GPT-5.4 Mini vs Mistral Medium 3.5
GPT-5.4 Mini leads Mistral Medium 3.5 on coding, 35.8 to 25.5 on the Vibe Coding Index, and GPT-5.4 Mini costs 1.7x less per output token ($4.50 vs $7.50 per million). Updated October 22, 2026; 70 benchmarks have a result for both.
GPT-5.4 Mini or Mistral Medium 3.5: which to pick
Pick GPT-5.4 Mini for coding: it scores 35.8 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5.
Pick Mistral Medium 3.5 for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 70
- GPT-5.4 Mini only
- 19
- Mistral Medium 3.5 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
GPT-5.4 Mini
GPT-5.4 Mini scores 35.8 against 25.5.
5 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.4 Mini
GPT-5.4 Mini leads, 24.1 against 14.2.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.4 Mini
GPT-5.4 Mini leads, 17.9 against 7.0.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.4 Mini
GPT-5.4 Mini leads, 83.1% against 34.9%.
Same board, both measured
Math
AIME
No call
Only GPT-5.4 Mini has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
GPT-5.4 Mini
GPT-5.4 Mini leads, 84.5% against 75.3%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Medium 3.5 has a Design Arena: websites result, 1142.
Directional only
Long documents
Listed context window
GPT-5.4 Mini
GPT-5.4 Mini takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Mini
GPT-5.4 Mini $0.0030, Mistral Medium 3.5 $0.0053 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.4 Mini
GPT-5.4 Mini $0.70, Mistral Medium 3.5 $6.02.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.4 Mini 35.8 from 5 benchmarks, Mistral Medium 3.5 25.5 from 3 benchmarks.
- Widest category
- Coding, 15.1 points apart on average over 13 shared benchmarks.
- Widest single gap
- GPQA Diamond: GPT-5.4 Mini 83.1% against Mistral Medium 3.5 34.9%, 48.2 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Mini $4.50 against Mistral Medium 3.5 $7.50 per million output tokens, 1.7x apart.
- Context window
- GPT-5.4 Mini takes 400K tokens, Mistral Medium 3.5 262K.
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 Mini | Bars | Mistral Medium 3.5 | Ties |
|---|---|---|---|---|
| Coding | 11 | 2 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 5 | 1 | ||
| Reasoning | 6 | 3 | ||
| Math | 1 | 2 | ||
| Knowledge | 5 | 4 | ||
| General | 17 | 11 | ||
| All shared boards | 47 | 23 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index112
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| LMArena WebDev | 1397 | 1264 | GPT-5.4 Mini |
| AA Coding Index | 56.1 | 46.9 | GPT-5.4 Mini |
| LiveCodeBench (Vals AI) | 81.5% | Not measured | Only GPT-5.4 Mini measured |
| SWE-bench Verified (Vals AI) | 73.0% | 66.4% | GPT-5.4 Mini |
| Terminal-Bench 4 (Vals AI) | 2.5% | Not measured | Only GPT-5.4 Mini measured |
| Vibe Code Bench (Vals AI) | 48.0% | 2.9% | GPT-5.4 Mini |
| Code migration (Vals AI) | 12.9% | 5.1% | GPT-5.4 Mini |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only GPT-5.4 Mini measured |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | 39.0% | GPT-5.4 Mini |
| SciCode | 52.1% | 40.2% | GPT-5.4 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 52.3% | 33.3% | GPT-5.4 Mini |
| FrontierCode | 27.0% | Not measured | Only GPT-5.4 Mini measured |
| WeirdML | 60.3% | Not measured | Only GPT-5.4 Mini measured |
| ALE-Bench | 1188.6 | 764.0 | GPT-5.4 Mini |
| LMArena Text: coding | 1438 | 1460 | Mistral Medium 3.5 |
| LMArena Text: software and IT | 1436 | 1458 | Mistral Medium 3.5 |
| LMArena WebDev: React | 1386 | 1254 | GPT-5.4 Mini |
