Codestral 2508 vs DeepSeek V3
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 1.1x less, and where the context window is larger, 256K against 164K tokens.
- Shared results
- 6
- Codestral 2508 only
- 1
- DeepSeek V3 only
- 7
- 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
Web design
Design Arena: websites
DeepSeek V3
DeepSeek V3 leads, 1120 against 1013.
Same board, both measured
Long documents
Listed context window
Codestral 2508
Codestral 2508 takes 256K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Codestral 2508
Codestral 2508 $0.0008, DeepSeek V3 $0.0008 per turn.
List prices
At a glance
- Coding index
- Codestral 2508 not benchmarked, DeepSeek V3 not benchmarked.
- Widest category
- Web design, 10.6 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: websites: Codestral 2508 1013 against DeepSeek V3 1120, 13.4 points apart on a 0 to 100 scale.
- Output price
- Codestral 2508 $0.90 against DeepSeek V3 $0.9594 per million output tokens, 1.1x apart.
- Context window
- Codestral 2508 takes 256K tokens, DeepSeek V3 164K.
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 | DeepSeek V3 | Ties |
|---|---|---|---|---|
| Web design | 0 | 6 | ||
| All shared boards | 0 | 6 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V3 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 70.2% | Only DeepSeek V3 measured |
| SWE-bench Lite | Not measured | 30.7% | Only DeepSeek V3 measured |
| ALE-Bench | 137.8 | Not measured | Only Codestral 2508 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V3 | Leader |
|---|---|---|---|
| Neither model has a result on 2 boards here | |||
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V3 | Leader |
|---|---|---|---|
| Neither model has a result on 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Codestral 2508 | DeepSeek V3 | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | Not measured | 71.2% | Only DeepSeek V3 measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Codestral 2508 | DeepSeek V3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 48.9% | Only DeepSeek V3 measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V3 | Leader |
|---|---|---|---|
| Neither model has a result on 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Codestral 2508 | DeepSeek V3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1013 | 1120 | DeepSeek V3 |
| Design Arena: UI components | 1017 | 1093 | DeepSeek V3 |
| Design Arena: game dev | 968 | 1053 | DeepSeek V3 |
| Design Arena: data viz | 1017 | 1089 | DeepSeek V3 |
| Design Arena: 3D | 1020 | 1087 | DeepSeek V3 |
| Design Arena: all code categories | 1007 | 1108 | DeepSeek V3 |
| Design Arena: SVG | Not measured | 977 | Only DeepSeek V3 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V3 | 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
DeepSeek V3 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3 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 | DeepSeek V3 |
|---|---|---|
| Maker | Mistral AI | DeepSeek |
| Weights | No public weights listed | Open weights |
| Released | August 1, 2025 | December 26, 2024 |
| Context window | 256K | 164K |
| Input $/Mtok | $0.30 | $0.2887 |
| Output $/Mtok | $0.90 | $0.9594 |
| 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 DeepSeek V3 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 1.1x less, and where the context window is larger, 256K against 164K tokens.
Which is cheaper, Codestral 2508 or DeepSeek V3?
Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; DeepSeek V3 costs $0.2887 and $0.9594. Cost per solved task is known for neither of them.
Which has the bigger context window, Codestral 2508 or DeepSeek V3?
Codestral 2508, with 256K tokens against 164K.
How many benchmarks is the Codestral 2508 vs DeepSeek V3 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 DeepSeek V3's on 0. Where only one model has a result, the page says so instead of naming a winner.