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Codestral 2508 vs Gemma 4 26B A4B

Updated October 21, 2026. 1 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
0
Gemma 4 26B A4BGoogle
Coding
No data
Overall
16.7
Output $/M
$0.60
1
vs boards won of 1 shared

Decision reading

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

Codestral 2508 has the edge where the benchmark that matters is ALE-Bench, where it leads.

Shared results
1
Codestral 2508 only
6
Gemma 4 26B A4B only
53
Like-for-like categories
1 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, Gemma 4 26B A4B not benchmarked.
Widest category
Coding, 26.3 points apart on average over 1 shared benchmark.
Widest single gap
ALE-Bench: Codestral 2508 137.8 against Gemma 4 26B A4B 927.2, 26.3 points apart on a 0 to 100 scale.
Output price
Codestral 2508 $0.90 against Gemma 4 26B A4B $0.60 per million output tokens, 1.5x apart.
Context window
Codestral 2508 takes 256K tokens, Gemma 4 26B A4B 262K.

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 2508BarsGemma 4 26B A4BTies
Coding01
All shared boards01
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
LMArena WebDevNot measured1360Only Gemma 4 26B A4B measured
AA Coding IndexNot measured39.3Only Gemma 4 26B A4B measured
SciCodeNot measured40.0%Only Gemma 4 26B A4B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured25.0%Only Gemma 4 26B A4B measured
WeirdMLNot measured35.2%Only Gemma 4 26B A4B measured
ALE-Bench137.8927.2Gemma 4 26B A4B
LMArena Text: codingNot measured1446Only Gemma 4 26B A4B measured
LMArena Text: software and ITNot measured1454Only Gemma 4 26B A4B measured
LMArena WebDev: ReactNot measured1351Only Gemma 4 26B A4B measured
LMArena WebDev: HTMLNot measured1362Only Gemma 4 26B A4B measured
Neither model has a result on the other 28 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
AA Intelligence IndexNot measured16.7Only Gemma 4 26B A4B measured
Epoch Capabilities IndexNot measured141.9Only Gemma 4 26B A4B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
AA Agentic IndexNot measured2.9Only Gemma 4 26B A4B measured
τ²-Bench TelecomNot measured43.6%Only Gemma 4 26B A4B measured
Neither model has a result on the other 37 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Reasoning benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
GPQA Diamond (Artificial Analysis run)Not measured79.2%Only Gemma 4 26B A4B measured
Humanity's Last Exam (Artificial Analysis run)Not measured19.3%Only Gemma 4 26B A4B measured
GPQA Diamond (Epoch AI run)Not measured73.2%Only Gemma 4 26B A4B measured
LMArena Text: hard promptsNot measured1438Only Gemma 4 26B A4B measured
LMArena Text: expertNot measured1447Only Gemma 4 26B A4B measured
LMArena Text: hard prompts in EnglishNot measured1448Only Gemma 4 26B A4B measured
LMArena Vision: diagramsNot measured1264Only Gemma 4 26B A4B measured
LMArena Vision: homeworkNot measured1293Only Gemma 4 26B A4B measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
OTIS Mock AIMENot measured82.2%Only Gemma 4 26B A4B measured
LMArena Text: mathNot measured1470Only Gemma 4 26B A4B measured
LMArena Text: mathematical workNot measured1475Only Gemma 4 26B A4B measured
Neither model has a result on the other 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
LMArena Text: scienceNot measured1446Only Gemma 4 26B A4B measured
LMArena Text: medicine and healthcareNot measured1428Only Gemma 4 26B A4B measured
LMArena Text: legal and governmentNot measured1457Only Gemma 4 26B A4B measured
LMArena Text: business and financeNot measured1429Only Gemma 4 26B A4B measured
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
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 index25 boards, none shared
General benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
IFBenchNot measured72.4%Only Gemma 4 26B A4B measured
Long context reasoning (AA-LCR)Not measured65.7%Only Gemma 4 26B A4B measured
DTBenchNot measured74.9%Only Gemma 4 26B A4B measured
LMCANot measured29.7%Only Gemma 4 26B A4B measured
LMArena TextNot measured1434Only Gemma 4 26B A4B measured
LMArena Text: instruction followingNot measured1420Only Gemma 4 26B A4B measured
LMArena Text: creative writingNot measured1400Only Gemma 4 26B A4B measured
LMArena VisionNot measured1260Only Gemma 4 26B A4B measured
LMArena Text: EnglishNot measured1444Only Gemma 4 26B A4B measured
LMArena Text: non-EnglishNot measured1421Only Gemma 4 26B A4B measured
LMArena Text: ChineseNot measured1495Only Gemma 4 26B A4B measured
LMArena Text: FrenchNot measured1460Only Gemma 4 26B A4B measured
LMArena Text: SpanishNot measured1415Only Gemma 4 26B A4B measured
LMArena Text: RussianNot measured1434Only Gemma 4 26B A4B measured
LMArena Text: multi-turnNot measured1441Only Gemma 4 26B A4B measured
LMArena Text: longer queriesNot measured1427Only Gemma 4 26B A4B measured
LMArena Text: writing and languageNot measured1405Only Gemma 4 26B A4B measured
LMArena Text: entertainment and mediaNot measured1403Only Gemma 4 26B A4B measured
LMArena Vision: EnglishNot measured1256Only Gemma 4 26B A4B measured
LMArena Vision: ChineseNot measured1312Only Gemma 4 26B A4B measured
LMArena Vision: reading textNot measured1268Only Gemma 4 26B A4B measured
LMArena Vision: humorNot measured1272Only Gemma 4 26B A4B measured
LMArena Vision: captioningNot measured1297Only Gemma 4 26B A4B measured
LMArena Vision: recognizing thingsNot measured1191Only Gemma 4 26B A4B measured
LMArena Vision: creative writingNot measured1256Only Gemma 4 26B A4B measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Codestral 2508 and Gemma 4 26B A4B
BenchmarkCodestral 2508Gemma 4 26B A4BLeader
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
Gemma 4 26B A4B$0.0004Fits in one request

Gemma 4 26B A4B costs less

Repository review

50K input + 3K output tokens

Codestral 2508$0.018Fits in one request
Gemma 4 26B A4B$0.0093Fits in one request

Gemma 4 26B A4B costs less

Agent loop

200K input + 10K output tokens

Codestral 2508$0.069Fits in one request
Gemma 4 26B A4B$0.036Fits in one request

Gemma 4 26B A4B 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 Gemma 4 26B A4B
SpecificationMistral Codestral 2508Google Gemma 4 26B A4B
MakerMistral AIGoogle
WeightsNo public weights listedOpen weights
ReleasedAugust 1, 2025April 3, 2026
Context window256K262K
Input $/Mtok$0.30$0.15
Output $/Mtok$0.90$0.60
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Codestral 2508 better than Gemma 4 26B A4B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Codestral 2508 has the edge where the benchmark that matters is ALE-Bench, where it leads.

Which is cheaper, Codestral 2508 or Gemma 4 26B A4B?

Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; Gemma 4 26B A4B costs $0.15 and $0.60. Cost per solved task is known for neither of them.

Which has the bigger context window, Codestral 2508 or Gemma 4 26B A4B?

Gemma 4 26B A4B, with 262K tokens against 256K.

How many benchmarks is the Codestral 2508 vs Gemma 4 26B A4B comparison based on?

1 benchmarks have a result for both models as of October 21, 2026. Codestral 2508's coding index rests on 0 independent benchmarks and Gemma 4 26B A4B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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