| LMArena WebDev: HTML | 1419 | 1308 | GPT-5.4 Mini |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.1 | 14.2 | GPT-5.4 Mini |
| Epoch Capabilities Index | 148.7 | 141.4 | GPT-5.4 Mini |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 17.9 | 7.0 | GPT-5.4 Mini |
| Finance Agent (Vals AI) | 45.4% | 32.1% | GPT-5.4 Mini |
| Tax Agent Bench (Vals AI) | 8.8% | 4.5% | GPT-5.4 Mini |
| Legal Research Bench (Vals AI) | 12.5% | 9.1% | GPT-5.4 Mini |
| Excel Modeling Benchmark (Vals AI) | 45.4% | 11.2% | GPT-5.4 Mini |
| τ²-Bench Telecom | 83.3% | 94.2% | Mistral Medium 3.5 |
| DeepResearch Bench | 36.3% | Not measured | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index63
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 83.1% | 34.9% | GPT-5.4 Mini |
| MMMU Pro (Vals AI) | 79.3% | Not measured | Only GPT-5.4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 87.5% | 74.8% | GPT-5.4 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 28.1% | 13.8% | GPT-5.4 Mini |
| GPQA Diamond (Epoch AI run) | 86.9% | Not measured | Only GPT-5.4 Mini measured |
| ARC-AGI | 63.7% | Not measured | Only GPT-5.4 Mini measured |
| ARC-AGI-2 | 18.9% | Not measured | Only GPT-5.4 Mini measured |
| Chess puzzles | 23.0% | Not measured | Only GPT-5.4 Mini measured |
| Mystery game puzzles | 11.0% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts | 1424 | 1436 | Mistral Medium 3.5 |
| LMArena Text: expert | 1435 | 1432 | GPT-5.4 Mini |
| LMArena Text: hard prompts in English | 1420 | 1445 | Mistral Medium 3.5 |
| LMArena Vision: diagrams | 1266 | 1254 | GPT-5.4 Mini |
| LMArena Vision: homework | 1285 | 1230 | GPT-5.4 Mini |
| Kagi LLM Benchmark | 37.9% | 41.4% | Mistral Medium 3.5 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AIME | 95.6% | Not measured | Only GPT-5.4 Mini measured |
| OTIS Mock AIME | 88.9% | Not measured | Only GPT-5.4 Mini measured |
| FrontierMath, tiers 1 to 3 | 51.2% | Not measured | Only GPT-5.4 Mini measured |
| FrontierMath, tier 4 | 9.8% | Not measured | Only GPT-5.4 Mini measured |
| ProofBench | 21.0% | 9.0% | GPT-5.4 Mini |
| LMArena Text: math | 1418 | 1431 | Mistral Medium 3.5 |
| LMArena Text: mathematical work | 1429 | 1440 | Mistral Medium 3.5 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index54
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| MMLU Pro | 84.5% | 75.3% | GPT-5.4 Mini |
| CaseLaw (Vals AI) | 51.7% | 44.2% | GPT-5.4 Mini |
| CorpFin (Vals AI) | 60.9% | 58.8% | GPT-5.4 Mini |
| TaxEval (Vals AI) | 71.2% | 68.0% | GPT-5.4 Mini |
| MortgageTax (Vals AI) | 63.5% | 28.9% | GPT-5.4 Mini |
| MedCode (Vals AI) | Not measured | 33.8% | Only Mistral Medium 3.5 measured |
| SimpleQA Verified | 29.4% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: science | 1417 | 1428 | Mistral Medium 3.5 |
| LMArena Text: medicine and healthcare | 1395 | 1409 | Mistral Medium 3.5 |
| LMArena Text: legal and government | 1414 | 1437 | Mistral Medium 3.5 |
| LMArena Text: business and finance | 1418 | 1426 | Mistral Medium 3.5 |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1142 | Only Mistral Medium 3.5 measured |
| Design Arena: UI components | Not measured | 1076 | Only Mistral Medium 3.5 measured |
| Design Arena: game dev | Not measured | 1079 | Only Mistral Medium 3.5 measured |
| Design Arena: data viz | Not measured | 1120 | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | Not measured | 1060 | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | Not measured | 1121 | Only Mistral Medium 3.5 measured |
| Design Arena: SVG | Not measured | 949 | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | Not measured | 1062 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index1711
