GPT-5.4 Nano vs MiniMax M3
GPT-5.4 Nano leads MiniMax M3 on coding, 44.8 to 39.2 on the Vibe Coding Index, at about the same output price ($1.25 vs $1.20 per million). Updated October 22, 2026; 76 benchmarks have a result for both.
GPT-5.4 Nano or MiniMax M3: which to pick
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 39.2 for MiniMax M3, though on 2 benchmarks against 6.
Pick MiniMax M3 for output tokens 1.0x cheaper ($1.20 vs $1.25 per million) and a larger context window (1.05M against 400K tokens).
- Shared results
- 76
- GPT-5.4 Nano only
- 9
- MiniMax M3 only
- 41
- Like-for-like categories
- 7 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
GPT-5.4 Nano
GPT-5.4 Nano scores 44.8 against 39.2.
2 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M3
MiniMax M3 leads, 29.2 against 20.7.
Same board, both measured
Agentic work
AA Agentic Index
MiniMax M3
MiniMax M3 leads, 29.5 against 16.0.
Same board, both measured
Reasoning
GPQA Diamond
MiniMax M3
MiniMax M3 leads, 92.7% against 77.5%.
Same board, both measured
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
MiniMax M3
MiniMax M3 leads, 84.2% against 77.2%.
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 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Nano
GPT-5.4 Nano $0.0008, MiniMax M3 $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.4 Nano
GPT-5.4 Nano $0.14, MiniMax M3 $0.56.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, MiniMax M3 39.2 from 6 benchmarks.
- Widest category
- Agentic work, 13.1 points apart on average over 6 shared benchmarks.
- Widest single gap
- Chess puzzles: GPT-5.4 Nano 45.0% against MiniMax M3 13.0%, 32.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against MiniMax M3 $1.20 per million output tokens, 1.0x apart.
- Context window
- GPT-5.4 Nano takes 400K 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-5.4 Nano | Bars | MiniMax M3 | Ties |
|---|---|---|---|---|
| Coding | 3 | 7 | 1 tie | |
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 6 | ||
| Reasoning | 2 | 10 | ||
| Math | 1 | 3 | ||
| Knowledge | 0 | 10 | ||
| General | 2 | 29 | ||
| All shared boards | 8 | 67 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index37
| Benchmark | GPT-5.4 Nano | 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 | 56.1 | 58.6 | MiniMax M3 |
| LiveCodeBench (Vals AI) | 84.0% | 82.2% | GPT-5.4 Nano |
| SWE-bench Verified (Vals AI) | 69.8% | 75.0% | MiniMax M3 |
| Terminal-Bench 4 (Vals AI) | Not measured | 1.0% | Only MiniMax M3 measured |
| Vibe Code Bench (Vals AI) | 26.1% | 47.6% | MiniMax M3 |
| Code migration (Vals AI) | 14.5% | 19.9% | MiniMax M3 |
| Terminal-Bench 2.1 (Vals AI) | 41.6% | 53.6% | MiniMax M3 |
| 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 |
| SciCode | 47.2% | 47.1% | GPT-5.4 Nano |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | 42.4% | Tie |
| FrontierCode | Not measured | 14.7% | Only MiniMax M3 measured |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | 640.0 | GPT-5.4 Nano |
| LMArena Text: coding | 1404 | 1470 | MiniMax M3 |
| LMArena Text: software and IT | 1402 | 1466 | MiniMax M3 |
| 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 |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.4 Nano | MiniMax M3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | 29.2 | MiniMax M3 |
| Epoch Capabilities Index | 146.0 | 146.9 | MiniMax M3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-5.4 Nano | MiniMax M3 | Leader |
|---|---|---|---|
| AA Agentic Index | 16.0 | 29.5 | MiniMax M3 |
