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Codestral 2508 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.

Codestral 2508Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.90
S ExtractScaledown
Coding
No data
Overall
No data
Output $/M
No data
vs 256K vs 1M context window. Extract fits 3.9x more.

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
Codestral 2508 only
7
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.

At a glance

Coding index
Codestral 2508 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
Codestral 2508 $0.90 against Extract Free per million output tokens.
Context window
Codestral 2508 takes 256K 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
Coding benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
ALE-Bench137.8Not measuredOnly Codestral 2508 measured
Neither model has a result on the other 37 boards here
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Intelligence benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
Neither model has a result on 2 boards here
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Agentic work benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
Neither model has a result on 39 boards here
ReasoningNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Reasoning benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
Neither model has a result on 21 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
Neither model has a result on 13 boards here
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Knowledge benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
Neither model has a result on 17 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
Design Arena: websites1013Not measuredOnly Codestral 2508 measured
Design Arena: UI components1017Not measuredOnly Codestral 2508 measured
Design Arena: game dev968Not measuredOnly Codestral 2508 measured
Design Arena: data viz1017Not measuredOnly Codestral 2508 measured
Design Arena: 3D1020Not measuredOnly Codestral 2508 measured
Design Arena: all code categories1007Not measuredOnly Codestral 2508 measured
Neither model has a result on the other 3 boards here
GeneralNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
General benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
Neither model has a result on 46 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Codestral 2508 and Extract
BenchmarkCodestral 2508ExtractLeader
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

Codestral 2508$0.0008Fits in one request
Extract$0.0000Fits in one request

Extract costs less

Repository review

50K input + 3K output tokens

Codestral 2508$0.018Fits in one request
Extract$0.0020Fits in one request

Extract costs less

Agent loop

200K input + 10K output tokens

Codestral 2508$0.069Fits in one request
Extract$0.0080Fits in one request

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.

Specifications of Codestral 2508 and Extract
SpecificationMistral Codestral 2508ScaleDown Extract
MakerMistral AIScaledown
WeightsNo public weights listedNo public weights listed
ReleasedAugust 1, 2025October 13, 2026
Context window256K1M
Input $/Mtok$0.30$0.04
Output $/Mtok$0.90Free
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Codestral 2508 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, Codestral 2508 or Extract?

Codestral 2508 costs $0.30 per million input tokens and $0.90 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, Codestral 2508 or Extract?

Extract, with 1M tokens against 256K.

How many benchmarks is the Codestral 2508 vs Extract comparison based on?

0 benchmarks have a result for both models as of October 21, 2026. Codestral 2508'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.

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