GPT-5.4 Nano vs MiMo-V2.5-Pro
GPT-5.4 Nano leads MiMo-V2.5-Pro on coding, 44.8 to 31.6 on the Vibe Coding Index, and MiMo-V2.5-Pro costs 1.4x less per output token ($0.9152 vs $1.25 per million). Updated October 22, 2026; 58 benchmarks have a result for both.
GPT-5.4 Nano or MiMo-V2.5-Pro: which to pick
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 31.6 for MiMo-V2.5-Pro, though on 2 benchmarks against 4.
Pick MiMo-V2.5-Pro for output tokens 1.4x cheaper ($0.9152 vs $1.25 per million) and a lower cost per solved task ($0.03 against $0.14).
- Shared results
- 58
- GPT-5.4 Nano only
- 27
- MiMo-V2.5-Pro only
- 12
- 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 31.6.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 26.0 against 20.7.
Same board, both measured
Agentic work
AA Agentic Index
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 21.3 against 16.0.
Same board, both measured
Reasoning
GPQA Diamond
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 82.6% 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
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 84.6% against 77.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiMo-V2.5-Pro has a Design Arena: websites result, 1266.
Directional only
Long documents
Listed context window
MiMo-V2.5-Pro
MiMo-V2.5-Pro 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, MiMo-V2.5-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiMo-V2.5-Pro
GPT-5.4 Nano $0.14, MiMo-V2.5-Pro $0.03.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, MiMo-V2.5-Pro 31.6 from 4 benchmarks.
- Widest category
- Math, 14.4 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena Text: creative writing: GPT-5.4 Nano 1315 against MiMo-V2.5-Pro 1438, 20.6 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against MiMo-V2.5-Pro $0.9152 per million output tokens, 1.4x apart.
- Context window
- GPT-5.4 Nano takes 400K tokens, MiMo-V2.5-Pro 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 | MiMo-V2.5-Pro | Ties |
|---|---|---|---|---|
| Coding | 2 | 9 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 6 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 3 | ||
| Knowledge | 2 | 7 | ||
| General | 1 | 21 | ||
| All shared boards | 5 | 53 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index29
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1480 | Only MiMo-V2.5-Pro measured |
| AA Coding Index | 56.1 | 60.2 | MiMo-V2.5-Pro |
| LiveCodeBench (Vals AI) | 84.0% | 81.3% | GPT-5.4 Nano |
| SWE-bench Verified (Vals AI) | 69.8% | 74.0% | MiMo-V2.5-Pro |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.5% | Only MiMo-V2.5-Pro measured |
| Vibe Code Bench (Vals AI) | 26.1% | 34.1% | MiMo-V2.5-Pro |
| Code migration (Vals AI) | 14.5% | 21.6% | MiMo-V2.5-Pro |
| Terminal-Bench 2.1 (Vals AI) | 41.6% | 57.3% | MiMo-V2.5-Pro |
| SciCode | 47.2% | 50.6% | MiMo-V2.5-Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | 43.2% | MiMo-V2.5-Pro |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | 899.8 | GPT-5.4 Nano |
| LMArena Text: coding | 1404 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: software and IT | 1402 | 1495 | MiMo-V2.5-Pro |
| LMArena WebDev: React | Not measured | 1469 | Only MiMo-V2.5-Pro measured |
| LMArena WebDev: HTML | Not measured | 1473 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | 26.0 | MiMo-V2.5-Pro |
| 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 index06
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 16.0 | 21.3 | MiMo-V2.5-Pro |
| Finance Agent (Vals AI) | 38.2% | 41.5% | MiMo-V2.5-Pro |
| Tax Agent Bench (Vals AI) | 5.0% | 11.5% | MiMo-V2.5-Pro |
| Legal Research Bench (Vals AI) | 6.3% | 15.9% | MiMo-V2.5-Pro |
| Excel Modeling Benchmark (Vals AI) | 44.8% | 55.2% | MiMo-V2.5-Pro |
| τ²-Bench Telecom | 76.0% | 94.2% | MiMo-V2.5-Pro |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | 82.6% | MiMo-V2.5-Pro |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | 86.6% | MiMo-V2.5-Pro |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | 35.7% | MiMo-V2.5-Pro |
| 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 | 1486 | MiMo-V2.5-Pro |
| LMArena Text: expert | 1396 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: hard prompts in English | 1387 | 1494 | MiMo-V2.5-Pro |
| 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 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano 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% | 22.0% | MiMo-V2.5-Pro |
