured | Only MiniMax M2.5 measured |
| Design Arena: data viz | 1171 | Not measured | Only MiniMax M2.5 measured |
| Design Arena: 3D | 1170 | Not measured | Only MiniMax M2.5 measured |
| Design Arena: all code categories | 1207 | Not measured | Only MiniMax M2.5 measured |
| Design Arena: SVG | 1147 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index25 boards, none shared
| Benchmark | MiniMax M2.5 | o3 Pro | Leader |
|---|---|---|---|
| IFBench | 71.6% | Not measured | Only MiniMax M2.5 measured |
| Long context reasoning (AA-LCR) | 73.3% | Not measured | Only MiniMax M2.5 measured |
| DTBench | Not measured | 86.9% | Only o3 Pro measured |
| LMCA | Not measured | 38.5% | Only o3 Pro measured |
| Fiction.LiveBench | Not measured | 97.2% | Only o3 Pro measured |
| Creative writing (Lech Mazur) | Not measured | 84.4% | Only o3 Pro measured |
| CL-bench | 11.4% | Not measured | Only MiniMax M2.5 measured |
| CL-bench Life | 6.3% | Not measured | Only MiniMax M2.5 measured |
| LMArena Text | 1359 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: instruction following | 1353 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: creative writing | 1331 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: English | 1380 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: non-English | 1338 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: Chinese | 1393 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: German | 1361 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: Japanese | 1171 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: Korean | 1233 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: French | 1363 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: Spanish | 1353 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: Russian | 1359 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: Polish | 1334 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: multi-turn | 1364 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: longer queries | 1366 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: writing and language | 1345 | Not measured | Only MiniMax M2.5 measured |
| LMArena Text: entertainment and media | 1329 | Not measured | Only MiniMax M2.5 measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M2.5 | o3 Pro | 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 Pro |
|---|---|---|
| Maker | MiniMax | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | February 12, 2026 | June 10, 2025 |
| Context window | 205K | 200K |
| Input $/Mtok | $0.27 | $20.00 |
| Output $/Mtok | $0.95 | $80.00 |
| Coding index | 59.4 | 84.9 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.62 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.5 better than o3 Pro for coding?
MiniMax M2.5 scores 59.4 and o3 Pro 84.9 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking. Pick MiniMax M2.5 when output tokens cost 84.2x less, or when the context window is larger, 205K against 200K tokens; pick o3 Pro when the benchmark that matters is Epoch Capabilities Index, where it leads.
Which is cheaper, MiniMax M2.5 or o3 Pro?
MiniMax M2.5 costs $0.27 per million input tokens and $0.95 per million output tokens; o3 Pro costs $20.00 and $80.00. Cost per solved task is known for MiniMax M2.5 only.
Which has the bigger context window, MiniMax M2.5 or o3 Pro?
MiniMax M2.5, with 205K tokens against 200K.
How many benchmarks is the MiniMax M2.5 vs o3 Pro comparison based on?
5 benchmarks have a result for both models as of October 21, 2026. MiniMax M2.5's coding index rests on 2 independent benchmarks and o3 Pro's on 1. Where only one model has a result, the page says so instead of naming a winner.