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 50.8% | 37.6% | GPT-5.4 Mini |
| MedScribe (Vals AI) | Not measured | 67.7% | Only Mistral Medium 3.5 measured |
| Vals Multimodal Index | 54.2% | 34.8% | GPT-5.4 Mini |
| IFBench | 73.3% | 68.8% | GPT-5.4 Mini |
| Long context reasoning (AA-LCR) | 77.0% | 69.3% | GPT-5.4 Mini |
| DTBench | 80.0% | 75.5% | GPT-5.4 Mini |
| LMCA | 40.8% | 26.1% | GPT-5.4 Mini |
| Surface Evolver Bench | Not measured | 26.9% | Only Mistral Medium 3.5 measured |
| LMArena Text | 1412 | 1421 | Mistral Medium 3.5 |
| LMArena Text: instruction following | 1405 | 1415 | Mistral Medium 3.5 |
| LMArena Text: creative writing | 1370 | 1374 | Mistral Medium 3.5 |
| LMArena Vision | 1245 | 1222 | GPT-5.4 Mini |
| LMArena Text: English | 1412 | 1433 | Mistral Medium 3.5 |
| LMArena Text: non-English | 1405 | 1404 | GPT-5.4 Mini |
| LMArena Text: Chinese | 1446 | 1444 | GPT-5.4 Mini |
| LMArena Text: German | 1408 | 1453 | Mistral Medium 3.5 |
| LMArena Text: Japanese | 1375 | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: Korean | 1370 | 1384 | Mistral Medium 3.5 |
| LMArena Text: French | 1441 | 1448 | Mistral Medium 3.5 |
| LMArena Text: Spanish | 1405 | 1411 | Mistral Medium 3.5 |
| LMArena Text: Russian | 1417 | 1395 | GPT-5.4 Mini |
| LMArena Text: Polish | 1415 | 1430 | Mistral Medium 3.5 |
| LMArena Text: multi-turn | 1429 | 1423 | GPT-5.4 Mini |
| LMArena Text: longer queries | 1408 | 1415 | Mistral Medium 3.5 |
| LMArena Text: writing and language | 1393 | 1384 | GPT-5.4 Mini |
| LMArena Text: entertainment and media | 1373 | 1382 | Mistral Medium 3.5 |
| LMArena Vision: English | 1244 | 1240 | GPT-5.4 Mini |
| LMArena Vision: Chinese | 1286 | 1244 | GPT-5.4 Mini |
| LMArena Vision: reading text | 1253 | 1233 | GPT-5.4 Mini |
| LMArena Vision: humor | 1235 | 1216 | GPT-5.4 Mini |
| LMArena Vision: recognizing things | 1218 | Not measured | Only GPT-5.4 Mini measured |
| LMArena Vision: creative writing | 1222 | 1198 | GPT-5.4 Mini |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Mini | Mistral Medium 3.5 | 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 Mini costs less
Repository review
50K input + 3K output tokens
GPT-5.4 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5.4 Mini 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 Mini | Mistral Medium 3.5 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | March 17, 2026 | April 30, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $0.75 | $1.50 |
| Output $/Mtok | $4.50 | $7.50 |
| Coding index | 35.8 | 25.5 |
| Independent measurements behind it | 5 | 3 |
| Cost per solved task | $0.70 | $6.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Mini better than Mistral Medium 3.5 for coding?
Pick GPT-5.4 Mini for coding: it scores 35.8 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5. Pick Mistral Medium 3.5 for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, GPT-5.4 Mini or Mistral Medium 3.5?
GPT-5.4 Mini costs $0.75 per million input tokens and $4.50 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Per solved SWE-bench Verified task, GPT-5.4 Mini costs $0.70 and Mistral Medium 3.5 $6.02.
Which has the bigger context window, GPT-5.4 Mini or Mistral Medium 3.5?
GPT-5.4 Mini, with 400K tokens against 262K.
How many benchmarks is the GPT-5.4 Mini vs Mistral Medium 3.5 comparison based on?
70 benchmarks have a result for both models as of October 22, 2026. GPT-5.4 Mini's coding index rests on 5 independent benchmarks and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.