GPT-5.1-Codex-Mini vs Mistral Large 3 2512
GPT-5.1-Codex-Mini leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 20.4 to 9.3, and Mistral Large 3 2512 costs 1.3x less per output token ($1.50 vs $2.00 per million). Updated October 22, 2026; 9 benchmarks have a result for both.
GPT-5.1-Codex-Mini or Mistral Large 3 2512: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Mini for a larger context window (400K against 262K tokens) and work measured by Design Arena: websites or Design Arena: UI components, where it leads.
- Shared results
- 9
- GPT-5.1-Codex-Mini only
- 13
- Mistral Large 3 2512 only
- 19
- Like-for-like categories
- 2 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads, 20.4 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
No call
Only Mistral Large 3 2512 has a GPQA Diamond result, 68.4%.
Directional only
Math
AIME
No call
Only Mistral Large 3 2512 has a AIME result, 42.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large 3 2512 has a MMLU Pro result, 79.8%.
Directional only
Web design
Design Arena: websites
Mistral Large 3 2512
Mistral Large 3 2512 leads, 1162 against 1111.
Same board, both measured
Long documents
Listed context window
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
GPT-5.1-Codex-Mini $0.0013, Mistral Large 3 2512 $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Large 3 2512 has the number, $0.77.
Directional only
At a glance
- Coding index
- GPT-5.1-Codex-Mini not benchmarked, Mistral Large 3 2512 not benchmarked.
- Widest category
- Intelligence, 11.1 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: 3D: GPT-5.1-Codex-Mini 988 against Mistral Large 3 2512 1099, 13.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Mini $2.00 against Mistral Large 3 2512 $1.50 per million output tokens, 1.3x apart.
- Context window
- GPT-5.1-Codex-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-5.1-Codex-Mini | Bars | Mistral Large 3 2512 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Web design | 2 | 6 | ||
| All shared boards | 3 | 6 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| LMArena WebDev | 1244 | Not measured | Only GPT-5.1-Codex-Mini measured |
| AA Coding Index | Not measured | 20.1 | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Vals AI) | Not measured | 55.3% | Only Mistral Large 3 2512 measured |
| SWE-bench Verified (Vals AI) | Not measured | 41.4% | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Artificial Analysis run) | 83.6% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Terminal-Bench | 61.6% | Not measured | Only GPT-5.1-Codex-Mini measured |
| ALE-Bench | Not measured | 264.7 | Only Mistral Large 3 2512 measured |
| LMArena WebDev: HTML | 1253 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.4 | 9.3 | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.0 | Only Mistral Large 3 2512 measured |
| τ²-Bench Telecom | 62.9% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 68.4% | Only Mistral Large 3 2512 measured |
| MMMU Pro (Vals AI) | Not measured | 66.2% | Only Mistral Large 3 2512 measured |
| GPQA Diamond (Artificial Analysis run) | 81.3% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 18.5% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AIME | Not measured | 42.9% | Only Mistral Large 3 2512 measured |
| MGSM (Vals AI) | Not measured | 85.4% | Only Mistral Large 3 2512 measured |
| AA Math Index | 91.7 | Not measured | Only GPT-5.1-Codex-Mini measured |
| AIME 2025 (Artificial Analysis run) | 91.7% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 79.8% | Only Mistral Large 3 2512 measured |
| LegalBench (Vals AI) | Not measured | 79.1% | Only Mistral Large 3 2512 measured |
| CaseLaw (Vals AI) | Not measured | 61.4% | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | Not measured | 61.0% | Only Mistral Large 3 2512 measured |
| TaxEval (Vals AI) | Not measured | 73.1% | Only Mistral Large 3 2512 measured |
| MortgageTax (Vals AI) | Not measured | 52.1% | Only Mistral Large 3 2512 measured |
| MedQA (Vals AI) | Not measured | 82.2% | Only Mistral Large 3 2512 measured |
| MMLU Pro (Artificial Analysis run) | 82.0% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index26
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 1111 | 1162 | Mistral Large 3 2512 |
| Design Arena: UI components | 1078 | 1099 | Mistral Large 3 2512 |
| Design Arena: game dev | 1092 | 1080 | GPT-5.1-Codex-Mini |
| Design Arena: data viz | 1097 | 1136 | Mistral Large 3 2512 |
| Design Arena: 3D | 988 | 1099 | Mistral Large 3 2512 |
| Design Arena: all code categories | 1093 | 1141 | Mistral Large 3 2512 |
| Design Arena: SVG | 978 | 992 | Mistral Large 3 2512 |
| Design Arena: ASCII art | 1105 | 1069 | GPT-5.1-Codex-Mini |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-5.1-Codex-Mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 24.6% | Only Mistral Large 3 2512 measured |
| IFBench | 67.9% | Not measured | Only GPT-5.1-Codex-Mini measured |
| Long context reasoning (AA-LCR) | 66.7% | Not measured | Only GPT-5.1-Codex-Mini measured |
| DTBench | Not measured | 65.1% | Only Mistral Large 3 2512 measured |
| LMCA | Not measured | 16.7% | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex-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-5.1-Codex-Mini costs less
Agent loop
200K input + 10K output tokens
GPT-5.1-Codex-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-5.1-Codex-Mini | Mistral Large 3 2512 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | November 13, 2025 | December 1, 2025 |
| Context window | 400K | 262K |
| Input $/Mtok | $0.25 | $0.50 |
| Output $/Mtok | $2.00 | $1.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | $0.77 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Mini better than Mistral Large 3 2512 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Mini for a larger context window (400K against 262K tokens) and work measured by Design Arena: websites or Design Arena: UI components, where it leads.
Which is cheaper, GPT-5.1-Codex-Mini or Mistral Large 3 2512?
GPT-5.1-Codex-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. Cost per solved task is known for Mistral Large 3 2512 only.
Which has the bigger context window, GPT-5.1-Codex-Mini or Mistral Large 3 2512?
GPT-5.1-Codex-Mini, with 400K tokens against 262K.
How many benchmarks is the GPT-5.1-Codex-Mini vs Mistral Large 3 2512 comparison based on?
9 benchmarks have a result for both models as of October 22, 2026. GPT-5.1-Codex-Mini's coding index rests on 1 independent benchmark and Mistral Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.