Codestral 2508 vs GLM 4.5 Air
Updated October 21, 2026. 6 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
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 1.2x less, and where the context window is larger, 256K against 131K tokens.
- Shared results
- 6
- Codestral 2508 only
- 1
- GLM 4.5 Air only
- 41
- 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.
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 GLM 4.5 Air has a AA Intelligence Index result, 11.1.
Directional only
Web design
Design Arena: websites
GLM 4.5 Air
GLM 4.5 Air leads, 1147 against 1013.
Same board, both measured
Long documents
Listed context window
Codestral 2508
Codestral 2508 takes 256K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
Codestral 2508 $0.0008, GLM 4.5 Air $0.0008 per turn.
List prices
At a glance
- Coding index
- Codestral 2508 not benchmarked, GLM 4.5 Air not benchmarked.
- Widest category
- Web design, 16.0 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: data viz: Codestral 2508 1017 against GLM 4.5 Air 1186, 21.1 points apart on a 0 to 100 scale.
- Output price
- Codestral 2508 $0.90 against GLM 4.5 Air $1.10 per million output tokens, 1.2x apart.
- Context window
- Codestral 2508 takes 256K tokens, GLM 4.5 Air 131K.
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.
| Category | Codestral 2508 | Bars | GLM 4.5 Air | Ties |
|---|---|---|---|---|
| Web design | 0 | 6 | ||
| All shared boards | 0 | 6 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
| Benchmark | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 68.4% | Only GLM 4.5 Air measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 20.5% | Only GLM 4.5 Air measured |
| GSO-Bench | Not measured | 2.9% | Only GLM 4.5 Air measured |
| ALE-Bench | 137.8 | Not measured | Only Codestral 2508 measured |
| LMArena Text: coding | Not measured | 1397 | Only GLM 4.5 Air measured |
| LMArena Text: software and IT | Not measured | 1401 | Only GLM 4.5 Air measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.1 | Only GLM 4.5 Air 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 | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 46.5% | Only GLM 4.5 Air measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 73.3% | Only GLM 4.5 Air measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 7.0% | Only GLM 4.5 Air measured |
| LMArena Text: hard prompts | Not measured | 1379 | Only GLM 4.5 Air measured |
| LMArena Text: expert | Not measured | 1370 | Only GLM 4.5 Air measured |
| LMArena Text: hard prompts in English | Not measured | 1388 | Only GLM 4.5 Air measured |
| 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
| Benchmark | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 80.7 | Only GLM 4.5 Air measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 80.7% | Only GLM 4.5 Air measured |
| LMArena Text: math | Not measured | 1396 | Only GLM 4.5 Air measured |
| LMArena Text: mathematical work | Not measured | 1396 | Only GLM 4.5 Air 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
| Benchmark | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 81.5% | Only GLM 4.5 Air measured |
| LMArena Text: science | Not measured | 1407 | Only GLM 4.5 Air measured |
| LMArena Text: medicine and healthcare | Not measured | 1402 | Only GLM 4.5 Air measured |
| LMArena Text: legal and government | Not measured | 1382 | Only GLM 4.5 Air measured |
| LMArena Text: business and finance | Not measured | 1371 | Only GLM 4.5 Air measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| Design Arena: websites | 1013 | 1147 | GLM 4.5 Air |
| Design Arena: UI components | 1017 | 1123 | GLM 4.5 Air |
| Design Arena: game dev | 968 | 1094 | GLM 4.5 Air |
| Design Arena: data viz | 1017 | 1186 | GLM 4.5 Air |
| Design Arena: 3D | 1020 | 1122 | GLM 4.5 Air |
| Design Arena: all code categories | 1007 | 1137 | GLM 4.5 Air |
| Design Arena: SVG | Not measured | 1071 | Only GLM 4.5 Air measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
| Benchmark | Codestral 2508 | GLM 4.5 Air | Leader |
|---|---|---|---|
| IFBench | Not measured | 37.6% | Only GLM 4.5 Air measured |
| Long context reasoning (AA-LCR) | Not measured | 46.7% | Only GLM 4.5 Air measured |
| LMArena Text | Not measured | 1384 | Only GLM 4.5 Air measured |
| LMArena Text: instruction following | Not measured | 1354 | Only GLM 4.5 Air measured |
| LMArena Text: creative writing | Not measured | 1343 | Only GLM 4.5 Air measured |
| LMArena Text: English | Not measured | 1397 | Only GLM 4.5 Air measured |
| LMArena Text: non-English | Not measured | 1366 | Only GLM 4.5 Air measured |
| LMArena Text: Chinese | Not measured | 1426 | Only GLM 4.5 Air measured |
| LMArena Text: German | Not measured | 1377 | Only GLM 4.5 Air measured |
| LMArena Text: Japanese | Not measured | 1348 | Only GLM 4.5 Air measured |
| LMArena Text: Korean | Not measured | 1308 | Only GLM 4.5 Air measured |
| LMArena Text: French | Not measured | 1400 | Only GLM 4.5 Air measured |
| LMArena Text: Spanish | Not measured | 1385 | Only GLM 4.5 Air measured |
| LMArena Text: Russian | Not measured | 1373 | Only GLM 4.5 Air measured |
| LMArena Text: Polish | Not measured | 1368 | Only GLM 4.5 Air measured |
| LMArena Text: multi-turn | Not measured | 1371 | Only GLM 4.5 Air measured |
| LMArena Text: longer queries | Not measured | 1366 | Only GLM 4.5 Air measured |
| LMArena Text: writing and language | Not measured | 1354 | Only GLM 4.5 Air measured |
| LMArena Text: entertainment and media | Not measured | 1339 | Only GLM 4.5 Air measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | GLM 4.5 Air | 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
Same cost
Repository review
50K input + 3K output tokens
GLM 4.5 Air costs less
Agent loop
200K input + 10K output tokens
GLM 4.5 Air 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 Codestral 2508 | Z.ai GLM 4.5 Air |
|---|---|---|
| Maker | Mistral AI | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | August 1, 2025 | July 25, 2025 |
| Context window | 256K | 131K |
| Input $/Mtok | $0.30 | $0.20 |
| Output $/Mtok | $0.90 | $1.10 |
| 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 Codestral 2508 better than GLM 4.5 Air 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 1.2x less, and where the context window is larger, 256K against 131K tokens.
Which is cheaper, Codestral 2508 or GLM 4.5 Air?
Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; GLM 4.5 Air costs $0.20 and $1.10. Cost per solved task is known for neither of them.
Which has the bigger context window, Codestral 2508 or GLM 4.5 Air?
Codestral 2508, with 256K tokens against 131K.
How many benchmarks is the Codestral 2508 vs GLM 4.5 Air comparison based on?
6 benchmarks have a result for both models as of October 21, 2026. Codestral 2508's coding index rests on 0 independent benchmarks and GLM 4.5 Air's on 0. Where only one model has a result, the page says so instead of naming a winner.