GPT-4o-mini (2024-07-18) vs Mistral Large 3 2512
GPT-4o-mini (2024-07-18) costs 2.5x less per output token than Mistral Large 3 2512 ($0.60 vs $1.50 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.50
GPT-4o-mini (2024-07-18) 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 (2024-07-18) for output tokens 2.5x cheaper ($0.60 vs $1.50 per million).
No benchmark has tested both yet. GPT-4o-mini (2024-07-18) has results on Aider polyglot, WeirdML and LMArena Text: coding; Mistral Large 3 2512 on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI). Compare them on price and context instead.
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
No call
Only Mistral Large 3 2512 has a AA Intelligence Index result, 9.3.
Directional only
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
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 (2024-07-18)
GPT-4o-mini (2024-07-18) $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 (2024-07-18) not benchmarked, Mistral Large 3 2512 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-4o-mini (2024-07-18) $0.60 against Mistral Large 3 2512 $1.50 per million output tokens, 2.5x apart.
- Context window
- GPT-4o-mini (2024-07-18) takes 128K tokens, Mistral Large 3 2512 262K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Aider polyglot | 3.6% | Not measured | Only GPT-4o-mini (2024-07-18) 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 |
| WeirdML | 11.8% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| ALE-Bench | Not measured | 264.7 | Only Mistral Large 3 2512 measured |
| LMArena Text: coding | 1290 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: software and IT | 1291 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 9.3 | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.0 | Only Mistral Large 3 2512 measured |
| BALROG | 17.4% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | 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 (Epoch AI run) | 37.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| SimpleBench | 10.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Chess puzzles | 3.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Mystery game puzzles | 12.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| VPCT | 34.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: hard prompts | 1267 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: expert | 1234 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: hard prompts in English | 1278 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | 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 |
| OTIS Mock AIME | 6.9% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| FrontierMath, tiers 1 to 3 | 0.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| MATH level 5 | 52.6% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: math | 1267 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: mathematical work | 1271 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | 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 |
| SimpleQA Verified | 8.3% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| MMLU | 76.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| GeoBench | 64.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: science | 1286 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: medicine and healthcare | 1282 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: legal and government | 1305 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: business and finance | 1265 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1162 | Only Mistral Large 3 2512 measured |
| Design Arena: UI components | Not measured | 1099 | Only Mistral Large 3 2512 measured |
| Design Arena: game dev | Not measured | 1079 | Only Mistral Large 3 2512 measured |
| Design Arena: data viz | Not measured | 1137 | Only Mistral Large 3 2512 measured |
| Design Arena: 3D | Not measured | 1099 | Only Mistral Large 3 2512 measured |
| Design Arena: all code categories | Not measured | 1141 | Only Mistral Large 3 2512 measured |
| Design Arena: SVG | Not measured | 992 | 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 | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index24 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 24.6% | Only Mistral Large 3 2512 measured |
| DTBench | Not measured | 65.1% | Only Mistral Large 3 2512 measured |
| LMCA | Not measured | 16.7% | Only Mistral Large 3 2512 measured |
| Creative writing (Lech Mazur) | 67.2% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text | 1286 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: instruction following | 1258 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: creative writing | 1268 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision | 1066 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: English | 1301 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: non-English | 1266 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Chinese | 1265 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: German | 1272 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Japanese | 1216 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Korean | 1195 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: French | 1297 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Spanish | 1276 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Russian | 1275 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Polish | 1244 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: multi-turn | 1285 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: longer queries | 1289 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: writing and language | 1282 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: entertainment and media | 1253 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision: English | 1072 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision: Chinese | 1033 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 24 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 (2024-07-18) costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini (2024-07-18) costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini (2024-07-18) 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 (2024-07-18) | 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 (2024-07-18) 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 (2024-07-18) for output tokens 2.5x cheaper ($0.60 vs $1.50 per million).
Which is cheaper, GPT-4o-mini (2024-07-18) or Mistral Large 3 2512?
GPT-4o-mini (2024-07-18) 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 (2024-07-18) or Mistral Large 3 2512?
Mistral Large 3 2512, with 262K tokens against 128K.
Has any benchmark tested both GPT-4o-mini (2024-07-18) and Mistral Large 3 2512?
No benchmark has tested both yet. GPT-4o-mini (2024-07-18) has results on Aider polyglot, WeirdML and LMArena Text: coding; Mistral Large 3 2512 on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI). Compare them on price and context instead. Data as of October 22, 2026.