GPT-4o vs Mistral Large 2407
Mistral Large 2407 costs 1.7x less per output token than GPT-4o ($6.00 vs $10.00 per million). Updated October 21, 2026; 11 benchmarks have a result for both.
GPT-4o or Mistral Large 2407: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o for work measured by τ²-Bench Telecom or Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 11
- GPT-4o only
- 15
- Mistral Large 2407 only
- 6
- 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
No call
Only Mistral Large 2407 has a AA Intelligence Index result, 7.6.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
Mistral Large 2407
Mistral Large 2407 takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large 2407
GPT-4o $0.0075, Mistral Large 2407 $0.0050 per turn.
List prices
At a glance
- Coding index
- GPT-4o not benchmarked, Mistral Large 2407 not benchmarked.
- Widest category
- General, 17.8 points apart on average over 3 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): GPT-4o 49.3% against Mistral Large 2407 2.0%, 47.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4o $10.00 against Mistral Large 2407 $6.00 per million output tokens, 1.7x apart.
- Context window
- GPT-4o takes 128K tokens, Mistral Large 2407 131K.
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 | Bars | Mistral Large 2407 | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 2 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 9 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| SWE-bench Verified | 38.8% | Not measured | Only GPT-4o measured |
| SWE-bench Lite | 38.0% | Not measured | Only GPT-4o measured |
| SWE-bench (full test set) | 18.8% | Not measured | Only GPT-4o measured |
| SWE-bench Multimodal | 30.4% | Not measured | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | 30.9% | 26.7% | GPT-4o |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 7.6 | Only Mistral Large 2407 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 25.1% | 33.0% | Mistral Large 2407 |
| GDPval | 9.9% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 54.3% | 47.2% | GPT-4o |
| Humanity's Last Exam (Artificial Analysis run) | 2.4% | 2.9% | Mistral Large 2407 |
| GPQA Diamond (Epoch AI run) | Not measured | 49.0% | Only Mistral Large 2407 measured |
| ARC-AGI | 4.5% | Not measured | Only GPT-4o measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o measured |
| SimpleBench | Not measured | 22.5% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Math Index | 6.0 | 0.0 | GPT-4o |
| AIME 2025 (Artificial Analysis run) | 6.0% | 0.0% | GPT-4o |
| OTIS Mock AIME | Not measured | 8.5% | Only Mistral Large 2407 measured |
| MATH level 5 | Not measured | 44.8% | Only Mistral Large 2407 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 74.8% | 68.3% | GPT-4o |
| MMLU | 88.1% | 80.0% | GPT-4o |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| Design Arena: websites | 831 | Not measured | Only GPT-4o measured |
| Design Arena: UI components | 885 | Not measured | Only GPT-4o measured |
| Design Arena: game dev | 906 | Not measured | Only GPT-4o measured |
| Design Arena: data viz | 858 | Not measured | Only GPT-4o measured |
| Design Arena: 3D | 869 | Not measured | Only GPT-4o measured |
| Design Arena: all code categories | 861 | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-4o | Mistral Large 2407 | Leader |
|---|---|---|---|
| IFBench | 34.3% | 31.6% | GPT-4o |
| Long context reasoning (AA-LCR) | 49.3% | 2.0% | GPT-4o |
| DTBench | 64.5% | 61.2% | GPT-4o |
| LMCA | 16.6% | Not measured | Only GPT-4o measured |
| Creative writing (Lech Mazur) | Not measured | 69.0% | Only Mistral Large 2407 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 | Mistral Large 2407 | 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
Mistral Large 2407 costs less
Repository review
50K input + 3K output tokens
Mistral Large 2407 costs less
Agent loop
200K input + 10K output tokens
Mistral Large 2407 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 | Mistral Large 2407 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | May 13, 2024 | November 19, 2024 |
| Context window | 128K | 131K |
| Input $/Mtok | $2.50 | $2.00 |
| Output $/Mtok | $10.00 | $6.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o better than Mistral Large 2407 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o for work measured by τ²-Bench Telecom or Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4o or Mistral Large 2407?
GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens; Mistral Large 2407 costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o or Mistral Large 2407?
Mistral Large 2407, with 131K tokens against 128K.
How many benchmarks is the GPT-4o vs Mistral Large 2407 comparison based on?
11 benchmarks have a result for both models as of October 21, 2026. GPT-4o's coding index rests on 0 independent benchmarks and Mistral Large 2407's on 0. Where only one model has a result, the page says so instead of naming a winner.