GPT-5.4 Nano vs MiniMax M2.1
MiniMax M2.1 leads GPT-5.4 Nano on the Artificial Analysis Intelligence Index, 20.9 to 20.7, at about the same output price ($1.20 vs $1.25 per million). Updated October 22, 2026; 19 benchmarks have a result for both.
GPT-5.4 Nano or MiniMax M2.1: which to pick
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding.
Pick MiniMax M2.1 for output tokens 1.0x cheaper ($1.20 vs $1.25 per million) and work measured by SWE-bench Verified (Vals AI) or AA Intelligence Index, where it leads.
- Shared results
- 19
- GPT-5.4 Nano only
- 66
- MiniMax M2.1 only
- 15
- 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
No call
Only GPT-5.4 Nano has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiniMax M2.1
MiniMax M2.1 leads, 20.9 against 20.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Nano has a AA Agentic Index result, 16.0.
Directional only
Reasoning
GPQA Diamond
MiniMax M2.1
MiniMax M2.1 leads, 78.5% against 77.5%.
Same board, both measured
Math
AIME
GPT-5.4 Nano
GPT-5.4 Nano leads, 88.8% against 77.9%.
Same board, both measured
Knowledge
MMLU Pro
MiniMax M2.1
MiniMax M2.1 leads, 87.0% against 77.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiniMax M2.1 has a Design Arena: websites result, 1201.
Directional only
Long documents
Listed context window
GPT-5.4 Nano
GPT-5.4 Nano takes 400K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Nano
GPT-5.4 Nano $0.0008, MiniMax M2.1 $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 M2.1 $0.59.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, MiniMax M2.1 not benchmarked.
- Widest category
- Math, 10.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Terminal-Bench Hard (Artificial Analysis run): GPT-5.4 Nano 42.4% against MiniMax M2.1 28.8%, 13.6 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against MiniMax M2.1 $1.20 per million output tokens, 1.0x apart.
- Context window
- GPT-5.4 Nano takes 400K tokens, MiniMax M2.1 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-5.4 Nano | Bars | MiniMax M2.1 | Ties |
|---|---|---|---|---|
| Coding | 3 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 2 | ||
| Math | 1 | 0 | ||
| Knowledge | 4 | 2 | ||
| General | 2 | 1 | ||
| All shared boards | 11 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Vals AI) | 84.0% | 81.8% | GPT-5.4 Nano |
| SWE-bench Verified (Vals AI) | 69.8% | 74.8% | MiniMax M2.1 |
| Vibe Code Bench (Vals AI) | 26.1% | Not measured | Only GPT-5.4 Nano measured |
| Code migration (Vals AI) | 14.5% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench 2.1 (Vals AI) | 41.6% | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 81.0% | Only MiniMax M2.1 measured |
| SciCode | 47.2% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | 28.8% | GPT-5.4 Nano |
| Terminal-Bench | Not measured | 36.6% | Only MiniMax M2.1 measured |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | 623.8 | GPT-5.4 Nano |
| LMArena Text: coding | 1404 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: software and IT | 1402 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | 20.9 | MiniMax M2.1 |
| Epoch Capabilities Index | 146.0 | Not measured | Only GPT-5.4 Nano measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| AA Agentic Index | 16.0 | Not measured | Only GPT-5.4 Nano measured |
| Finance Agent (Vals AI) | 38.2% | Not measured | Only GPT-5.4 Nano measured |
| Tax Agent Bench (Vals AI) | 5.0% | Not measured | Only GPT-5.4 Nano measured |
| Legal Research Bench (Vals AI) | 6.3% | Not measured | Only GPT-5.4 Nano measured |
| Excel Modeling Benchmark (Vals AI) | 44.8% | Not measured | Only GPT-5.4 Nano measured |
| τ²-Bench Telecom | 76.0% | 85.4% | MiniMax M2.1 |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | 78.5% | MiniMax M2.1 |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | 83.0% | MiniMax M2.1 |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | 23.2% | GPT-5.4 Nano |
| GPQA Diamond (Epoch AI run) | 78.5% | Not measured | Only GPT-5.4 Nano measured |
| 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 |
| Chess puzzles | 45.0% | Not measured | Only GPT-5.4 Nano measured |
| Mystery game puzzles | 9.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: expert | 1396 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts in English | 1387 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: diagrams | 1210 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: homework | 1225 | Not measured | Only GPT-5.4 Nano measured |
| Kagi LLM Benchmark | 39.7% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| AIME | 88.8% | 77.9% | GPT-5.4 Nano |
| MATH 500 (Vals AI) | Not measured | 89.0% | Only MiniMax M2.1 measured |
| MGSM (Vals AI) | Not measured | 87.8% | Only MiniMax M2.1 measured |
| AA Math Index | Not measured | 82.7 | Only MiniMax M2.1 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 82.7% | Only MiniMax M2.1 measured |
| OTIS Mock AIME | 87.8% | Not measured | Only GPT-5.4 Nano measured |
