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Codestral 2508 vs MiniMax M2

Codestral 2508 and MiniMax M2 cost about the same per output token ($0.90 vs $1.02 per million). Updated October 21, 2026; 7 benchmarks have a result for both.

Codestral 2508Mistral AI
Coding
No data
Overall
No data
Output $/M
$0.90
0
MiniMax M2MiniMax
Coding
No data
Overall
No data
Output $/M
$1.02
7
vs boards won of 7 shared

Codestral 2508 or MiniMax M2: which to pick

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

Pick Codestral 2508 for output tokens 1.1x cheaper ($0.90 vs $1.02 per million) and a larger context window (256K against 205K tokens).

Shared results
7
Codestral 2508 only
1
MiniMax M2 only
43
Like-for-like categories
2 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.

At a glance

Coding index
Codestral 2508 not benchmarked, MiniMax M2 not benchmarked.
Widest category
Reasoning, 25.3 points apart on average over 1 shared benchmark.
Widest single gap
Kagi LLM Benchmark: Codestral 2508 32.5% against MiniMax M2 57.8%, 25.3 points apart on a 0 to 100 scale.
Output price
Codestral 2508 $0.90 against MiniMax M2 $1.02 per million output tokens, 1.1x apart.
Context window
Codestral 2508 takes 256K tokens, MiniMax M2 205K.

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.

Boards won, where both have a result
CategoryCodestral 2508BarsMiniMax M2Ties
Reasoning01
Web design06
All shared boards07
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards, none shared
Coding benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
SWE-bench VerifiedNot measured61.0%Only MiniMax M2 measured
LMArena WebDevNot measured1297Only MiniMax M2 measured
LiveCodeBench (Artificial Analysis run)Not measured82.6%Only MiniMax M2 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured25.8%Only MiniMax M2 measured
Terminal-BenchNot measured30.0%Only MiniMax M2 measured
ALE-Bench137.8Not measuredOnly Codestral 2508 measured
LMArena Text: codingNot measured1371Only MiniMax M2 measured
LMArena Text: software and ITNot measured1373Only MiniMax M2 measured
LMArena WebDev: HTMLNot measured1306Only MiniMax M2 measured
Neither model has a result on the other 30 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
AA Intelligence IndexNot measured18.6Only MiniMax M2 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, none shared
Agentic work benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
τ²-Bench TelecomNot measured86.8%Only MiniMax M2 measured
Vending-Bench 2Not measured$161Only MiniMax M2 measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
GPQA Diamond (Artificial Analysis run)Not measured77.7%Only MiniMax M2 measured
Humanity's Last Exam (Artificial Analysis run)Not measured13.7%Only MiniMax M2 measured
LMArena Text: hard promptsNot measured1357Only MiniMax M2 measured
LMArena Text: expertNot measured1338Only MiniMax M2 measured
LMArena Text: hard prompts in EnglishNot measured1376Only MiniMax M2 measured
Kagi LLM Benchmark32.5%57.8%MiniMax M2
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
AA Math IndexNot measured78.3Only MiniMax M2 measured
AIME 2025 (Artificial Analysis run)Not measured78.3%Only MiniMax M2 measured
LMArena Text: mathNot measured1351Only MiniMax M2 measured
LMArena Text: mathematical workNot measured1368Only MiniMax M2 measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
MMLU Pro (Artificial Analysis run)Not measured82.0%Only MiniMax M2 measured
LMArena Text: scienceNot measured1348Only MiniMax M2 measured
LMArena Text: medicine and healthcareNot measured1367Only MiniMax M2 measured
LMArena Text: legal and governmentNot measured1349Only MiniMax M2 measured
LMArena Text: business and financeNot measured1336Only MiniMax M2 measured
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
Design Arena: websites10131143MiniMax M2
Design Arena: UI components10171136MiniMax M2
Design Arena: game dev9681118MiniMax M2
Design Arena: data viz10171140MiniMax M2
Design Arena: 3D10201098MiniMax M2
Design Arena: all code categories10071135MiniMax M2
Design Arena: SVGNot measured1100Only MiniMax M2 measured
Neither model has a result on the other 2 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
General benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
IFBenchNot measured72.3%Only MiniMax M2 measured
Long context reasoning (AA-LCR)Not measured64.3%Only MiniMax M2 measured
LMArena TextNot measured1340Only MiniMax M2 measured
LMArena Text: instruction followingNot measured1329Only MiniMax M2 measured
LMArena Text: creative writingNot measured1286Only MiniMax M2 measured
LMArena Text: EnglishNot measured1364Only MiniMax M2 measured
LMArena Text: non-EnglishNot measured1313Only MiniMax M2 measured
LMArena Text: ChineseNot measured1366Only MiniMax M2 measured
LMArena Text: GermanNot measured1357Only MiniMax M2 measured
LMArena Text: FrenchNot measured1336Only MiniMax M2 measured
LMArena Text: SpanishNot measured1326Only MiniMax M2 measured
LMArena Text: RussianNot measured1330Only MiniMax M2 measured
LMArena Text: PolishNot measured1312Only MiniMax M2 measured
LMArena Text: multi-turnNot measured1361Only MiniMax M2 measured
LMArena Text: longer queriesNot measured1331Only MiniMax M2 measured
LMArena Text: writing and languageNot measured1295Only MiniMax M2 measured
LMArena Text: entertainment and mediaNot measured1298Only MiniMax M2 measured
Neither model has a result on the other 29 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Codestral 2508 and MiniMax M2
BenchmarkCodestral 2508MiniMax M2Leader
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
MiniMax M2$0.0008Fits in one request

Codestral 2508 costs less

Repository review

50K input + 3K output tokens

Codestral 2508$0.018Fits in one request
MiniMax M2$0.016Fits in one request

MiniMax M2 costs less

Agent loop

200K input + 10K output tokens

Codestral 2508$0.069Fits in one request
MiniMax M2$0.061Exceeds the context window

MiniMax M2 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 MiniMax M2
SpecificationMistral Codestral 2508MiniMax M2
MakerMistral AIMiniMax
WeightsNo public weights listedOpen weights
ReleasedAugust 1, 2025October 23, 2025
Context window256K205K
Input $/Mtok$0.30$0.255
Output $/Mtok$0.90$1.02
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computable$0.702
SourceOpenRouter listingOpenRouter listing

Questions

Is Codestral 2508 better than MiniMax M2 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Codestral 2508 for output tokens 1.1x cheaper ($0.90 vs $1.02 per million) and a larger context window (256K against 205K tokens).

Which is cheaper, Codestral 2508 or MiniMax M2?

Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Cost per solved task is known for MiniMax M2 only.

Which has the bigger context window, Codestral 2508 or MiniMax M2?

Codestral 2508, with 256K tokens against 205K.

How many benchmarks is the Codestral 2508 vs MiniMax M2 comparison based on?

7 benchmarks have a result for both models as of October 21, 2026. Codestral 2508's coding index rests on 0 independent benchmarks and MiniMax M2's on 1. Where only one model has a result, the page says so instead of naming a winner.

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