GPT-4o-mini vs MiniMax M3
MiniMax M3 leads GPT-4o-mini on the Artificial Analysis Intelligence Index, 29.2 to 6.7, and GPT-4o-mini costs 2.0x less per output token ($0.60 vs $1.20 per million). Updated October 22, 2026; 15 benchmarks have a result for both.
vs boards won of 15 shared
GPT-4o-mini or MiniMax M3: which to pick
Only MiniMax M3 has a coding score, 39.2 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding.
Pick GPT-4o-mini for output tokens 2.0x cheaper ($0.60 vs $1.20 per million).
Model AGPT-4o-miniOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BMiniMax M3MiniMax39.2/1006 independent benchmarks$0.56 per solved task
- Shared results
- 15
- GPT-4o-mini only
- 14
- MiniMax M3 only
- 101
- Like-for-like categories
- 5 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 M3 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M3
MiniMax M3 leads, 29.2 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiniMax M3 has a AA Agentic Index result, 29.5.
Directional only
Reasoning
GPQA Diamond
MiniMax M3
MiniMax M3 leads, 92.7% against 44.2%.
Same board, both measured
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
MiniMax M3
MiniMax M3 leads, 84.2% against 62.7%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiniMax M3 has a Design Arena: websites result, 1257.
Directional only
Long documents
Listed context window
MiniMax M3
MiniMax M3 takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o-mini
GPT-4o-mini $0.0004, MiniMax M3 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M3 has the number, $0.56.
Directional only
At a glance
- Coding index
- GPT-4o-mini not benchmarked, MiniMax M3 39.2 from 6 benchmarks.
- Widest category
- Coding, 51.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- LiveCodeBench (Vals AI): GPT-4o-mini 26.4% against MiniMax M3 82.2%, 55.7 points apart on a 0 to 100 scale.
- Output price
- GPT-4o-mini $0.60 against MiniMax M3 $1.20 per million output tokens, 2.0x apart.
- Context window
- GPT-4o-mini takes 128K tokens, MiniMax M3 1.05M.
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-4o-mini | Bars | MiniMax M3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 4 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 3 | ||
| All shared boards | 0 | 15 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 70.9% | Only MiniMax M3 measured |
| LMArena WebDev | Not measured | 1482 | Only MiniMax M3 measured |
| AA Coding Index | 11.4 | 58.6 | MiniMax M3 |
| LiveCodeBench (Vals AI) | 26.4% | 82.2% | MiniMax M3 |
| SWE-bench Verified (Vals AI) | Not measured | 75.0% | Only MiniMax M3 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 1.0% | Only MiniMax M3 measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.6% | Only MiniMax M3 measured |
| Code migration (Vals AI) | Not measured | 19.9% | Only MiniMax M3 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 53.6% | Only MiniMax M3 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 33.3% | Only MiniMax M3 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 9.2% | Only MiniMax M3 measured |
| SkillsBench (Vals AI) | Not measured | 51.5% | Only MiniMax M3 measured |
| CyberBench (Vals AI) | Not measured | 65.0% | Only MiniMax M3 measured |
| LiveCodeBench (Artificial Analysis run) | 23.4% | Not measured | Only GPT-4o-mini measured |
| SciCode | Not measured | 47.1% | Only MiniMax M3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 42.4% | Only MiniMax M3 measured |
| FrontierCode | Not measured | 14.7% | Only MiniMax M3 measured |
| ALE-Bench | Not measured | 640.0 | Only MiniMax M3 measured |
| LMArena Text: coding | Not measured | 1470 | Only MiniMax M3 measured |
| LMArena Text: software and IT | Not measured | 1466 | Only MiniMax M3 measured |
| LMArena WebDev: React | Not measured | 1478 | Only MiniMax M3 measured |
| LMArena WebDev: HTML | Not measured | 1455 | Only MiniMax M3 measured |
| LMArena WebDev: from an image | Not measured | 1470 | Only MiniMax M3 measured |
| SciCode | 1.5% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 29.2 | MiniMax M3 |
| Epoch Capabilities Index | 126.5 | 146.9 | MiniMax M3 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 29.5 | Only MiniMax M3 measured |
| Design Arena: agents building web apps | Not measured | 1200 | Only MiniMax M3 measured |
| Design Arena: agents building full-stack apps | Not measured | 1197 | Only MiniMax M3 measured |
| Design Arena: agents building mobile apps | Not measured | 1169 | Only MiniMax M3 measured |
| Design Arena: agents building Android apps | Not measured | 1159 | Only MiniMax M3 measured |
