Codestral 2508 vs GPT-4.1
Updated October 21, 2026. 7 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 8.9x less, and where what matters is ALE-Bench or Design Arena: websites, where it leads.
- Shared results
- 7
- Codestral 2508 only
- 0
- GPT-4.1 only
- 80
- Like-for-like categories
- 2 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 GPT-4.1 has a AA Intelligence Index result, 12.7.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4.1 has a GPQA Diamond result, 65.4%.
Directional only
Math
AIME
No call
Only GPT-4.1 has a AIME result, 39.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 has a MMLU Pro result, 80.5%.
Directional only
Web design
Design Arena: websites
GPT-4.1
GPT-4.1 leads, 1039 against 1013.
Same board, both measured
Long documents
Listed context window
GPT-4.1
GPT-4.1 takes 1.05M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Codestral 2508
Codestral 2508 $0.0008, GPT-4.1 $0.0060 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-4.1 has the number, $0.37.
Directional only
At a glance
- Coding index
- Codestral 2508 not benchmarked, GPT-4.1 not benchmarked.
- Widest category
- Coding, 14.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: 3D: Codestral 2508 1020 against GPT-4.1 850, 21.3 points apart on a 0 to 100 scale.
- Output price
- Codestral 2508 $0.90 against GPT-4.1 $8.00 per million output tokens, 8.9x apart.
- Context window
- Codestral 2508 takes 256K tokens, GPT-4.1 1.05M.
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 | GPT-4.1 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Web design | 2 | 4 | ||
| All shared boards | 2 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 52.4% | Only GPT-4.1 measured |
| SWE-bench Verified | Not measured | 39.6% | Only GPT-4.1 measured |
| SWE-bench Multimodal | Not measured | 31.1% | Only GPT-4.1 measured |
| LiveCodeBench (Vals AI) | Not measured | 54.7% | Only GPT-4.1 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 45.7% | Only GPT-4.1 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 13.6% | Only GPT-4.1 measured |
| WeirdML | Not measured | 39.0% | Only GPT-4.1 measured |
| ALE-Bench | 137.8 | 558.1 | GPT-4.1 |
| LMArena Text: coding | Not measured | 1390 | Only GPT-4.1 measured |
| LMArena Text: software and IT | Not measured | 1391 | Only GPT-4.1 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
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.7 | Only GPT-4.1 measured |
| Epoch Capabilities Index | Not measured | 136.7 | Only GPT-4.1 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 47.1% | Only GPT-4.1 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 65.4% | Only GPT-4.1 measured |
| MMMU Pro (Vals AI) | Not measured | 72.4% | Only GPT-4.1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 66.6% | Only GPT-4.1 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 4.2% | Only GPT-4.1 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 66.9% | Only GPT-4.1 measured |
| ARC-AGI | Not measured | 5.5% | Only GPT-4.1 measured |
| ARC-AGI-2 | Not measured | 0.4% | Only GPT-4.1 measured |
| SimpleBench | Not measured | 27.0% | Only GPT-4.1 measured |
| Chess puzzles | Not measured | 3.0% | Only GPT-4.1 measured |
| LMArena Text: hard prompts | Not measured | 1384 | Only GPT-4.1 measured |
| LMArena Text: expert | Not measured | 1364 | Only GPT-4.1 measured |
| LMArena Text: hard prompts in English | Not measured | 1393 | Only GPT-4.1 measured |
| LMArena Vision: diagrams | Not measured | 1215 | Only GPT-4.1 measured |
| LMArena Vision: homework | Not measured | 1248 | Only GPT-4.1 measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| AIME | Not measured | 39.6% | Only GPT-4.1 measured |
| MATH 500 (Vals AI) | Not measured | 87.2% | Only GPT-4.1 measured |
| MGSM (Vals AI) | Not measured | 87.7% | Only GPT-4.1 measured |
| AA Math Index | Not measured | 34.7 | Only GPT-4.1 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 34.7% | Only GPT-4.1 measured |
| OTIS Mock AIME | Not measured | 38.3% | Only GPT-4.1 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 6.0% | Only GPT-4.1 measured |
| MATH level 5 | Not measured | 83.0% | Only GPT-4.1 measured |
| LMArena Text: math | Not measured | 1369 | Only GPT-4.1 measured |
| LMArena Text: mathematical work | Not measured | 1360 | Only GPT-4.1 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 80.5% | Only GPT-4.1 measured |
| LegalBench (Vals AI) | Not measured | 83.1% | Only GPT-4.1 measured |
| CaseLaw (Vals AI) | Not measured | 69.9% | Only GPT-4.1 measured |
| CorpFin (Vals AI) | Not measured | 63.0% | Only GPT-4.1 measured |
| TaxEval (Vals AI) | Not measured | 75.1% | Only GPT-4.1 measured |
