GPT-5.4 Nano vs Mistral Large
GPT-5.4 Nano leads Mistral Large on the Artificial Analysis Intelligence Index, 20.7 to 5.8, and GPT-5.4 Nano costs 4.8x less per output token ($1.25 vs $6.00 per million). Updated October 21, 2026; 38 benchmarks have a result for both.
GPT-5.4 Nano or Mistral Large: which to pick
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 38
- GPT-5.4 Nano only
- 47
- Mistral Large only
- 6
- Like-for-like categories
- 6 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
GPT-5.4 Nano
GPT-5.4 Nano leads, 20.7 against 5.8.
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
GPT-5.4 Nano
GPT-5.4 Nano leads, 77.5% against 47.7%.
Same board, both measured
Math
AIME
GPT-5.4 Nano
GPT-5.4 Nano leads, 88.8% against 9.2%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.4 Nano
GPT-5.4 Nano leads, 77.2% against 69.7%.
Same board, both measured
Long documents
Listed context window
GPT-5.4 Nano
GPT-5.4 Nano takes 400K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Nano
GPT-5.4 Nano $0.0008, Mistral Large $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 Nano has the number, $0.14.
Directional only
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, Mistral Large not benchmarked.
- Widest category
- Math, 43.0 points apart on average over 3 shared benchmarks.
- Widest single gap
- AIME: GPT-5.4 Nano 88.8% against Mistral Large 9.2%, 79.6 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against Mistral Large $6.00 per million output tokens, 4.8x apart.
- Context window
- GPT-5.4 Nano takes 400K tokens, Mistral Large 128K.
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 | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 6 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 38 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | GPT-5.4 Nano | Mistral Large | Leader |
|---|---|---|---|
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Vals AI) | 84.0% | 37.1% | GPT-5.4 Nano |
| SWE-bench Verified (Vals AI) | 69.8% | Not measured | Only GPT-5.4 Nano measured |
| 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 | 17.8% | Only Mistral Large measured |
| SciCode | 47.2% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | Not measured | Only GPT-5.4 Nano measured |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: coding | 1404 | 1275 | GPT-5.4 Nano |
| LMArena Text: software and IT | 1402 | 1274 | GPT-5.4 Nano |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Nano | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | 5.8 | GPT-5.4 Nano |
| Epoch Capabilities Index | 146.0 | 122.1 | GPT-5.4 Nano |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.4 Nano | Mistral Large | 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% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | GPT-5.4 Nano | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | 47.7% | GPT-5.4 Nano |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | 35.1% | GPT-5.4 Nano |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | 3.5% | 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 | 1257 | GPT-5.4 Nano |
| LMArena Text: expert | 1396 | 1208 | GPT-5.4 Nano |
| LMArena Text: hard prompts in English | 1387 | 1268 | GPT-5.4 Nano |
| 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 index30
| Benchmark | GPT-5.4 Nano | Mistral Large | Leader |
|---|---|---|---|
| AIME | 88.8% | 9.2% | GPT-5.4 Nano |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large 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 | 1261 | GPT-5.4 Nano |
| LMArena Text: mathematical work | 1409 | 1257 | GPT-5.4 Nano |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | GPT-5.4 Nano | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | 69.7% | GPT-5.4 Nano |
| LegalBench (Vals AI) | 77.9% | Not measured | Only GPT-5.4 Nano measured |
| CaseLaw (Vals AI) | 51.9% | Not measured | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.2% | Not measured | Only GPT-5.4 Nano measured |
| TaxEval (Vals AI) | 67.4% | 63.8% | GPT-5.4 Nano |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MedCode (Vals AI) | 41.0% | Not measured | Only GPT-5.4 Nano measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 51.5% | Only Mistral Large measured |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| MMLU | Not measured | 68.8% | Only Mistral Large measured |
| LMArena Text: science | 1374 | 1260 | GPT-5.4 Nano |
| LMArena Text: medicine and healthcare | 1369 | 1255 | GPT-5.4 Nano |
| LMArena Text: legal and government | 1368 | 1275 | GPT-5.4 Nano |
| LMArena Text: business and finance | 1366 | 1238 | GPT-5.4 Nano |
| Neither model has a result on the other 3 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | Mistral Large | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | GPT-5.4 Nano | Mistral Large | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 38.1% | Not measured | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 77.1% | Not measured | Only GPT-5.4 Nano measured |
| Vals Multimodal Index | 47.6% | Not measured | Only GPT-5.4 Nano measured |
| IFBench | 75.9% | Not measured | Only GPT-5.4 Nano measured |
| Long context reasoning (AA-LCR) | 76.7% | Not measured | Only GPT-5.4 Nano measured |
| DTBench | 80.3% | 60.8% | GPT-5.4 Nano |
| LMCA | 36.9% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text | 1372 | 1265 | GPT-5.4 Nano |
| LMArena Text: instruction following | 1362 | 1249 | GPT-5.4 Nano |
| LMArena Text: creative writing | 1315 | 1242 | GPT-5.4 Nano |
| LMArena Vision | 1196 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: English | 1381 | 1284 | GPT-5.4 Nano |
| LMArena Text: non-English | 1359 | 1235 | GPT-5.4 Nano |
| LMArena Text: Chinese | 1391 | 1239 | GPT-5.4 Nano |
| LMArena Text: German | 1368 | 1242 | GPT-5.4 Nano |
| LMArena Text: Japanese | 1343 | 1170 | GPT-5.4 Nano |
| LMArena Text: Korean | 1321 | 1202 | GPT-5.4 Nano |
| LMArena Text: French | 1395 | 1325 | GPT-5.4 Nano |
| LMArena Text: Spanish | 1371 | 1268 | GPT-5.4 Nano |
| LMArena Text: Russian | 1363 | 1252 | GPT-5.4 Nano |
| LMArena Text: Polish | 1366 | 1157 | GPT-5.4 Nano |
| LMArena Text: multi-turn | 1382 | 1260 | GPT-5.4 Nano |
| LMArena Text: longer queries | 1365 | 1261 | GPT-5.4 Nano |
| LMArena Text: writing and language | 1338 | 1261 | GPT-5.4 Nano |
| LMArena Text: entertainment and media | 1325 | 1230 | GPT-5.4 Nano |
| 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 | Mistral Large | 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 | Mistral Large |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | March 17, 2026 | February 26, 2024 |
| Context window | 400K | 128K |
| Input $/Mtok | $0.20 | $2.00 |
| Output $/Mtok | $1.25 | $6.00 |
| Coding index | 44.8 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | $0.14 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than Mistral Large for coding?
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-5.4 Nano or Mistral Large?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for GPT-5.4 Nano only.
Which has the bigger context window, GPT-5.4 Nano or Mistral Large?
GPT-5.4 Nano, with 400K tokens against 128K.
How many benchmarks is the GPT-5.4 Nano vs Mistral Large comparison based on?
38 benchmarks have a result for both models as of October 21, 2026. GPT-5.4 Nano's coding index rests on 2 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.