GPT-4.1 vs MiniMax M2
Updated October 21, 2026. 44 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
GPT-4.1 and MiniMax M2 are level for coding, 46.5 against 45.3 on the Vibe Coding Index, so price and context decide.
Pick MiniMax M2 when output tokens cost 7.8x less, or when what matters is SWE-bench Verified or LiveCodeBench (Artificial Analysis run), where it leads. Pick GPT-4.1 when a solved task costs $0.37 against $0.702, or when the context window is larger, 1.05M against 205K tokens.
- Shared results
- 44
- GPT-4.1 only
- 43
- MiniMax M2 only
- 5
- Like-for-like categories
- 8 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
Level: 46.5 against 45.3, inside 2 points.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
MiniMax M2
MiniMax M2 leads, 18.6 against 12.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4.1 has a GPQA Diamond result, 65.4%.
Directional only
Math
AIME
No call
Only GPT-4.1 has a AIME result, 39.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 has a MMLU Pro result, 80.5%.
Directional only
Web design
Design Arena: websites
MiniMax M2
MiniMax M2 leads, 1144 against 1039.
Same board, both measured
Long documents
Listed context window
GPT-4.1
GPT-4.1 takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2
GPT-4.1 $0.0060, MiniMax M2 $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-4.1
GPT-4.1 $0.37, MiniMax M2 $0.702.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-4.1 46.5 from 2 benchmarks, MiniMax M2 45.3 from 2 benchmarks.
- Widest category
- Agentic work, 39.8 points apart on average over 1 shared benchmark.
- Widest single gap
- AIME 2025 (Artificial Analysis run): GPT-4.1 34.7% against MiniMax M2 78.3%, 43.7 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 $8.00 against MiniMax M2 $1.02 per million output tokens, 7.8x apart.
- Context window
- GPT-4.1 takes 1.05M tokens, MiniMax M2 205K.
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-4.1 | Bars | MiniMax M2 | Ties |
|---|---|---|---|---|
| Coding | 2 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 3 | 2 | ||
| Math | 1 | 3 | ||
| Knowledge | 4 | 1 | ||
| Web design | 0 | 6 | ||
| General | 16 | 1 | ||
| All shared boards | 26 | 18 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index23
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| Aider polyglot | 52.4% | Not measured | Only GPT-4.1 measured |
| SWE-bench Verified | 39.6% | 61.0% | MiniMax M2 |
| SWE-bench Multimodal | 31.1% | Not measured | Only GPT-4.1 measured |
| LMArena WebDev | Not measured | 1297 | Only MiniMax M2 measured |
| LiveCodeBench (Vals AI) | 54.7% | Not measured | Only GPT-4.1 measured |
| LiveCodeBench (Artificial Analysis run) | 45.7% | 82.6% | MiniMax M2 |
| Terminal-Bench Hard (Artificial Analysis run) | 13.6% | 25.8% | MiniMax M2 |
| Terminal-Bench | Not measured | 30.0% | Only MiniMax M2 measured |
| WeirdML | 39.0% | Not measured | Only GPT-4.1 measured |
| ALE-Bench | 558.1 | Not measured | Only GPT-4.1 measured |
| LMArena Text: coding | 1390 | 1371 | GPT-4.1 |
| LMArena Text: software and IT | 1391 | 1373 | GPT-4.1 |
| LMArena WebDev: HTML | Not measured | 1306 | Only MiniMax M2 measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | 18.6 | MiniMax M2 |
| Epoch Capabilities Index | 136.7 | Not measured | Only GPT-4.1 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 47.1% | 86.8% | MiniMax M2 |
| Vending-Bench 2 | Not measured | $161 | Only MiniMax M2 measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| GPQA Diamond | 65.4% | Not measured | Only GPT-4.1 measured |
| MMMU Pro (Vals AI) | 72.4% | Not measured | Only GPT-4.1 measured |
| GPQA Diamond (Artificial Analysis run) | 66.6% | 77.7% | MiniMax M2 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 13.7% | MiniMax M2 |
| GPQA Diamond (Epoch AI run) | 66.9% | Not measured | Only GPT-4.1 measured |
| ARC-AGI | 5.5% | Not measured | Only GPT-4.1 measured |
| ARC-AGI-2 | 0.4% | Not measured | Only GPT-4.1 measured |
| SimpleBench | 27.0% | Not measured | Only GPT-4.1 measured |
| Chess puzzles | 3.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: hard prompts | 1384 | 1357 | GPT-4.1 |
| LMArena Text: expert | 1364 | 1338 | GPT-4.1 |
| LMArena Text: hard prompts in English | 1393 | 1376 | GPT-4.1 |
| LMArena Vision: diagrams | 1215 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: homework | 1248 | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| AIME | 39.6% | Not measured | Only GPT-4.1 measured |
| MATH 500 (Vals AI) | 87.2% | Not measured | Only GPT-4.1 measured |
| MGSM (Vals AI) | 87.7% | Not measured | Only GPT-4.1 measured |
| AA Math Index | 34.7 | 78.3 | MiniMax M2 |
| AIME 2025 (Artificial Analysis run) | 34.7% | 78.3% | MiniMax M2 |
| OTIS Mock AIME | 38.3% | Not measured | Only GPT-4.1 measured |
| FrontierMath, tiers 1 to 3 | 6.0% | Not measured | Only GPT-4.1 measured |
| MATH level 5 | 83.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: math | 1369 | 1351 | GPT-4.1 |
