GPT-5.4 Nano vs Mistral Medium 3
GPT-5.4 Nano leads Mistral Medium 3 on the Artificial Analysis Intelligence Index, 20.7 to 9.0, and GPT-5.4 Nano costs 1.6x less per output token ($1.25 vs $2.00 per million). Updated October 23, 2026; 46 benchmarks have a result for both.
GPT-5.4 Nano or Mistral Medium 3: which to pick
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Mistral Medium 3 has none, so the two cannot be ranked on coding.
Pick Mistral Medium 3 for work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.
- Shared results
- 46
- GPT-5.4 Nano only
- 39
- Mistral Medium 3 only
- 11
- 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
GPT-5.4 Nano
GPT-5.4 Nano leads, 20.7 against 9.0.
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
No call
Only GPT-5.4 Nano has a GPQA Diamond result, 77.5%.
Directional only
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Nano has a MMLU Pro result, 77.2%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Medium 3 has a Design Arena: websites result, 1079.
Directional only
Long documents
Listed context window
GPT-5.4 Nano
GPT-5.4 Nano takes 400K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Nano
GPT-5.4 Nano $0.0008, Mistral Medium 3 $0.0014 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 Medium 3 not benchmarked.
- Widest category
- Agentic work, 51.8 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GPT-5.4 Nano 76.0% against Mistral Medium 3 24.3%, 51.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against Mistral Medium 3 $2.00 per million output tokens, 1.6x apart.
- Context window
- GPT-5.4 Nano takes 400K tokens, Mistral Medium 3 131K.
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 Medium 3 | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 7 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 3 | ||
| General | 20 | 7 | ||
| All shared boards | 36 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only GPT-5.4 Nano measured |
| 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 | 40.0% | Only Mistral Medium 3 measured |
| SciCode | 47.2% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | 3.8% | GPT-5.4 Nano |
| 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 | 1405 | 1385 | GPT-5.4 Nano |
| LMArena Text: software and IT | 1403 | 1385 | GPT-5.4 Nano |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | 9.0 | GPT-5.4 Nano |
| Epoch Capabilities Index | 146.0 | 134.0 | GPT-5.4 Nano |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | 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% | 24.3% | GPT-5.4 Nano |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | Not measured | Only GPT-5.4 Nano measured |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | 57.8% | GPT-5.4 Nano |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | 4.1% | 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 | 1364 | GPT-5.4 Nano |
| LMArena Text: expert | 1396 | 1342 | GPT-5.4 Nano |
| LMArena Text: hard prompts in English | 1387 | 1374 | GPT-5.4 Nano |
| LMArena Vision: diagrams | 1210 | 1155 | GPT-5.4 Nano |
| LMArena Vision: homework | 1225 | 1165 | GPT-5.4 Nano |
| 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 index20
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano measured |
| AA Math Index | Not measured | 30.3 | Only Mistral Medium 3 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 30.3% | Only Mistral Medium 3 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 | 1406 | 1353 | GPT-5.4 Nano |
| LMArena Text: mathematical work | 1409 | 1354 | GPT-5.4 Nano |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-5.4 Nano measured |
| 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% | Not measured | Only GPT-5.4 Nano measured |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedCode (Vals AI) | 41.0% | Not measured | Only GPT-5.4 Nano measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 76.0% | Only Mistral Medium 3 measured |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | 1381 | Mistral Medium 3 |
| LMArena Text: medicine and healthcare | 1369 | 1381 | Mistral Medium 3 |
| LMArena Text: legal and government | 1368 | 1384 | Mistral Medium 3 |
| LMArena Text: business and finance | 1366 | 1352 | GPT-5.4 Nano |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1079 | Only Mistral Medium 3 measured |
| Design Arena: UI components | Not measured | 1022 | Only Mistral Medium 3 measured |
| Design Arena: game dev | Not measured | 1017 | Only Mistral Medium 3 measured |
| Design Arena: data viz | Not measured | 1035 | Only Mistral Medium 3 measured |
| Design Arena: 3D | Not measured | 1084 | Only Mistral Medium 3 measured |
| Design Arena: all code categories | Not measured | 1068 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index207
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | 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% | 39.3% | GPT-5.4 Nano |
| Long context reasoning (AA-LCR) | 76.7% | 31.3% | GPT-5.4 Nano |
| DTBench | 80.3% | 62.3% | GPT-5.4 Nano |
| LMCA | 36.9% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text | 1372 | 1370 | GPT-5.4 Nano |
| LMArena Text: instruction following | 1362 | 1338 | GPT-5.4 Nano |
| LMArena Text: creative writing | 1314 | 1343 | Mistral Medium 3 |
| LMArena Vision | 1196 | 1157 | GPT-5.4 Nano |
| LMArena Text: English | 1381 | 1384 | Mistral Medium 3 |
| LMArena Text: non-English | 1360 | 1353 | GPT-5.4 Nano |
| LMArena Text: Chinese | 1391 | 1374 | GPT-5.4 Nano |
| LMArena Text: German | 1368 | 1377 | Mistral Medium 3 |
| LMArena Text: Japanese | 1343 | 1316 | GPT-5.4 Nano |
| LMArena Text: Korean | 1320 | 1304 | GPT-5.4 Nano |
| LMArena Text: French | 1395 | 1368 | GPT-5.4 Nano |
| LMArena Text: Spanish | 1371 | 1364 | GPT-5.4 Nano |
| LMArena Text: Russian | 1362 | 1359 | GPT-5.4 Nano |
| LMArena Text: Polish | 1366 | 1371 | Mistral Medium 3 |
| LMArena Text: multi-turn | 1382 | 1383 | Mistral Medium 3 |
| LMArena Text: longer queries | 1366 | 1360 | GPT-5.4 Nano |
| LMArena Text: writing and language | 1338 | 1352 | Mistral Medium 3 |
| LMArena Text: entertainment and media | 1324 | 1335 | Mistral Medium 3 |
| LMArena Vision: English | 1202 | 1172 | GPT-5.4 Nano |
| LMArena Vision: Chinese | 1232 | 1161 | GPT-5.4 Nano |
| LMArena Vision: reading text | 1204 | 1154 | GPT-5.4 Nano |
| LMArena Vision: humor | 1161 | 1145 | GPT-5.4 Nano |
| LMArena Vision: captioning | Not measured | 1094 | Only Mistral Medium 3 measured |
| LMArena Vision: recognizing things | 1141 | 1141 | GPT-5.4 Nano |
| LMArena Vision: creative writing | 1159 | 1146 | GPT-5.4 Nano |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | Mistral Medium 3 | 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 Medium 3 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | March 17, 2026 | May 7, 2025 |
| Context window | 400K | 131K |
| Input $/Mtok | $0.20 | $0.40 |
| Output $/Mtok | $1.25 | $2.00 |
| 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 Medium 3 for coding?
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Mistral Medium 3 has none, so the two cannot be ranked on coding. Pick Mistral Medium 3 for work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.
Which is cheaper, GPT-5.4 Nano or Mistral Medium 3?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; Mistral Medium 3 costs $0.40 and $2.00. Cost per solved task is known for GPT-5.4 Nano only.
Which has the bigger context window, GPT-5.4 Nano or Mistral Medium 3?
GPT-5.4 Nano, with 400K tokens against 131K.
How many benchmarks is the GPT-5.4 Nano vs Mistral Medium 3 comparison based on?
46 benchmarks have a result for both models as of October 23, 2026. GPT-5.4 Nano's coding index rests on 2 independent benchmarks and Mistral Medium 3's on 0. Where only one model has a result, the page says so instead of naming a winner.