DeepSeek V3 vs GPT-4o
Updated October 21, 2026. 9 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick DeepSeek V3 for coding: it scores 70.2 on the Vibe Coding Index against 38.8 for GPT-4o.
Pick GPT-4o when what matters is SWE-bench Lite or DTBench, where it leads.
- Shared results
- 9
- DeepSeek V3 only
- 4
- GPT-4o only
- 17
- Like-for-like categories
- 3 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, four public coding benchmarks
DeepSeek V3
DeepSeek V3 scores 70.2 against 38.8.
One benchmark behind each score
Web design
Design Arena: websites
DeepSeek V3
DeepSeek V3 leads, 1120 against 831.
Same board, both measured
Long documents
Listed context window
DeepSeek V3
DeepSeek V3 takes 164K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3
DeepSeek V3 $0.0008, GPT-4o $0.0075 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 70.2 from 1 benchmark, GPT-4o 38.8 from 1 benchmark.
- Widest category
- Web design, 27.9 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: websites: DeepSeek V3 1120 against GPT-4o 831, 36.1 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 $1.0287 against GPT-4o $10.00 per million output tokens, 9.7x apart.
- Context window
- DeepSeek V3 takes 164K tokens, GPT-4o 128K.
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 | GPT-4o | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Web design | 6 | 0 | ||
| General | 0 | 2 | ||
| All shared boards | 6 | 3 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index01
| Benchmark | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| Aider polyglot | 70.2% | Not measured | Only DeepSeek V3 measured |
| SWE-bench Verified | Not measured | 38.8% | Only GPT-4o measured |
| SWE-bench Lite | 30.7% | 38.0% | GPT-4o |
| SWE-bench (full test set) | Not measured | 18.8% | Only GPT-4o measured |
| SWE-bench Multimodal | Not measured | 30.4% | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 30.9% | Only GPT-4o measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 8.3% | Only GPT-4o measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| Neither model has a result on 2 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 25.1% | Only GPT-4o measured |
| GDPval | Not measured | 9.9% | Only GPT-4o measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 54.3% | Only GPT-4o measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 2.4% | Only GPT-4o measured |
| GPQA Diamond (Epoch AI run) | 71.2% | Not measured | Only DeepSeek V3 measured |
| ARC-AGI | Not measured | 4.5% | Only GPT-4o measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4o 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 | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 6.0 | Only GPT-4o measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 6.0% | Only GPT-4o measured |
| OTIS Mock AIME | 48.9% | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 74.8% | Only GPT-4o measured |
| MMLU | Not measured | 88.1% | Only GPT-4o measured |
| Neither model has a result on the other 15 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| Design Arena: websites | 1120 | 831 | DeepSeek V3 |
| Design Arena: UI components | 1093 | 885 | DeepSeek V3 |
| Design Arena: game dev | 1054 | 906 | DeepSeek V3 |
| Design Arena: data viz | 1089 | 858 | DeepSeek V3 |
| Design Arena: 3D | 1087 | 869 | DeepSeek V3 |
| Design Arena: all code categories | 1108 | 861 | DeepSeek V3 |
| Design Arena: SVG | 976 | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3 | GPT-4o | Leader |
|---|---|---|---|
| IFBench | Not measured | 34.3% | Only GPT-4o measured |
| Long context reasoning (AA-LCR) | Not measured | 49.3% | Only GPT-4o measured |
| DTBench | 62.7% | 64.5% | GPT-4o |
| LMCA | 15.2% | 16.6% | GPT-4o |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 | GPT-4o | 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 | OpenAI GPT-4o |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | December 26, 2024 | May 13, 2024 |
| Context window | 164K | 128K |
| Input $/Mtok | $0.2574 | $2.50 |
| Output $/Mtok | $1.0287 | $10.00 |
| Coding index | 70.2 | 38.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 better than GPT-4o for coding?
Pick DeepSeek V3 for coding: it scores 70.2 on the Vibe Coding Index against 38.8 for GPT-4o. Pick GPT-4o when what matters is SWE-bench Lite or DTBench, where it leads.
Which is cheaper, DeepSeek V3 or GPT-4o?
DeepSeek V3 costs $0.2574 per million input tokens and $1.0287 per million output tokens; GPT-4o costs $2.50 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 or GPT-4o?
DeepSeek V3, with 164K tokens against 128K.
How many benchmarks is the DeepSeek V3 vs GPT-4o comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3's coding index rests on 1 independent benchmark and GPT-4o's on 1. Where only one model has a result, the page says so instead of naming a winner.