GPT-5 Mini vs Mistral Large 3 2512
GPT-5 Mini leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 20.6 to 9.3, and Mistral Large 3 2512 costs 1.3x less per output token ($1.50 vs $2.00 per million). Updated October 21, 2026; 25 benchmarks have a result for both.
GPT-5 Mini or Mistral Large 3 2512: which to pick
Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for output tokens 1.3x cheaper ($1.50 vs $2.00 per million) and work measured by CorpFin (Vals AI) or Design Arena: websites, where it leads.
- Shared results
- 25
- GPT-5 Mini only
- 76
- Mistral Large 3 2512 only
- 3
- 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 Mini has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5 Mini
GPT-5 Mini leads, 20.6 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Large 3 2512 has a AA Agentic Index result, 1.0.
Directional only
Reasoning
GPQA Diamond
GPT-5 Mini
GPT-5 Mini leads, 80.3% against 68.4%.
Same board, both measured
Math
AIME
GPT-5 Mini
GPT-5 Mini leads, 91.5% against 42.9%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5 Mini
GPT-5 Mini leads, 82.2% against 79.8%.
Same board, both measured
Web design
Design Arena: websites
Mistral Large 3 2512
Mistral Large 3 2512 leads, 1162 against 1125.
Same board, both measured
Long documents
Listed context window
GPT-5 Mini
GPT-5 Mini takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
GPT-5 Mini $0.0013, Mistral Large 3 2512 $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5 Mini
GPT-5 Mini $0.08, Mistral Large 3 2512 $0.77.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5 Mini 34.2 from 2 benchmarks, Mistral Large 3 2512 not benchmarked.
- Widest category
- Math, 27.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- AIME: GPT-5 Mini 91.5% against Mistral Large 3 2512 42.9%, 48.5 points apart on a 0 to 100 scale.
- Output price
- GPT-5 Mini $2.00 against Mistral Large 3 2512 $1.50 per million output tokens, 1.3x apart.
- Context window
- GPT-5 Mini takes 400K tokens, Mistral Large 3 2512 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 Mini | Bars | Mistral Large 3 2512 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 6 | 1 | ||
| Web design | 4 | 4 | ||
| General | 3 | 0 | ||
| All shared boards | 20 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SWE-bench Verified | 59.8% | Not measured | Only GPT-5 Mini measured |
| SWE-bench Multilingual | 39.7% | Not measured | Only GPT-5 Mini measured |
| AA Coding Index | Not measured | 20.1 | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Vals AI) | 86.6% | 55.3% | GPT-5 Mini |
| SWE-bench Verified (Vals AI) | 60.8% | 41.4% | GPT-5 Mini |
| Vibe Code Bench (Vals AI) | 14.2% | Not measured | Only GPT-5 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 83.8% | Not measured | Only GPT-5 Mini measured |
| SciCode | 39.0% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only GPT-5 Mini measured |
| Terminal-Bench | 34.8% | Not measured | Only GPT-5 Mini measured |
| WeirdML | 52.7% | Not measured | Only GPT-5 Mini measured |
| ALE-Bench | Not measured | 264.7 | Only Mistral Large 3 2512 measured |
| LMArena Text: coding | 1406 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: software and IT | 1394 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.6 | 9.3 | GPT-5 Mini |
| Epoch Capabilities Index | 145.3 | Not measured | Only GPT-5 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.0 | Only Mistral Large 3 2512 measured |
| τ²-Bench Telecom | 71.1% | Not measured | Only GPT-5 Mini measured |
| Vending-Bench 2 | -$31 | Not measured | Only GPT-5 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | 55.5% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| GPQA Diamond | 80.3% | 68.4% | GPT-5 Mini |
| MMMU Pro (Vals AI) | 78.9% | 66.2% | GPT-5 Mini |
| GPQA Diamond (Artificial Analysis run) | 82.8% | Not measured | Only GPT-5 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 21.5% | Not measured | Only GPT-5 Mini measured |
| GPQA Diamond (Epoch AI run) | 75.0% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI | 54.3% | Not measured | Only GPT-5 Mini measured |
| ARC-AGI-2 | 4.4% | Not measured | Only GPT-5 Mini measured |
| Chess puzzles | 24.0% | Not measured | Only GPT-5 Mini measured |
| Mystery game puzzles | 10.0% | Not measured | Only GPT-5 Mini measured |
| VPCT | 40.2% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: expert | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: hard prompts in English | 1383 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: diagrams | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: homework | 1210 | Not measured | Only GPT-5 Mini measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AIME | 91.5% | 42.9% | GPT-5 Mini |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only GPT-5 Mini measured |
| MGSM (Vals AI) | 92.6% | 85.4% | GPT-5 Mini |
| AA Math Index | 90.7 | Not measured | Only GPT-5 Mini measured |
| AIME 2025 (Artificial Analysis run) | 90.7% | Not measured | Only GPT-5 Mini measured |
| OTIS Mock AIME | 86.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tiers 1 to 3 | 46.7% | Not measured | Only GPT-5 Mini measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5 Mini measured |
| ProofBench | 9.0% | Not measured | Only GPT-5 Mini measured |
| MATH level 5 | 97.8% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: math | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: mathematical work | 1380 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| MMLU Pro | 82.2% | 79.8% | GPT-5 Mini |
