DeepSeek V4 Pro 0423 vs Hy3
Updated October 21, 2026. 40 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Hy3 for coding: it scores 43.9 on the Vibe Coding Index against 35.3 for DeepSeek V4 Pro 0423.
Pick DeepSeek V4 Pro 0423 when the context window is larger, 1.05M against 262K tokens, or when what matters is ALE-Bench or LMArena Text: coding, where it leads.
- Shared results
- 40
- DeepSeek V4 Pro 0423 only
- 43
- Hy3 only
- 4
- Like-for-like categories
- 6 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
Hy3
Hy3 scores 43.9 against 35.3.
One benchmark behind each score
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
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 1235 against 1230.
Same board, both measured
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
Hy3
DeepSeek V4 Pro 0423 $0.0019, Hy3 $0.0004 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
- DeepSeek V4 Pro 0423 35.3 from 1 benchmark, Hy3 43.9 from 1 benchmark.
- Widest category
- Coding, 6.0 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: DeepSeek V4 Pro 0423 1441 against Hy3 1511, 11.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0423 $1.9105 against Hy3 $0.528 per million output tokens, 3.6x apart.
- Context window
- DeepSeek V4 Pro 0423 takes 1.05M tokens, Hy3 262K.
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 V4 Pro 0423 | Bars | Hy3 | Ties |
|---|---|---|---|---|
| Coding | 3 | 3 | ||
| Reasoning | 3 | 0 | ||
| Math | 0 | 2 | ||
| Knowledge | 4 | 0 | ||
| Web design | 6 | 2 | ||
| General | 15 | 2 | ||
| All shared boards | 31 | 9 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index33
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| LMArena WebDev | 1447 | 1507 | Hy3 |
| AA Coding Index | 59.4 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LiveCodeBench (Vals AI) | 87.5% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| SWE-bench Verified (Vals AI) | 77.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 4 (Vals AI) | 11.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Vibe Code Bench (Vals AI) | 49.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Code migration (Vals AI) | 26.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| SkillsBench (Vals AI) | 51.3% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| SciCode | Not measured | 48.6% | Only Hy3 measured |
| FrontierCode | 17.6% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| WeirdML | 48.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| ALE-Bench | 1006.1 | 838.6 | DeepSeek V4 Pro 0423 |
| LMArena Text: coding | 1470 | 1466 | DeepSeek V4 Pro 0423 |
| LMArena Text: software and IT | 1469 | 1463 | DeepSeek V4 Pro 0423 |
| LMArena WebDev: React | 1441 | 1511 | Hy3 |
| LMArena WebDev: HTML | 1435 | 1487 | Hy3 |
| Neither model has a result on the other 20 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 30.4 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Epoch Capabilities Index | 149.1 | Not measured | Only DeepSeek V4 Pro 0423 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| AA Agentic Index | 26.3 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building web apps | 1000 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building full-stack apps | 948 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: agents building Godot games | 1059 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Finance Agent (Vals AI) | 44.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Tax Agent Bench (Vals AI) | 25.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Legal Research Bench (Vals AI) | 23.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Excel Modeling Benchmark (Vals AI) | 51.6% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Vending-Bench 2 | $3,285 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond | 89.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.7% | Only Hy3 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 33.5% | Only Hy3 measured |
| GPQA Diamond (Epoch AI run) | 90.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Chess puzzles | 19.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Mystery game puzzles | 17.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts | 1461 | 1447 | DeepSeek V4 Pro 0423 |
| LMArena Text: expert | 1463 | 1461 | DeepSeek V4 Pro 0423 |
| LMArena Text: hard prompts in English | 1466 | 1455 | DeepSeek V4 Pro 0423 |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 96.7% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tiers 1 to 3 | 45.3% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| FrontierMath, tier 4 | 2.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| ProofBench | 16.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: math | 1443 | 1473 | Hy3 |