| 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 | 1158 | Only MiniMax M3 measured |
| Design Arena: agents building games | Not measured | 1159 | Only MiniMax M3 measured |
| Design Arena: HTML slides | Not measured | 1120 | Only MiniMax M3 measured |
| Design Arena: PowerPoint slides | Not measured | 1178 | Only MiniMax M3 measured |
| Design Arena: spreadsheets | Not measured | 1042 | 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) | 38.2% | 48.3% | MiniMax M3 |
| Tax Agent Bench (Vals AI) | 5.0% | 20.6% | MiniMax M3 |
| Legal Research Bench (Vals AI) | 6.3% | 29.8% | MiniMax M3 |
| Excel Modeling Benchmark (Vals AI) | 44.8% | 47.8% | MiniMax M3 |
| τ²-Bench Telecom | 76.0% | 88.9% | MiniMax M3 |
| 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 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index210
| Benchmark | GPT-5.4 Nano | MiniMax M3 | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | 92.7% | MiniMax M3 |
| LiveBench reasoning | Not measured | 74.5% | Only MiniMax M3 measured |
| MMMU Pro (Vals AI) | 73.6% | 81.2% | MiniMax M3 |
| GPQA Diamond (Artificial Analysis run) | 81.7% | 92.9% | MiniMax M3 |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | 39.0% | MiniMax M3 |
| GPQA Diamond (Epoch AI run) | 78.5% | 90.9% | MiniMax M3 |
| ARC-AGI | 51.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI-2 | 5.7% | Not measured | Only GPT-5.4 Nano measured |
| SimpleBench | Not measured | 45.8% | Only MiniMax M3 measured |
| Chess puzzles | 45.0% | 13.0% | GPT-5.4 Nano |
| Mystery game puzzles | 9.0% | 8.0% | GPT-5.4 Nano |
| LMArena Text: hard prompts | 1381 | 1447 | MiniMax M3 |
| LMArena Text: expert | 1396 | 1461 | MiniMax M3 |
| LMArena Text: hard prompts in English | 1387 | 1455 | MiniMax M3 |
| LMArena Vision: diagrams | 1210 | 1266 | MiniMax M3 |
| LMArena Vision: homework | 1225 | 1268 | MiniMax M3 |
| Kagi LLM Benchmark | 39.7% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GPT-5.4 Nano | MiniMax M3 | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano measured |
| OTIS Mock AIME | 87.8% | 71.1% | GPT-5.4 Nano |
| FrontierMath, tiers 1 to 3 | 44.9% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5.4 Nano measured |
| ProofBench | 5.0% | 18.0% | MiniMax M3 |
| LMArena Text: math | 1405 | 1429 | MiniMax M3 |
| LMArena Text: mathematical work | 1409 | 1448 | MiniMax M3 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | GPT-5.4 Nano | MiniMax M3 | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | 84.2% | MiniMax M3 |
| LegalBench (Vals AI) | 77.9% | 85.4% | MiniMax M3 |
| CaseLaw (Vals AI) | 51.9% | Not measured | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.2% | 68.1% | MiniMax M3 |
| TaxEval (Vals AI) | 67.4% | 72.7% | MiniMax M3 |
| MortgageTax (Vals AI) | 59.1% | 68.4% | MiniMax M3 |
| MedCode (Vals AI) | 41.0% | 46.3% | MiniMax M3 |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | 1452 | MiniMax M3 |
| LMArena Text: medicine and healthcare | 1369 | 1441 | MiniMax M3 |
| LMArena Text: legal and government | 1368 | 1437 | MiniMax M3 |
| LMArena Text: business and finance | 1366 | 1434 | MiniMax M3 |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-5.4 Nano | MiniMax M3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1257 | Only MiniMax M3 measured |
| Design Arena: UI components | Not measured | 1243 | 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 | 1246 | Only MiniMax M3 measured |
| Design Arena: SVG | Not measured | 1160 | 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 index229