| LegalBench (Vals AI) | 81.8% | 79.1% | GPT-5 Mini |
| CaseLaw (Vals AI) | 68.5% | 61.4% | GPT-5 Mini |
| CorpFin (Vals AI) | 60.2% | 61.0% | Mistral Large 3 2512 |
| TaxEval (Vals AI) | 75.2% | 73.1% | GPT-5 Mini |
| MortgageTax (Vals AI) | 66.9% | 52.1% | GPT-5 Mini |
| MedQA (Vals AI) | 96.1% | 82.2% | GPT-5 Mini |
| MedCode (Vals AI) | 43.0% | Not measured | Only GPT-5 Mini measured |
| MMLU Pro (Artificial Analysis run) | 83.7% | Not measured | Only GPT-5 Mini measured |
| SimpleQA Verified | 21.6% | Not measured | Only GPT-5 Mini measured |
| LMArena Text: science | 1371 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: medicine and healthcare | 1380 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: legal and government | 1375 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: business and finance | 1358 | Not measured | Only GPT-5 Mini measured |
| FACTS Benchmark Suite | 38.6% | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1125 | 1162 | Mistral Large 3 2512 |
| Design Arena: UI components | 1106 | 1102 | GPT-5 Mini |
| Design Arena: game dev | 1130 | 1080 | GPT-5 Mini |
| Design Arena: data viz | 1130 | 1136 | Mistral Large 3 2512 |
| Design Arena: 3D | 1037 | 1100 | Mistral Large 3 2512 |
| Design Arena: all code categories | 1115 | 1142 | Mistral Large 3 2512 |
| Design Arena: SVG | 1091 | 993 | GPT-5 Mini |
| Design Arena: ASCII art | 1125 | 1069 | GPT-5 Mini |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 43.0% | 24.6% | GPT-5 Mini |
| MedScribe (Vals AI) | 80.6% | Not measured | Only GPT-5 Mini measured |
| IFBench | 75.4% | Not measured | Only GPT-5 Mini measured |
| Long context reasoning (AA-LCR) | 72.3% | Not measured | Only GPT-5 Mini measured |
| DTBench | 80.5% | 65.1% | GPT-5 Mini |
| LMCA | 34.2% | 16.7% | GPT-5 Mini |
| Fiction.LiveBench | 69.4% | Not measured | Only GPT-5 Mini measured |
| Creative writing (Lech Mazur) | 83.1% | Not measured | Only GPT-5 Mini measured |
| LMArena Text | 1373 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: instruction following | 1357 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: creative writing | 1325 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision | 1202 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: English | 1379 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: non-English | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Chinese | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: German | 1366 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Japanese | 1341 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Korean | 1308 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: French | 1386 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Spanish | 1354 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Russian | 1362 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: Polish | 1378 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: multi-turn | 1363 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: longer queries | 1355 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: writing and language | 1344 | Not measured | Only GPT-5 Mini measured |
| LMArena Text: entertainment and media | 1340 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: English | 1216 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: Chinese | 1214 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: reading text | 1199 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: humor | 1205 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: captioning | 1217 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only GPT-5 Mini measured |
| LMArena Vision: creative writing | 1181 | Not measured | Only GPT-5 Mini measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Mini | Mistral Large 3 2512 | 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
Same cost
Repository review
50K input + 3K output tokens
GPT-5 Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5 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 Mini | Mistral Large 3 2512 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | August 7, 2025 | December 1, 2025 |
| Context window | 400K | 262K |
| Input $/Mtok | $0.25 | $0.50 |
| Output $/Mtok | $2.00 | $1.50 |
| Coding index | 34.2 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.08 | $0.77 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Mini better than Mistral Large 3 2512 for coding?
Only GPT-5 Mini has a coding score, 34.2 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for output tokens 1.3x cheaper ($1.50 vs $2.00 per million) and work measured by CorpFin (Vals AI) or Design Arena: websites, where it leads.
Which is cheaper, GPT-5 Mini or Mistral Large 3 2512?
GPT-5 Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Mistral Large 3 2512 costs $0.50 and $1.50. Per solved SWE-bench Verified task, GPT-5 Mini costs $0.08 and Mistral Large 3 2512 $0.77.
Which has the bigger context window, GPT-5 Mini or Mistral Large 3 2512?
GPT-5 Mini, with 400K tokens against 262K.
How many benchmarks is the GPT-5 Mini vs Mistral Large 3 2512 comparison based on?
25 benchmarks have a result for both models as of October 21, 2026. GPT-5 Mini's coding index rests on 2 independent benchmarks and Mistral Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.