| 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% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: math | 1405 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: mathematical work | 1409 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index42
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | 87.0% | MiniMax M2.1 |
| LegalBench (Vals AI) | 77.9% | 75.5% | GPT-5.4 Nano |
| CaseLaw (Vals AI) | 51.9% | 55.8% | MiniMax M2.1 |
| CorpFin (Vals AI) | 61.2% | 58.9% | GPT-5.4 Nano |
| TaxEval (Vals AI) | 67.4% | 66.3% | GPT-5.4 Nano |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedQA (Vals AI) | Not measured | 91.2% | Only MiniMax M2.1 measured |
| MedCode (Vals AI) | 41.0% | 34.1% | GPT-5.4 Nano |
| MMLU Pro (Artificial Analysis run) | Not measured | 87.5% | Only MiniMax M2.1 measured |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: medicine and healthcare | 1369 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: legal and government | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: business and finance | 1366 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1201 | Only MiniMax M2.1 measured |
| Design Arena: UI components | Not measured | 1220 | Only MiniMax M2.1 measured |
| Design Arena: game dev | Not measured | 1134 | Only MiniMax M2.1 measured |
| Design Arena: data viz | Not measured | 1206 | Only MiniMax M2.1 measured |
| Design Arena: 3D | Not measured | 1164 | Only MiniMax M2.1 measured |
| Design Arena: all code categories | Not measured | 1190 | Only MiniMax M2.1 measured |
| Design Arena: SVG | Not measured | 1131 | Only MiniMax M2.1 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 38.1% | Not measured | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 77.1% | 80.8% | MiniMax M2.1 |
| Vals Multimodal Index | 47.6% | Not measured | Only GPT-5.4 Nano measured |
| IFBench | 75.9% | 69.9% | GPT-5.4 Nano |
| Long context reasoning (AA-LCR) | 76.7% | 67.7% | GPT-5.4 Nano |
| DTBench | 80.3% | Not measured | Only GPT-5.4 Nano measured |
| LMCA | 36.9% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text | 1372 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: instruction following | 1362 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: creative writing | 1315 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision | 1196 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: English | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: non-English | 1359 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Chinese | 1391 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: German | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Japanese | 1343 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Korean | 1321 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: French | 1395 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Spanish | 1371 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Russian | 1363 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Polish | 1366 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: multi-turn | 1382 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: longer queries | 1365 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: writing and language | 1338 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: entertainment and media | 1325 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: English | 1202 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: Chinese | 1232 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: reading text | 1204 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: humor | 1161 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: recognizing things | 1141 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: creative writing | 1159 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | MiniMax M2.1 | 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 M2.1 |
|---|---|---|
| Maker | OpenAI | MiniMax |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | December 23, 2025 |
| Context window | 400K | 205K |
| Input $/Mtok | $0.20 | $0.30 |
| Output $/Mtok | $1.25 | $1.20 |
| Coding index | 44.8 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.14 | $0.59 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than MiniMax M2.1 for coding?
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding. Pick MiniMax M2.1 for output tokens 1.0x cheaper ($1.20 vs $1.25 per million) and work measured by SWE-bench Verified (Vals AI) or AA Intelligence Index, where it leads.
Which is cheaper, GPT-5.4 Nano or MiniMax M2.1?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; MiniMax M2.1 costs $0.30 and $1.20. Per solved SWE-bench Verified task, GPT-5.4 Nano costs $0.14 and MiniMax M2.1 $0.59.
Which has the bigger context window, GPT-5.4 Nano or MiniMax M2.1?
GPT-5.4 Nano, with 400K tokens against 205K.
How many benchmarks is the GPT-5.4 Nano vs MiniMax M2.1 comparison based on?
19 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 M2.1's on 1. Where only one model has a result, the page says so instead of naming a winner.