| Design Arena: agents building games | Not measured | 1158 | Only MiniMax M3 measured |
| Design Arena: HTML slides | Not measured | 1130 | Only MiniMax M3 measured |
| Design Arena: PowerPoint slides | Not measured | 1181 | Only MiniMax M3 measured |
| Design Arena: spreadsheets | Not measured | 1028 | Only MiniMax M3 measured |
| LiveBench research | Not measured | 68.0% | Only MiniMax M3 measured |
| LiveBench browser | Not measured | 8.0% | Only MiniMax M3 measured |
| LiveBench long agentic | Not measured | 12.4% | Only MiniMax M3 measured |
| Finance Agent (Vals AI) | Not measured | 48.3% | Only MiniMax M3 measured |
| Tax Agent Bench (Vals AI) | Not measured | 20.6% | Only MiniMax M3 measured |
| Legal Research Bench (Vals AI) | Not measured | 29.8% | Only MiniMax M3 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 47.8% | Only MiniMax M3 measured |
| τ²-Bench Telecom | Not measured | 88.9% | Only MiniMax M3 measured |
| APEX-Agents | Not measured | 37.7% | Only MiniMax M3 measured |
| OSWorld 2.0 | Not measured | 4.6% | Only MiniMax M3 measured |
| Vending-Bench 2 | Not measured | $2,158 | Only MiniMax M3 measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| GPQA Diamond | 44.2% | 92.7% | MiniMax M3 |
| LiveBench reasoning | Not measured | 74.5% | Only MiniMax M3 measured |
| MMMU Pro (Vals AI) | 56.6% | 81.2% | MiniMax M3 |
| GPQA Diamond (Artificial Analysis run) | 42.6% | 92.9% | MiniMax M3 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 39.0% | MiniMax M3 |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only MiniMax M3 measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o-mini measured |
| SimpleBench | Not measured | 45.8% | Only MiniMax M3 measured |
| Chess puzzles | Not measured | 13.0% | Only MiniMax M3 measured |
| Mystery game puzzles | Not measured | 8.0% | Only MiniMax M3 measured |
| LMArena Text: hard prompts | Not measured | 1447 | Only MiniMax M3 measured |
| LMArena Text: expert | Not measured | 1461 | Only MiniMax M3 measured |
| LMArena Text: hard prompts in English | Not measured | 1455 | Only MiniMax M3 measured |
| LMArena Vision: diagrams | Not measured | 1266 | Only MiniMax M3 measured |
| LMArena Vision: homework | Not measured | 1268 | Only MiniMax M3 measured |
| Kagi LLM Benchmark | 28.8% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| AIME | 11.5% | Not measured | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | 72.6% | Not measured | Only GPT-4o-mini measured |
| MGSM (Vals AI) | 86.2% | Not measured | Only GPT-4o-mini measured |
| AA Math Index | 14.7 | Not measured | Only GPT-4o-mini measured |
| AIME 2025 (Artificial Analysis run) | 14.7% | Not measured | Only GPT-4o-mini measured |
| OTIS Mock AIME | Not measured | 71.1% | Only MiniMax M3 measured |
| ProofBench | Not measured | 18.0% | Only MiniMax M3 measured |
| GSM8K | 91.3% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: math | Not measured | 1429 | Only MiniMax M3 measured |
| LMArena Text: mathematical work | Not measured | 1448 | Only MiniMax M3 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| MMLU Pro | 62.7% | 84.2% | MiniMax M3 |
| LegalBench (Vals AI) | Not measured | 85.4% | Only MiniMax M3 measured |
| CorpFin (Vals AI) | 45.5% | 68.1% | MiniMax M3 |
| TaxEval (Vals AI) | 60.5% | 72.7% | MiniMax M3 |
| MortgageTax (Vals AI) | 54.5% | 68.4% | MiniMax M3 |
| MedQA (Vals AI) | 72.4% | Not measured | Only GPT-4o-mini measured |
| MedCode (Vals AI) | Not measured | 46.3% | Only MiniMax M3 measured |
| MMLU Pro (Artificial Analysis run) | 64.8% | Not measured | Only GPT-4o-mini measured |
| MMLU | 81.8% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: science | Not measured | 1452 | Only MiniMax M3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1441 | Only MiniMax M3 measured |
| LMArena Text: legal and government | Not measured | 1437 | Only MiniMax M3 measured |
| LMArena Text: business and finance | Not measured | 1434 | Only MiniMax M3 measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1257 | Only MiniMax M3 measured |
| Design Arena: UI components | Not measured | 1242 | Only MiniMax M3 measured |
| Design Arena: game dev | Not measured | 1210 | Only MiniMax M3 measured |
| Design Arena: data viz | Not measured | 1236 | Only MiniMax M3 measured |
| Design Arena: 3D | Not measured | 1208 | Only MiniMax M3 measured |
| Design Arena: all code categories | Not measured | 1247 | Only MiniMax M3 measured |
| Design Arena: SVG | Not measured | 1161 | Only MiniMax M3 measured |
| Design Arena: ASCII art | Not measured | 1161 | Only MiniMax M3 measured |
