GPT-4o-mini vs Mistral Large 3 2512
Mistral Large 3 2512 leads GPT-4o-mini on the Artificial Analysis Intelligence Index, 9.3 to 6.7, and GPT-4o-mini costs 2.5x less per output token ($0.60 vs $1.50 per million). Updated October 21, 2026; 14 benchmarks have a result for both.
GPT-4o-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-4o-mini for output tokens 2.5x cheaper ($0.60 vs $1.50 per million) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.
- Shared results
- 14
- GPT-4o-mini only
- 15
- Mistral Large 3 2512 only
- 14
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Mistral Large 3 2512
Mistral Large 3 2512 leads, 9.3 against 6.7.
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
Mistral Large 3 2512
Mistral Large 3 2512 leads, 68.4% against 44.2%.
Same board, both measured
Math
AIME
Mistral Large 3 2512
Mistral Large 3 2512 leads, 42.9% against 11.5%.
Same board, both measured
Knowledge
MMLU Pro
Mistral Large 3 2512
Mistral Large 3 2512 leads, 79.8% against 62.7%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Large 3 2512 has a Design Arena: websites result, 1162.
Directional only
Long documents
Listed context window
Mistral Large 3 2512
Mistral Large 3 2512 takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o-mini
GPT-4o-mini $0.0004, 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-4o-mini not benchmarked, Mistral Large 3 2512 not benchmarked.
- Widest category
- Coding, 18.8 points apart on average over 2 shared benchmarks.
- Widest single gap
- AIME: GPT-4o-mini 11.5% against Mistral Large 3 2512 42.9%, 31.5 points apart on a 0 to 100 scale.
- Output price
- GPT-4o-mini $0.60 against Mistral Large 3 2512 $1.50 per million output tokens, 2.5x apart.
- Context window
- GPT-4o-mini takes 128K 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-4o-mini | Bars | Mistral Large 3 2512 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Math | 1 | 1 | ||
| Knowledge | 1 | 4 | ||
| General | 0 | 2 | ||
| All shared boards | 2 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Coding Index | 11.4 | 20.1 | Mistral Large 3 2512 |
| LiveCodeBench (Vals AI) | 26.4% | 55.3% | Mistral Large 3 2512 |
| SWE-bench Verified (Vals AI) | Not measured | 41.4% | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Artificial Analysis run) | 23.4% | Not measured | Only GPT-4o-mini measured |
| ALE-Bench | Not measured | 264.7 | Only Mistral Large 3 2512 measured |
| SciCode | 1.5% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 9.3 | Mistral Large 3 2512 |
| Epoch Capabilities Index | 126.5 | Not measured | Only GPT-4o-mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.0 | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| GPQA Diamond | 44.2% | 68.4% | Mistral Large 3 2512 |
| MMMU Pro (Vals AI) | 56.6% | 66.2% | Mistral Large 3 2512 |
| GPQA Diamond (Artificial Analysis run) | 42.6% | Not measured | Only GPT-4o-mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | Not measured | Only GPT-4o-mini measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o-mini measured |
| Kagi LLM Benchmark | 28.8% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AIME | 11.5% | 42.9% | Mistral Large 3 2512 |
| MATH 500 (Vals AI) | 72.6% | Not measured | Only GPT-4o-mini measured |
| MGSM (Vals AI) | 86.2% | 85.4% | GPT-4o-mini |
| AA Math Index | 14.7 | Not measured | Only GPT-4o-mini measured |
| AIME 2025 (Artificial Analysis run) | 14.7% | Not measured | Only GPT-4o-mini measured |
| GSM8K | 91.3% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| MMLU Pro | 62.7% | 79.8% | Mistral Large 3 2512 |
| 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) | 45.5% | 61.0% | Mistral Large 3 2512 |
| TaxEval (Vals AI) | 60.5% | 73.1% | Mistral Large 3 2512 |
| MortgageTax (Vals AI) | 54.5% | 52.1% | GPT-4o-mini |
| MedQA (Vals AI) | 72.4% | 82.2% | Mistral Large 3 2512 |
| MMLU Pro (Artificial Analysis run) | 64.8% | Not measured | Only GPT-4o-mini measured |
| MMLU | 81.8% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1162 | Only Mistral Large 3 2512 measured |
| Design Arena: UI components | Not measured | 1102 | Only Mistral Large 3 2512 measured |
| Design Arena: game dev | Not measured | 1080 | Only Mistral Large 3 2512 measured |
| Design Arena: data viz | Not measured | 1136 | Only Mistral Large 3 2512 measured |
| Design Arena: 3D | Not measured | 1100 | Only Mistral Large 3 2512 measured |
| Design Arena: all code categories | Not measured | 1142 | Only Mistral Large 3 2512 measured |
| Design Arena: SVG | Not measured | 993 | Only Mistral Large 3 2512 measured |
| Design Arena: ASCII art | Not measured | 1069 | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o-mini | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 24.6% | Only Mistral Large 3 2512 measured |
| IFBench | 31.0% | Not measured | Only GPT-4o-mini measured |
| DTBench | 54.4% | 65.1% | Mistral Large 3 2512 |
| LMCA | 10.4% | 16.7% | Mistral Large 3 2512 |
| PIQA | 88.7% | Not measured | Only GPT-4o-mini 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-4o-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
GPT-4o-mini costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini costs less
Agent loop
200K input + 10K output tokens
GPT-4o-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-4o-mini | Mistral Large 3 2512 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | July 18, 2024 | December 1, 2025 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.15 | $0.50 |
| Output $/Mtok | $0.60 | $1.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | $0.77 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-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-4o-mini for output tokens 2.5x cheaper ($0.60 vs $1.50 per million) and work measured by AA Coding Index or LiveCodeBench (Vals AI), where it leads.
Which is cheaper, GPT-4o-mini or Mistral Large 3 2512?
GPT-4o-mini costs $0.15 per million input tokens and $0.60 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-4o-mini or Mistral Large 3 2512?
Mistral Large 3 2512, with 262K tokens against 128K.
How many benchmarks is the GPT-4o-mini vs Mistral Large 3 2512 comparison based on?
14 benchmarks have a result for both models as of October 21, 2026. GPT-4o-mini's coding index rests on 0 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.