DeepSeek V3 vs DeepSeek V3.1
DeepSeek V3 costs 1.6x less per output token than DeepSeek V3.1 ($0.9594 vs $1.50 per million). Updated October 21, 2026; 9 benchmarks have a result for both.
DeepSeek V3 or DeepSeek V3.1: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3 for output tokens 1.6x cheaper ($0.9594 vs $1.50 per million) and work measured by Design Arena: websites or Design Arena: game dev, where it leads.
- Shared results
- 9
- DeepSeek V3 only
- 4
- DeepSeek V3.1 only
- 1
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only DeepSeek V3.1 has a AA Intelligence Index result, 13.7.
Directional only
Web design
Design Arena: websites
DeepSeek V3.1
DeepSeek V3.1 leads, 1123 against 1120.
Same board, both measured
Long documents
Listed context window
No call
Both take 164K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3
DeepSeek V3 $0.0008, DeepSeek V3.1 $0.0013 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 not benchmarked, DeepSeek V3.1 not benchmarked.
- Widest category
- General, 14.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- DTBench: DeepSeek V3 62.7% against DeepSeek V3.1 82.7%, 20.0 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 $0.9594 against DeepSeek V3.1 $1.50 per million output tokens, 1.6x apart.
- Context window
- Both take 164K tokens.
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 | DeepSeek V3 | Bars | DeepSeek V3.1 | Ties |
|---|---|---|---|---|
| Web design | 3 | 4 | ||
| General | 0 | 2 | ||
| All shared boards | 3 | 6 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards, none shared
| Benchmark | DeepSeek V3 | DeepSeek V3.1 | Leader |
|---|---|---|---|
| Aider polyglot | 70.2% | Not measured | Only DeepSeek V3 measured |
| SWE-bench Lite | 30.7% | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V3 | DeepSeek V3.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 13.7 | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 | DeepSeek V3.1 | 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 | DeepSeek V3 | DeepSeek V3.1 | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | 71.2% | Not measured | 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 | DeepSeek V3 | DeepSeek V3.1 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 48.9% | Not measured | 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 | DeepSeek V3 | DeepSeek V3.1 | Leader |
|---|---|---|---|
| Neither model has a result on 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index34
| Benchmark | DeepSeek V3 | DeepSeek V3.1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1120 | 1123 | DeepSeek V3.1 |
| Design Arena: UI components | 1093 | 1085 | DeepSeek V3 |
| Design Arena: game dev | 1053 | 1084 | DeepSeek V3.1 |
| Design Arena: data viz | 1089 | 1095 | DeepSeek V3.1 |
| Design Arena: 3D | 1087 | 1077 | DeepSeek V3 |
| Design Arena: all code categories | 1108 | 1112 | DeepSeek V3.1 |
| Design Arena: SVG | 976 | 967 | DeepSeek V3 |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 | DeepSeek V3.1 | 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
DeepSeek V3 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 | DeepSeek V3 | DeepSeek V3.1 |
|---|---|---|
| Maker | DeepSeek | DeepSeek |
| Weights | Open weights | Open weights |
| Released | December 26, 2024 | August 21, 2025 |
| Context window | 164K | 164K |
| Input $/Mtok | $0.2887 | $0.55 |
| Output $/Mtok | $0.9594 | $1.50 |
| 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 DeepSeek V3 better than DeepSeek V3.1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 for output tokens 1.6x cheaper ($0.9594 vs $1.50 per million) and work measured by Design Arena: websites or Design Arena: game dev, where it leads.
Which is cheaper, DeepSeek V3 or DeepSeek V3.1?
DeepSeek V3 costs $0.2887 per million input tokens and $0.9594 per million output tokens; DeepSeek V3.1 costs $0.55 and $1.50. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 or DeepSeek V3.1?
Neither: both take 164K tokens.
How many benchmarks is the DeepSeek V3 vs DeepSeek V3.1 comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3's coding index rests on 0 independent benchmarks and DeepSeek V3.1's on 0. Where only one model has a result, the page says so instead of naming a winner.