| LMArena Text: mathematical work | 1360 | 1368 | MiniMax M2 |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| MMLU Pro | 80.5% | Not measured | Only GPT-4.1 measured |
| LegalBench (Vals AI) | 83.1% | Not measured | Only GPT-4.1 measured |
| CaseLaw (Vals AI) | 69.9% | Not measured | Only GPT-4.1 measured |
| CorpFin (Vals AI) | 63.0% | Not measured | Only GPT-4.1 measured |
| TaxEval (Vals AI) | 75.1% | Not measured | Only GPT-4.1 measured |
| MortgageTax (Vals AI) | 65.9% | Not measured | Only GPT-4.1 measured |
| MedQA (Vals AI) | 91.2% | Not measured | Only GPT-4.1 measured |
| MMLU Pro (Artificial Analysis run) | 80.6% | 82.0% | MiniMax M2 |
| SimpleQA Verified | 31.1% | Not measured | Only GPT-4.1 measured |
| GeoBench | 72.0% | Not measured | Only GPT-4.1 measured |
| LMArena Text: science | 1382 | 1348 | GPT-4.1 |
| LMArena Text: medicine and healthcare | 1379 | 1367 | GPT-4.1 |
| LMArena Text: legal and government | 1399 | 1349 | GPT-4.1 |
| LMArena Text: business and finance | 1369 | 1336 | GPT-4.1 |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| Design Arena: websites | 1039 | 1144 | MiniMax M2 |
| Design Arena: UI components | 1000 | 1136 | MiniMax M2 |
| Design Arena: game dev | 1080 | 1119 | MiniMax M2 |
| Design Arena: data viz | 1104 | 1140 | MiniMax M2 |
| Design Arena: 3D | 850 | 1098 | MiniMax M2 |
| Design Arena: all code categories | 1026 | 1135 | MiniMax M2 |
| Design Arena: SVG | Not measured | 1098 | 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 index161
| Benchmark | GPT-4.1 | MiniMax M2 | Leader |
|---|---|---|---|
| IFBench | 43.0% | 72.3% | MiniMax M2 |
| Long context reasoning (AA-LCR) | 68.3% | 64.3% | GPT-4.1 |
| DTBench | 68.3% | Not measured | Only GPT-4.1 measured |
| LMCA | 25.6% | Not measured | Only GPT-4.1 measured |
| Fiction.LiveBench | 63.9% | Not measured | Only GPT-4.1 measured |
| LMArena Text | 1383 | 1340 | GPT-4.1 |
| LMArena Text: instruction following | 1367 | 1329 | GPT-4.1 |
| LMArena Text: creative writing | 1363 | 1286 | GPT-4.1 |
| LMArena Vision | 1210 | Not measured | Only GPT-4.1 measured |
| LMArena Text: English | 1392 | 1364 | GPT-4.1 |
| LMArena Text: non-English | 1370 | 1313 | GPT-4.1 |
| LMArena Text: Chinese | 1382 | 1366 | GPT-4.1 |
| LMArena Text: German | 1381 | 1357 | GPT-4.1 |
| LMArena Text: Japanese | 1319 | Not measured | Only GPT-4.1 measured |
| LMArena Text: Korean | 1338 | Not measured | Only GPT-4.1 measured |
| LMArena Text: French | 1382 | 1336 | GPT-4.1 |
| LMArena Text: Spanish | 1376 | 1326 | GPT-4.1 |
| LMArena Text: Russian | 1377 | 1330 | GPT-4.1 |
| LMArena Text: Polish | 1389 | 1312 | GPT-4.1 |
| LMArena Text: multi-turn | 1397 | 1361 | GPT-4.1 |
| LMArena Text: longer queries | 1385 | 1331 | GPT-4.1 |
| LMArena Text: writing and language | 1371 | 1295 | GPT-4.1 |
| LMArena Text: entertainment and media | 1365 | 1298 | GPT-4.1 |
| LMArena Vision: English | 1209 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: Chinese | 1226 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: reading text | 1218 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: humor | 1196 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: captioning | 1207 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: recognizing things | 1208 | Not measured | Only GPT-4.1 measured |
| LMArena Vision: creative writing | 1210 | Not measured | Only GPT-4.1 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 | MiniMax M2 | 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 | OpenAI GPT-4.1 | MiniMax M2 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | April 14, 2025 | October 23, 2025 |
| Context window | 1.05M | 205K |
| Input $/Mtok | $2.00 | $0.255 |
| Output $/Mtok | $8.00 | $1.02 |
| Coding index | 46.5 | 45.3 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.37 | $0.702 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 better than MiniMax M2 for coding?
GPT-4.1 and MiniMax M2 are level for coding, 46.5 against 45.3 on the Vibe Coding Index, so price and context decide. Pick MiniMax M2 when output tokens cost 7.8x less, or when what matters is SWE-bench Verified or LiveCodeBench (Artificial Analysis run), where it leads. Pick GPT-4.1 when a solved task costs $0.37 against $0.702, or when the context window is larger, 1.05M against 205K tokens.
Which is cheaper, GPT-4.1 or MiniMax M2?
GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Per solved SWE-bench Verified task, GPT-4.1 costs $0.37 and MiniMax M2 $0.702.
Which has the bigger context window, GPT-4.1 or MiniMax M2?
GPT-4.1, with 1.05M tokens against 205K.
How many benchmarks is the GPT-4.1 vs MiniMax M2 comparison based on?
44 benchmarks have a result for both models as of October 21, 2026. GPT-4.1's coding index rests on 2 independent benchmarks and MiniMax M2's on 2. Where only one model has a result, the page says so instead of naming a winner.