Mistral Large 2407 vs Extract
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- 7.6
- Output $/M
- $6.00
- Coding
- No data
- Overall
- No data
- Output $/M
- No data
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 0
- Mistral Large 2407 only
- 17
- Extract only
- 0
- Like-for-like categories
- 0 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
Long documents
Listed context window
Extract
Extract takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Extract
Mistral Large 2407 $0.0050, Extract $0.0000 per turn.
List prices
At a glance
- Coding index
- Mistral Large 2407 not benchmarked, Extract not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- Mistral Large 2407 $6.00 against Extract Free per million output tokens.
- Context window
- Mistral Large 2407 takes 131K tokens, Extract 1M.
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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index1 board, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 26.7% | Not measured | Only Mistral Large 2407 measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.6 | Not measured | Only Mistral Large 2407 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 33.0% | Not measured | Only Mistral Large 2407 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 47.2% | Not measured | Only Mistral Large 2407 measured |
| Humanity's Last Exam (Artificial Analysis run) | 2.9% | Not measured | Only Mistral Large 2407 measured |
| GPQA Diamond (Epoch AI run) | 49.0% | Not measured | Only Mistral Large 2407 measured |
| SimpleBench | 22.5% | Not measured | Only Mistral Large 2407 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| AA Math Index | 0.0 | Not measured | Only Mistral Large 2407 measured |
| AIME 2025 (Artificial Analysis run) | 0.0% | Not measured | Only Mistral Large 2407 measured |
| OTIS Mock AIME | 8.5% | Not measured | Only Mistral Large 2407 measured |
| MATH level 5 | 44.8% | Not measured | Only Mistral Large 2407 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 68.3% | Not measured | Only Mistral Large 2407 measured |
| MMLU | 80.0% | Not measured | Only Mistral Large 2407 measured |
| Neither model has a result on the other 15 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Large 2407 | Extract | Leader |
|---|---|---|---|
| IFBench | 31.6% | Not measured | Only Mistral Large 2407 measured |
| Long context reasoning (AA-LCR) | 2.0% | Not measured | Only Mistral Large 2407 measured |
| DTBench | 61.2% | Not measured | Only Mistral Large 2407 measured |
| Creative writing (Lech Mazur) | 69.0% | Not measured | Only Mistral Large 2407 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 2407 | Extract | 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
Extract costs less
Repository review
50K input + 3K output tokens
Extract costs less
Agent loop
200K input + 10K output tokens
Extract 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 | Mistral Large 2407 | ScaleDown Extract |
|---|---|---|
| Maker | Mistral AI | Scaledown |
| Weights | No public weights listed | No public weights listed |
| Released | November 19, 2024 | October 13, 2026 |
| Context window | 131K | 1M |
| Input $/Mtok | $2.00 | $0.04 |
| Output $/Mtok | $6.00 | Free |
| 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 Mistral Large 2407 better than Extract for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Mistral Large 2407 or Extract?
Mistral Large 2407 costs $2.00 per million input tokens and $6.00 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 2407 or Extract?
Extract, with 1M tokens against 131K.
How many benchmarks is the Mistral Large 2407 vs Extract comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. Mistral Large 2407's coding index rests on 0 independent benchmarks and Extract's on 0. Where only one model has a result, the page says so instead of naming a winner.