| LiveBench design | Not measured | 66.2% | Only MiniMax M3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-4o-mini | MiniMax M3 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.2% | Only MiniMax M3 measured |
| Public Benefits Bench (Vals AI) | Not measured | 64.1% | Only MiniMax M3 measured |
| SAGE (Vals AI) | Not measured | 50.6% | Only MiniMax M3 measured |
| MedScribe (Vals AI) | Not measured | 87.3% | Only MiniMax M3 measured |
| Vals Multimodal Index | Not measured | 60.0% | Only MiniMax M3 measured |
| IFBench | 31.0% | 82.9% | MiniMax M3 |
| Long context reasoning (AA-LCR) | Not measured | 83.0% | Only MiniMax M3 measured |
| DTBench | 54.4% | 78.9% | MiniMax M3 |
| LMCA | 10.4% | 33.7% | MiniMax M3 |
| Surface Evolver Bench | Not measured | 55.0% | Only MiniMax M3 measured |
| PIQA | 88.7% | Not measured | Only GPT-4o-mini measured |
| LMArena Text | Not measured | 1433 | Only MiniMax M3 measured |
| LMArena Text: instruction following | Not measured | 1433 | Only MiniMax M3 measured |
| LMArena Text: creative writing | Not measured | 1404 | Only MiniMax M3 measured |
| LMArena Vision | Not measured | 1251 | Only MiniMax M3 measured |
| LMArena Text: English | Not measured | 1443 | Only MiniMax M3 measured |
| LMArena Text: non-English | Not measured | 1420 | Only MiniMax M3 measured |
| LMArena Text: Chinese | Not measured | 1466 | Only MiniMax M3 measured |
| LMArena Text: German | Not measured | 1428 | Only MiniMax M3 measured |
| LMArena Text: Japanese | Not measured | 1380 | Only MiniMax M3 measured |
| LMArena Text: Korean | Not measured | 1373 | Only MiniMax M3 measured |
| LMArena Text: French | Not measured | 1444 | Only MiniMax M3 measured |
| LMArena Text: Spanish | Not measured | 1433 | Only MiniMax M3 measured |
| LMArena Text: Russian | Not measured | 1426 | Only MiniMax M3 measured |
| LMArena Text: Polish | Not measured | 1423 | Only MiniMax M3 measured |
| LMArena Text: multi-turn | Not measured | 1443 | Only MiniMax M3 measured |
| LMArena Text: longer queries | Not measured | 1446 | Only MiniMax M3 measured |
| LMArena Text: writing and language | Not measured | 1419 | Only MiniMax M3 measured |
| LMArena Text: entertainment and media | Not measured | 1403 | Only MiniMax M3 measured |
| LMArena Vision: English | Not measured | 1263 | Only MiniMax M3 measured |
| LMArena Vision: Chinese | Not measured | 1311 | Only MiniMax M3 measured |
| LMArena Vision: reading text | Not measured | 1259 | Only MiniMax M3 measured |
| LMArena Vision: humor | Not measured | 1235 | Only MiniMax M3 measured |
| LMArena Vision: recognizing things | Not measured | 1197 | Only MiniMax M3 measured |
| LMArena Vision: creative writing | Not measured | 1234 | Only MiniMax M3 measured |
| LMArena Document | Not measured | 1435 | Only MiniMax M3 measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini | MiniMax M3 | 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
GPT-4o-mini$0.0004Fits in one request
MiniMax M3$0.0009Fits in one request
GPT-4o-mini costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini$0.0093Fits in one request
MiniMax M3$0.019Fits in one request
GPT-4o-mini costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini$0.036Exceeds the context window
MiniMax M3$0.072Fits in one request
GPT-4o-mini 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-4o-mini | MiniMax M3 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | July 18, 2024 | May 31, 2026 |
| Context window | 128K | 1.05M |
| Input $/Mtok | $0.15 | $0.30 |
| Output $/Mtok | $0.60 | $1.20 |
| Coding index | Not benchmarked | 39.2 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | Not computable | $0.56 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-mini better than MiniMax M3 for coding?
Only MiniMax M3 has a coding score, 39.2 on the Vibe Coding Index; GPT-4o-mini has none, so the two cannot be ranked on coding. Pick GPT-4o-mini for output tokens 2.0x cheaper ($0.60 vs $1.20 per million).
Which is cheaper, GPT-4o-mini or MiniMax M3?
GPT-4o-mini costs $0.15 per million input tokens and $0.60 per million output tokens; MiniMax M3 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M3 only.
Which has the bigger context window, GPT-4o-mini or MiniMax M3?
MiniMax M3, with 1.05M tokens against 128K.
How many benchmarks is the GPT-4o-mini vs MiniMax M3 comparison based on?
15 benchmarks have a result for both models as of October 22, 2026. GPT-4o-mini's coding index rests on 0 independent benchmarks and MiniMax M3's on 6. Where only one model has a result, the page says so instead of naming a winner.