| LMArena Text: math | 1405 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: mathematical work | 1409 | 1491 | MiMo-V2.5-Pro |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index27
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | 84.6% | MiMo-V2.5-Pro |
| LegalBench (Vals AI) | 77.9% | 77.1% | GPT-5.4 Nano |
| CaseLaw (Vals AI) | 51.9% | Not measured | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.2% | 61.4% | MiMo-V2.5-Pro |
| TaxEval (Vals AI) | 67.4% | 73.8% | MiMo-V2.5-Pro |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedCode (Vals AI) | 41.0% | 32.5% | GPT-5.4 Nano |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | 1482 | MiMo-V2.5-Pro |
| LMArena Text: medicine and healthcare | 1369 | 1473 | MiMo-V2.5-Pro |
| LMArena Text: legal and government | 1368 | 1474 | MiMo-V2.5-Pro |
| LMArena Text: business and finance | 1366 | 1466 | MiMo-V2.5-Pro |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1266 | Only MiMo-V2.5-Pro measured |
| Design Arena: UI components | Not measured | 1246 | Only MiMo-V2.5-Pro measured |
| Design Arena: game dev | Not measured | 1261 | Only MiMo-V2.5-Pro measured |
| Design Arena: data viz | Not measured | 1257 | Only MiMo-V2.5-Pro measured |
| Design Arena: 3D | Not measured | 1243 | Only MiMo-V2.5-Pro measured |
| Design Arena: all code categories | Not measured | 1265 | Only MiMo-V2.5-Pro measured |
| Design Arena: SVG | Not measured | 1181 | Only MiMo-V2.5-Pro measured |
| Design Arena: ASCII art | Not measured | 1156 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index121
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 38.1% | Not measured | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 77.1% | 83.7% | MiMo-V2.5-Pro |
| Vals Multimodal Index | 47.6% | Not measured | Only GPT-5.4 Nano measured |
| IFBench | 75.9% | 79.9% | MiMo-V2.5-Pro |
| Long context reasoning (AA-LCR) | 76.7% | 79.7% | MiMo-V2.5-Pro |
| DTBench | 80.3% | 84.5% | MiMo-V2.5-Pro |
| LMCA | 36.9% | 29.5% | GPT-5.4 Nano |
| LMArena Text | 1372 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: instruction following | 1362 | 1475 | MiMo-V2.5-Pro |
| LMArena Text: creative writing | 1315 | 1438 | MiMo-V2.5-Pro |
| LMArena Vision | 1196 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: English | 1381 | 1477 | MiMo-V2.5-Pro |
| LMArena Text: non-English | 1359 | 1448 | MiMo-V2.5-Pro |
| LMArena Text: Chinese | 1391 | 1507 | MiMo-V2.5-Pro |
| LMArena Text: German | 1368 | 1459 | MiMo-V2.5-Pro |
| LMArena Text: Japanese | 1343 | 1410 | MiMo-V2.5-Pro |
| LMArena Text: Korean | 1321 | 1435 | MiMo-V2.5-Pro |
| LMArena Text: French | 1395 | 1487 | MiMo-V2.5-Pro |
| LMArena Text: Spanish | 1371 | 1469 | MiMo-V2.5-Pro |
| LMArena Text: Russian | 1363 | 1449 | MiMo-V2.5-Pro |
| LMArena Text: Polish | 1366 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: multi-turn | 1382 | 1476 | MiMo-V2.5-Pro |
| LMArena Text: longer queries | 1365 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: writing and language | 1338 | 1451 | MiMo-V2.5-Pro |
| LMArena Text: entertainment and media | 1325 | 1438 | MiMo-V2.5-Pro |
| 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 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | MiMo-V2.5-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
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 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Maker | OpenAI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | April 22, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $0.20 | $0.4575 |
| Output $/Mtok | $1.25 | $0.9152 |
| Coding index | 44.8 | 31.6 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | $0.14 | $0.03 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than MiMo-V2.5-Pro for coding?
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 31.6 for MiMo-V2.5-Pro, though on 2 benchmarks against 4. Pick MiMo-V2.5-Pro for output tokens 1.4x cheaper ($0.9152 vs $1.25 per million) and a lower cost per solved task ($0.03 against $0.14).
Which is cheaper, GPT-5.4 Nano or MiMo-V2.5-Pro?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; MiMo-V2.5-Pro costs $0.4575 and $0.9152. Per solved SWE-bench Verified task, GPT-5.4 Nano costs $0.14 and MiMo-V2.5-Pro $0.03.
Which has the bigger context window, GPT-5.4 Nano or MiMo-V2.5-Pro?
MiMo-V2.5-Pro, with 1.05M tokens against 400K.
How many benchmarks is the GPT-5.4 Nano vs MiMo-V2.5-Pro comparison based on?
58 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 MiMo-V2.5-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.