| Benchmark | GPT-5.4 Nano | 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) | 38.1% | 50.6% | MiniMax M3 |
| MedScribe (Vals AI) | 77.1% | 87.3% | MiniMax M3 |
| Vals Multimodal Index | 47.6% | 60.0% | MiniMax M3 |
| IFBench | 75.9% | 82.9% | MiniMax M3 |
| Long context reasoning (AA-LCR) | 76.7% | 83.0% | MiniMax M3 |
| DTBench | 80.3% | 78.9% | GPT-5.4 Nano |
| LMCA | 36.9% | 33.7% | GPT-5.4 Nano |
| Surface Evolver Bench | Not measured | 55.0% | Only MiniMax M3 measured |
| LMArena Text | 1372 | 1433 | MiniMax M3 |
| LMArena Text: instruction following | 1362 | 1433 | MiniMax M3 |
| LMArena Text: creative writing | 1315 | 1404 | MiniMax M3 |
| LMArena Vision | 1196 | 1251 | MiniMax M3 |
| LMArena Text: English | 1381 | 1443 | MiniMax M3 |
| LMArena Text: non-English | 1359 | 1420 | MiniMax M3 |
| LMArena Text: Chinese | 1391 | 1466 | MiniMax M3 |
| LMArena Text: German | 1368 | 1428 | MiniMax M3 |
| LMArena Text: Japanese | 1343 | 1380 | MiniMax M3 |
| LMArena Text: Korean | 1321 | 1373 | MiniMax M3 |
| LMArena Text: French | 1395 | 1444 | MiniMax M3 |
| LMArena Text: Spanish | 1371 | 1433 | MiniMax M3 |
| LMArena Text: Russian | 1363 | 1426 | MiniMax M3 |
| LMArena Text: Polish | 1366 | 1423 | MiniMax M3 |
| LMArena Text: multi-turn | 1382 | 1443 | MiniMax M3 |
| LMArena Text: longer queries | 1365 | 1446 | MiniMax M3 |
| LMArena Text: writing and language | 1338 | 1419 | MiniMax M3 |
| LMArena Text: entertainment and media | 1325 | 1403 | MiniMax M3 |
| LMArena Vision: English | 1202 | 1263 | MiniMax M3 |
| LMArena Vision: Chinese | 1232 | 1311 | MiniMax M3 |
| LMArena Vision: reading text | 1204 | 1259 | MiniMax M3 |
| LMArena Vision: humor | 1161 | 1235 | MiniMax M3 |
| LMArena Vision: recognizing things | 1141 | 1197 | MiniMax M3 |
| LMArena Vision: creative writing | 1159 | 1234 | MiniMax M3 |
| LMArena Document | Not measured | 1435 | Only MiniMax M3 measured |
| EQ-Bench 4 | Not measured | 1150 | Only MiniMax M3 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | 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-5.4 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5.4 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5.4 Nano 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-5.4 Nano | MiniMax M3 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | May 31, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $0.20 | $0.30 |
| Output $/Mtok | $1.25 | $1.20 |
| Coding index | 44.8 | 39.2 |
| Independent measurements behind it | 2 | 6 |
| Cost per solved task | $0.14 | $0.56 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than MiniMax M3 for coding?
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 39.2 for MiniMax M3, though on 2 benchmarks against 6. Pick MiniMax M3 for output tokens 1.0x cheaper ($1.20 vs $1.25 per million) and a larger context window (1.05M against 400K tokens).
Which is cheaper, GPT-5.4 Nano or MiniMax M3?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; MiniMax M3 costs $0.30 and $1.20. Per solved SWE-bench Verified task, GPT-5.4 Nano costs $0.14 and MiniMax M3 $0.56.
Which has the bigger context window, GPT-5.4 Nano or MiniMax M3?
MiniMax M3, with 1.05M tokens against 400K.
How many benchmarks is the GPT-5.4 Nano vs MiniMax M3 comparison based on?
76 benchmarks have a result for both models as of October 22, 2026. GPT-5.4 Nano's coding index rests on 2 independent benchmarks and MiniMax M3's on 6. Where only one model has a result, the page says so instead of naming a winner.