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Codestral 2508 vs Mistral Large

Updated October 21, 2026. No benchmark has tested both models yet. 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
Mistral LargeMistral AI
Coding
No data
Overall
5.8
Output $/M
$6.00
vs $0.90 vs $6.00 per 1M output tokens. Codestral 2508 is 6.7x cheaper.

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Codestral 2508 has the edge where output tokens cost 6.7x less, and where the context window is larger, 256K against 128K tokens.

No benchmark has tested both yet. Codestral 2508 has results on ALE-Bench, Design Arena: websites and Design Arena: UI components; Mistral Large on LiveCodeBench (Vals AI), LiveCodeBench (Artificial Analysis run) and LMArena Text: coding. 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.

At a glance

Coding index
Codestral 2508 not benchmarked, Mistral Large 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
Codestral 2508 $0.90 against Mistral Large $6.00 per million output tokens, 6.7x apart.
Context window
Codestral 2508 takes 256K tokens, Mistral Large 128K.

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 Index5 boards measured
Coding benchmarks for Codestral 2508 and Mistral Large
BenchmarkCodestral 2508Mistral LargeLeader
LiveCodeBench (Vals AI)Not measured37.1%Only Mistral Large measured
LiveCodeBench (Artificial Analysis run)Not measured17.8%Only Mistral Large measured
ALE-Bench137.8Not measuredOnly Codestral 2508 measured
LMArena Text: codingNot measured1275Only Mistral Large measured
LMArena Text: software and ITNot measured1274Only Mistral Large measured
Neither model has a result on the other 33 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for Codestral 2508 and Mistral Large
BenchmarkCodestral 2508Mistral LargeLeader
AA Intelligence IndexNot measured5.8Only Mistral Large measured
Epoch Capabilities IndexNot measured122.1Only Mistral Large measured
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Reasoning benchmarks for Codestral 2508 and Mistral Large
BenchmarkCodestral 2508Mistral LargeLeader
GPQA DiamondNot measured47.7%Only Mistral Large measured
GPQA Diamond (Artificial Analysis run)Not measured35.1%Only Mistral Large measured
Humanity's Last Exam (Artificial Analysis run)Not measured3.5%Only Mistral Large measured
LMArena Text: hard promptsNot measured1257Only Mistral Large measured
LMArena Text: expertNot measured1208Only Mistral Large measured
LMArena Text: hard prompts in EnglishNot measured1268Only Mistral Large measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Math benchmarks for Codestral 2508 and Mistral Large
BenchmarkCodestral 2508Mistral LargeLeader
AIMENot measured9.2%Only Mistral Large measured
MATH 500 (Vals AI)Not measured74.4%Only Mistral Large measured
MGSM (Vals AI)Not measured87.2%Only Mistral Large measured
LMArena Text: mathNot measured1261Only Mistral Large measured
LMArena Text: mathematical workNot measured1257Only Mistral Large measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
Knowledge benchmarks for Codestral 2508 and Mistral Large
BenchmarkCodestral 2508Mistral LargeLeader
MMLU ProNot measured69.7%Only Mistral Large measured
TaxEval (Vals AI)Not measured63.8%Only Mistral Large measured
MedQA (Vals AI)Not measured76.2%Only Mistral Large measured
MMLU Pro (Artificial Analysis run)Not measured51.5%Only Mistral Large measured
MMLUNot measured68.8%Only Mistral Large measured
LMArena Text: scienceNot measured1260Only Mistral Large measured
LMArena Text: medicine and healthcareNot measured1255Only Mistral Large measured
LMArena Text: legal and governmentNot measured1275Only Mistral Large measured
LMArena Text: business and financeNot measured1238Only Mistral Large measured
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Web design benchmarks for Codestral 2508 and Mistral Large
BenchmarkCodestral 2508Mistral LargeLeader
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
GeneralDirectional onlyPublic boards, shown as published, kept out of the index18 boards measured
General benchmarks for Codestral 2508 and Mistral Large
BenchmarkCodestral 2508Mistral LargeLeader
DTBenchNot measured60.8%Only Mistral Large measured
LMArena TextNot measured1265Only Mistral Large measured
LMArena Text: instruction followingNot measured1249Only Mistral Large measured
LMArena Text: creative writingNot measured1242Only Mistral Large measured
LMArena Text: EnglishNot measured1284Only Mistral Large measured
LMArena Text: non-EnglishNot measured1235Only Mistral Large measured
LMArena Text: ChineseNot measured1239Only Mistral Large measured
LMArena Text: GermanNot measured1242Only Mistral Large measured
LMArena Text: JapaneseNot measured1170Only Mistral Large measured
LMArena Text: KoreanNot measured1202Only Mistral Large measured
LMArena Text: FrenchNot measured1325Only Mistral Large measured
LMArena Text: SpanishNot measured1268Only Mistral Large measured
LMArena Text: RussianNot measured1252Only Mistral Large measured
LMArena Text: PolishNot measured1157Only Mistral Large measured
LMArena Text: multi-turnNot measured1260Only Mistral Large measured
LMArena Text: longer queriesNot measured1261Only Mistral Large measured
LMArena Text: writing and languageNot measured1261Only Mistral Large measured
LMArena Text: entertainment and mediaNot measured1230Only Mistral Large measured
Neither model has a result on the other 28 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
Mistral Large$0.0050Fits in one request

Codestral 2508 costs less

Repository review

50K input + 3K output tokens

Codestral 2508$0.018Fits in one request
Mistral Large$0.118Fits in one request

Codestral 2508 costs less

Agent loop

200K input + 10K output tokens

Codestral 2508$0.069Fits in one request
Mistral Large$0.460Exceeds the context window

Codestral 2508 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 Mistral Large
SpecificationMistral Codestral 2508Mistral Large
MakerMistral AIMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 1, 2025February 26, 2024
Context window256K128K
Input $/Mtok$0.30$2.00
Output $/Mtok$0.90$6.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Codestral 2508 better than Mistral Large for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Codestral 2508 has the edge where output tokens cost 6.7x less, and where the context window is larger, 256K against 128K tokens.

Which is cheaper, Codestral 2508 or Mistral Large?

Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Codestral 2508 or Mistral Large?

Codestral 2508, with 256K tokens against 128K.

Has any benchmark tested both Codestral 2508 and Mistral Large?

No benchmark has tested both yet. Codestral 2508 has results on ALE-Bench, Design Arena: websites and Design Arena: UI components; Mistral Large on LiveCodeBench (Vals AI), LiveCodeBench (Artificial Analysis run) and LMArena Text: coding. Compare them on price and context instead. Data as of October 21, 2026.

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