Codestral 2508 vs DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 costs 1.5x less per output token than Codestral 2508 ($0.60 vs $0.90 per million). Updated October 21, 2026; 7 benchmarks have a result for both.
Codestral 2508 or DeepSeek V4.1 Flash 1017: which to pick
Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 on the Vibe Coding Index; Codestral 2508 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 7
- Codestral 2508 only
- 1
- DeepSeek V4.1 Flash 1017 only
- 32
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only DeepSeek V4.1 Flash 1017 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only DeepSeek V4.1 Flash 1017 has a AA Intelligence Index result, 39.5.
Directional only
Web design
Design Arena: websites
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads, 1312 against 1013.
Same board, both measured
General
Vals Index
No call
Only DeepSeek V4.1 Flash 1017 has a Vals Index result, 61.3%.
Directional only
Long documents
Listed context window
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 takes 1.05M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash 1017
Codestral 2508 $0.0008, DeepSeek V4.1 Flash 1017 $0.0004 per turn.
List prices
At a glance
- Coding index
- Codestral 2508 not benchmarked, DeepSeek V4.1 Flash 1017 70.3 from 4 benchmarks.
- Widest category
- Coding, 49.5 points apart on average over 1 shared benchmark.
- Widest single gap
- ALE-Bench: Codestral 2508 137.8 against DeepSeek V4.1 Flash 1017 1622.0, 49.5 points apart on a 0 to 100 scale.
- Output price
- Codestral 2508 $0.90 against DeepSeek V4.1 Flash 1017 $0.60 per million output tokens, 1.5x apart.
- Context window
- Codestral 2508 takes 256K tokens, DeepSeek V4.1 Flash 1017 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 | DeepSeek V4.1 Flash 1017 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Web design | 0 | 6 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 96.0% | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena WebDev | Not measured | 1664 | Only DeepSeek V4.1 Flash 1017 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.8% | Only DeepSeek V4.1 Flash 1017 measured |
| Vibe Code Bench (Vals AI) | Not measured | 87.7% | Only DeepSeek V4.1 Flash 1017 measured |
| Code migration (Vals AI) | Not measured | 44.2% | Only DeepSeek V4.1 Flash 1017 measured |
| SciCode | Not measured | 55.9% | Only DeepSeek V4.1 Flash 1017 measured |
| ALE-Bench | 137.8 | 1622.0 | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev: React | Not measured | 1667 | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena WebDev: HTML | Not measured | 1687 | Only DeepSeek V4.1 Flash 1017 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
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 39.5 | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | Not measured | 1230 | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench research | Not measured | 79.5% | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench browser | Not measured | 76.0% | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench long agentic | Not measured | 50.9% | Only DeepSeek V4.1 Flash 1017 measured |
| Finance Agent (Vals AI) | Not measured | 57.0% | Only DeepSeek V4.1 Flash 1017 measured |
| Tax Agent Bench (Vals AI) | Not measured | 44.4% | Only DeepSeek V4.1 Flash 1017 measured |
| Legal Research Bench (Vals AI) | Not measured | 45.2% | Only DeepSeek V4.1 Flash 1017 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 14.2% | Only DeepSeek V4.1 Flash 1017 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 61.8% | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 89.1% | Only DeepSeek V4.1 Flash 1017 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 43.3% | Only DeepSeek V4.1 Flash 1017 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 93.2% | Only DeepSeek V4.1 Flash 1017 measured |
| Chess puzzles | Not measured | 46.0% | Only DeepSeek V4.1 Flash 1017 measured |
| Mystery game puzzles | Not measured | 49.0% | Only DeepSeek V4.1 Flash 1017 measured |
| Kagi LLM Benchmark | 32.5% | Not measured | Only Codestral 2508 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 99.4% | Only DeepSeek V4.1 Flash 1017 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 71.2% | Only DeepSeek V4.1 Flash 1017 measured |
| FrontierMath, tier 4 | Not measured | 46.3% | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| SimpleQA Verified | Not measured | 42.5% | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| Design Arena: websites | 1013 | 1312 | DeepSeek V4.1 Flash 1017 |
| Design Arena: UI components | 1017 | 1300 | DeepSeek V4.1 Flash 1017 |
| Design Arena: game dev | 968 | 1362 | DeepSeek V4.1 Flash 1017 |
| Design Arena: data viz | 1017 | 1335 | DeepSeek V4.1 Flash 1017 |
| Design Arena: 3D | 1020 | 1372 | DeepSeek V4.1 Flash 1017 |
| Design Arena: all code categories | 1007 | 1334 | DeepSeek V4.1 Flash 1017 |
| Design Arena: ASCII art | Not measured | 1243 | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench design | Not measured | 83.4% | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 61.3% | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench data analysis | Not measured | 79.5% | Only DeepSeek V4.1 Flash 1017 measured |
| Long context reasoning (AA-LCR) | Not measured | 82.7% | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | DeepSeek V4.1 Flash 1017 | 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
DeepSeek V4.1 Flash 1017 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash 1017 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash 1017 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 V4.1 Flash 1017 |
|---|---|---|
| Maker | Mistral AI | DeepSeek |
| Weights | No public weights listed | Open weights |
| Released | August 1, 2025 | October 17, 2026 |
| Context window | 256K | 1.05M |
| Input $/Mtok | $0.30 | $0.15 |
| Output $/Mtok | $0.90 | $0.60 |
| Coding index | Not benchmarked | 70.3 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Codestral 2508 better than DeepSeek V4.1 Flash 1017 for coding?
Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 on the Vibe Coding Index; Codestral 2508 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Codestral 2508 or DeepSeek V4.1 Flash 1017?
Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; DeepSeek V4.1 Flash 1017 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 DeepSeek V4.1 Flash 1017?
DeepSeek V4.1 Flash 1017, with 1.05M tokens against 256K.
How many benchmarks is the Codestral 2508 vs DeepSeek V4.1 Flash 1017 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 DeepSeek V4.1 Flash 1017's on 4. Where only one model has a result, the page says so instead of naming a winner.