Seed-2.0-Code vs DeepSeek V4 Pro 0423
Updated October 21, 2026. No benchmark has tested both models yet. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- No data
- Output $/M
- $3.00
- Coding
- 38.7
- Overall
- 30.4
- Output $/M
- $2.716
Decision reading
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Seed-2.0-Code has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Seed-2.0-Code has none yet; DeepSeek V4 Pro 0423 on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI). Compare them on price and context instead.
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 Pro 0423 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only DeepSeek V4 Pro 0423 has a AA Intelligence Index result, 30.4.
Directional only
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Pro 0423 has a AA Agentic Index result, 26.3.
Directional only
Reasoning
GPQA Diamond
No call
Only DeepSeek V4 Pro 0423 has a GPQA Diamond result, 89.4%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V4 Pro 0423 has a MMLU Pro result, 87.3%.
Directional only
Web design
Design Arena: websites
No call
Only DeepSeek V4 Pro 0423 has a Design Arena: websites result, 1235.
Directional only
Long documents
Listed context window
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Seed-2.0-Code
Seed-2.0-Code $0.0020, DeepSeek V4 Pro 0423 $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Pro 0423 has the number, $0.57.
Directional only
At a glance
- Coding index
- Seed-2.0-Code not benchmarked, DeepSeek V4 Pro 0423 38.7 from 5 benchmarks.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Seed-2.0-Code $3.00 against DeepSeek V4 Pro 0423 $2.716 per million output tokens, 1.1x apart.
- Context window
- Seed-2.0-Code takes 262K tokens, DeepSeek V4 Pro 0423 1.05M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index17 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1447 | Only DeepSeek V4 Pro 0423 measured |
| AA Coding Index | Not measured | 59.4 | Only DeepSeek V4 Pro 0423 measured |
| LiveCodeBench (Vals AI) | Not measured | 87.5% | Only DeepSeek V4 Pro 0423 measured |
| SWE-bench Verified (Vals AI) | Not measured | 77.4% | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 11.1% | Only DeepSeek V4 Pro 0423 measured |
| Vibe Code Bench (Vals AI) | Not measured | 49.9% | Only DeepSeek V4 Pro 0423 measured |
| Code migration (Vals AI) | Not measured | 26.2% | Only DeepSeek V4 Pro 0423 measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 50.2% | Only DeepSeek V4 Pro 0423 measured |
| SkillsBench (Vals AI) | Not measured | 51.3% | Only DeepSeek V4 Pro 0423 measured |
| FrontierCode | Not measured | 17.6% | Only DeepSeek V4 Pro 0423 measured |
| WeirdML | Not measured | 48.9% | Only DeepSeek V4 Pro 0423 measured |
| ALE-Bench | Not measured | 1006.1 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: coding | Not measured | 1470 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: software and IT | Not measured | 1469 | Only DeepSeek V4 Pro 0423 measured |
| LMArena WebDev: React | Not measured | 1441 | Only DeepSeek V4 Pro 0423 measured |
| LMArena WebDev: HTML | Not measured | 1435 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 30.4 | Only DeepSeek V4 Pro 0423 measured |
| Epoch Capabilities Index | Not measured | 149.1 | Only DeepSeek V4 Pro 0423 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 26.3 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building web apps | Not measured | 1000 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building full-stack apps | Not measured | 948 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building Godot games | Not measured | 1059 | Only DeepSeek V4 Pro 0423 measured |
| Finance Agent (Vals AI) | Not measured | 44.1% | Only DeepSeek V4 Pro 0423 measured |
| Tax Agent Bench (Vals AI) | Not measured | 25.2% | Only DeepSeek V4 Pro 0423 measured |
| Legal Research Bench (Vals AI) | Not measured | 23.1% | Only DeepSeek V4 Pro 0423 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 51.6% | Only DeepSeek V4 Pro 0423 measured |
| Vending-Bench 2 | Not measured | $3,285 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 89.4% | Only DeepSeek V4 Pro 0423 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only DeepSeek V4 Pro 0423 measured |
| Chess puzzles | Not measured | 19.0% | Only DeepSeek V4 Pro 0423 measured |
| Mystery game puzzles | Not measured | 17.0% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts | Not measured | 1461 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: expert | Not measured | 1463 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts in English | Not measured | 1466 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 96.7% | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 45.3% | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tier 4 | Not measured | 2.4% | Only DeepSeek V4 Pro 0423 measured |
| ProofBench | Not measured | 16.0% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: math | Not measured | 1443 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: mathematical work | Not measured | 1455 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 87.3% | Only DeepSeek V4 Pro 0423 measured |