| MortgageTax (Vals AI) | Not measured | 65.9% | Only GPT-4.1 measured |
| MedQA (Vals AI) | Not measured | 91.2% | Only GPT-4.1 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 80.6% | Only GPT-4.1 measured |
| SimpleQA Verified | Not measured | 31.1% | Only GPT-4.1 measured |
| GeoBench | Not measured | 72.0% | Only GPT-4.1 measured |
| LMArena Text: science | Not measured | 1382 | Only GPT-4.1 measured |
| LMArena Text: medicine and healthcare | Not measured | 1379 | Only GPT-4.1 measured |
| LMArena Text: legal and government | Not measured | 1399 | Only GPT-4.1 measured |
| LMArena Text: business and finance | Not measured | 1369 | Only GPT-4.1 measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1013 | 1039 | GPT-4.1 |
| Design Arena: UI components | 1017 | 1000 | Codestral 2508 |
| Design Arena: game dev | 968 | 1079 | GPT-4.1 |
| Design Arena: data viz | 1017 | 1104 | GPT-4.1 |
| Design Arena: 3D | 1020 | 850 | Codestral 2508 |
| Design Arena: all code categories | 1007 | 1026 | GPT-4.1 |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index30 boards, none shared
| Benchmark | Codestral 2508 | GPT-4.1 | Leader |
|---|---|---|---|
| IFBench | Not measured | 43.0% | Only GPT-4.1 measured |
| Long context reasoning (AA-LCR) | Not measured | 68.3% | Only GPT-4.1 measured |
| DTBench | Not measured | 68.3% | Only GPT-4.1 measured |
| LMCA | Not measured | 25.6% | Only GPT-4.1 measured |
| Fiction.LiveBench | Not measured | 63.9% | Only GPT-4.1 measured |
| LMArena Text | Not measured | 1383 | Only GPT-4.1 measured |
| LMArena Text: instruction following | Not measured | 1367 | Only GPT-4.1 measured |
| LMArena Text: creative writing | Not measured | 1363 | Only GPT-4.1 measured |
| LMArena Vision | Not measured | 1210 | Only GPT-4.1 measured |
| LMArena Text: English | Not measured | 1392 | Only GPT-4.1 measured |
| LMArena Text: non-English | Not measured | 1370 | Only GPT-4.1 measured |
| LMArena Text: Chinese | Not measured | 1382 | Only GPT-4.1 measured |
| LMArena Text: German | Not measured | 1381 | Only GPT-4.1 measured |
| LMArena Text: Japanese | Not measured | 1319 | Only GPT-4.1 measured |
| LMArena Text: Korean | Not measured | 1338 | Only GPT-4.1 measured |
| LMArena Text: French | Not measured | 1382 | Only GPT-4.1 measured |
| LMArena Text: Spanish | Not measured | 1376 | Only GPT-4.1 measured |
| LMArena Text: Russian | Not measured | 1377 | Only GPT-4.1 measured |
| LMArena Text: Polish | Not measured | 1389 | Only GPT-4.1 measured |
| LMArena Text: multi-turn | Not measured | 1397 | Only GPT-4.1 measured |
| LMArena Text: longer queries | Not measured | 1385 | Only GPT-4.1 measured |
| LMArena Text: writing and language | Not measured | 1371 | Only GPT-4.1 measured |
| LMArena Text: entertainment and media | Not measured | 1365 | Only GPT-4.1 measured |
| LMArena Vision: English | Not measured | 1209 | Only GPT-4.1 measured |
| LMArena Vision: Chinese | Not measured | 1226 | Only GPT-4.1 measured |
| LMArena Vision: reading text | Not measured | 1218 | Only GPT-4.1 measured |
| LMArena Vision: humor | Not measured | 1196 | Only GPT-4.1 measured |
| LMArena Vision: captioning | Not measured | 1207 | Only GPT-4.1 measured |
| LMArena Vision: recognizing things | Not measured | 1208 | Only GPT-4.1 measured |
| LMArena Vision: creative writing | Not measured | 1210 | Only GPT-4.1 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | GPT-4.1 | 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
Codestral 2508 costs less
Repository review
50K input + 3K output tokens
Codestral 2508 costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | Mistral Codestral 2508 | OpenAI GPT-4.1 |
|---|---|---|
| Maker | Mistral AI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 1, 2025 | April 14, 2025 |
| Context window | 256K | 1.05M |
| Input $/Mtok | $0.30 | $2.00 |
| Output $/Mtok | $0.90 | $8.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | $0.37 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Codestral 2508 better than GPT-4.1 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 8.9x less, and where what matters is ALE-Bench or Design Arena: websites, where it leads.
Which is cheaper, Codestral 2508 or GPT-4.1?
Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; GPT-4.1 costs $2.00 and $8.00. Cost per solved task is known for GPT-4.1 only.
Which has the bigger context window, Codestral 2508 or GPT-4.1?
GPT-4.1, with 1.05M tokens against 256K.
How many benchmarks is the Codestral 2508 vs GPT-4.1 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 GPT-4.1's on 0. Where only one model has a result, the page says so instead of naming a winner.