| LegalBench (Vals AI) | Not measured | 80.3% | Only DeepSeek V4 Pro 0423 measured |
| CaseLaw (Vals AI) | Not measured | 59.4% | Only DeepSeek V4 Pro 0423 measured |
| CorpFin (Vals AI) | Not measured | 61.4% | Only DeepSeek V4 Pro 0423 measured |
| TaxEval (Vals AI) | Not measured | 72.1% | Only DeepSeek V4 Pro 0423 measured |
| MedCode (Vals AI) | Not measured | 40.5% | Only DeepSeek V4 Pro 0423 measured |
| SimpleQA Verified | Not measured | 47.0% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: science | Not measured | 1470 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: medicine and healthcare | Not measured | 1466 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: legal and government | Not measured | 1464 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: business and finance | Not measured | 1443 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1235 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: UI components | Not measured | 1222 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: game dev | Not measured | 1229 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: data viz | Not measured | 1202 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: 3D | Not measured | 1254 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: all code categories | Not measured | 1240 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: SVG | Not measured | 1140 | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: ASCII art | Not measured | 1148 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index23 boards measured
| Benchmark | Seed-2.0-Code | DeepSeek V4 Pro 0423 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 62.9% | Only DeepSeek V4 Pro 0423 measured |
| MedScribe (Vals AI) | Not measured | 75.1% | Only DeepSeek V4 Pro 0423 measured |
| DTBench | Not measured | 90.7% | Only DeepSeek V4 Pro 0423 measured |
| LMCA | Not measured | 41.2% | Only DeepSeek V4 Pro 0423 measured |
| Surface Evolver Bench | Not measured | 40.0% | Only DeepSeek V4 Pro 0423 measured |
| CL-bench Life | Not measured | 13.5% | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text | Not measured | 1451 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: instruction following | Not measured | 1445 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: creative writing | Not measured | 1446 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: English | Not measured | 1459 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: non-English | Not measured | 1439 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Chinese | Not measured | 1481 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: German | Not measured | 1458 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Japanese | Not measured | 1446 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Korean | Not measured | 1409 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: French | Not measured | 1473 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Spanish | Not measured | 1457 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Russian | Not measured | 1453 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Polish | Not measured | 1461 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: multi-turn | Not measured | 1468 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: longer queries | Not measured | 1458 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: writing and language | Not measured | 1447 | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: entertainment and media | Not measured | 1431 | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 23 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
Seed-2.0-Code costs less
Repository review
50K input + 3K output tokens
Seed-2.0-Code costs less
Agent loop
200K input + 10K output tokens
Seed-2.0-Code 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 | ByteDance Seed Seed-2.0-Code | DeepSeek V4 Pro 0423 |
|---|---|---|
| Maker | ByteDance Seed | DeepSeek |
| Weights | No public weights listed | Open weights |
| Released | August 12, 2026 | April 24, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.50 | $1.225 |
| Output $/Mtok | $3.00 | $2.716 |
| Coding index | Not benchmarked | 38.7 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | $0.57 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Seed-2.0-Code better than DeepSeek V4 Pro 0423 for coding?
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Seed-2.0-Code has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Seed-2.0-Code or DeepSeek V4 Pro 0423?
Seed-2.0-Code costs $0.50 per million input tokens and $3.00 per million output tokens; DeepSeek V4 Pro 0423 costs $1.225 and $2.716. Cost per solved task is known for DeepSeek V4 Pro 0423 only.
Which has the bigger context window, Seed-2.0-Code or DeepSeek V4 Pro 0423?
DeepSeek V4 Pro 0423, with 1.05M tokens against 262K.
Has any benchmark tested both Seed-2.0-Code and DeepSeek V4 Pro 0423?
No benchmark has tested both yet. Seed-2.0-Code has none yet; DeepSeek V4 Pro 0423 on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI). Compare them on price and context instead. Data as of October 21, 2026.