| LMArena Text: mathematical work | 1455 | 1482 | Hy3 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| MMLU Pro | 87.3% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LegalBench (Vals AI) | 80.3% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| CaseLaw (Vals AI) | 59.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| CorpFin (Vals AI) | 61.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| TaxEval (Vals AI) | 72.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| MedCode (Vals AI) | 40.5% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| SimpleQA Verified | 47.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: science | 1470 | 1457 | DeepSeek V4 Pro 0423 |
| LMArena Text: medicine and healthcare | 1466 | 1452 | DeepSeek V4 Pro 0423 |
| LMArena Text: legal and government | 1464 | 1422 | DeepSeek V4 Pro 0423 |
| LMArena Text: business and finance | 1443 | 1424 | DeepSeek V4 Pro 0423 |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index62
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1235 | 1230 | DeepSeek V4 Pro 0423 |
| Design Arena: UI components | 1221 | 1205 | DeepSeek V4 Pro 0423 |
| Design Arena: game dev | 1229 | 1208 | DeepSeek V4 Pro 0423 |
| Design Arena: data viz | 1203 | 1163 | DeepSeek V4 Pro 0423 |
| Design Arena: 3D | 1254 | 1233 | DeepSeek V4 Pro 0423 |
| Design Arena: all code categories | 1240 | 1227 | DeepSeek V4 Pro 0423 |
| Design Arena: SVG | 1139 | 1199 | Hy3 |
| Design Arena: ASCII art | 1148 | 1157 | Hy3 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index152
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 62.9% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| MedScribe (Vals AI) | 75.1% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Long context reasoning (AA-LCR) | Not measured | 79.0% | Only Hy3 measured |
| DTBench | 90.7% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMCA | 41.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Surface Evolver Bench | 40.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| CL-bench Life | 13.5% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text | 1451 | 1438 | DeepSeek V4 Pro 0423 |
| LMArena Text: instruction following | 1445 | 1426 | DeepSeek V4 Pro 0423 |
| LMArena Text: creative writing | 1446 | 1403 | DeepSeek V4 Pro 0423 |
| LMArena Text: English | 1459 | 1448 | DeepSeek V4 Pro 0423 |
| LMArena Text: non-English | 1439 | 1426 | DeepSeek V4 Pro 0423 |
| LMArena Text: Chinese | 1481 | 1485 | Hy3 |
| LMArena Text: German | 1458 | 1449 | DeepSeek V4 Pro 0423 |
| LMArena Text: Japanese | 1446 | 1397 | DeepSeek V4 Pro 0423 |
| LMArena Text: Korean | 1409 | 1396 | DeepSeek V4 Pro 0423 |
| LMArena Text: French | 1473 | 1456 | DeepSeek V4 Pro 0423 |
| LMArena Text: Spanish | 1457 | 1457 | Hy3 |
| LMArena Text: Russian | 1453 | 1432 | DeepSeek V4 Pro 0423 |
| LMArena Text: Polish | 1461 | 1447 | DeepSeek V4 Pro 0423 |
| LMArena Text: multi-turn | 1468 | 1436 | DeepSeek V4 Pro 0423 |
| LMArena Text: longer queries | 1458 | 1442 | DeepSeek V4 Pro 0423 |
| LMArena Text: writing and language | 1447 | 1414 | DeepSeek V4 Pro 0423 |
| LMArena Text: entertainment and media | 1431 | 1400 | DeepSeek V4 Pro 0423 |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Hy3 | 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
Hy3 costs less
Repository review
50K input + 3K output tokens
Hy3 costs less
Agent loop
200K input + 10K output tokens
Hy3 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 V4 Pro 0423 | Tencent Hy3 |
|---|---|---|
| Maker | DeepSeek | Tencent |
| Weights | Open weights | Open weights |
| Released | April 24, 2026 | July 6, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.9553 | $0.132 |
| Output $/Mtok | $1.9105 | $0.528 |
| Coding index | 35.3 | 43.9 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.57 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0423 better than Hy3 for coding?
Pick Hy3 for coding: it scores 43.9 on the Vibe Coding Index against 35.3 for DeepSeek V4 Pro 0423. Pick DeepSeek V4 Pro 0423 when the context window is larger, 1.05M against 262K tokens, or when what matters is ALE-Bench or LMArena Text: coding, where it leads.
Which is cheaper, DeepSeek V4 Pro 0423 or Hy3?
DeepSeek V4 Pro 0423 costs $0.9553 per million input tokens and $1.9105 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for DeepSeek V4 Pro 0423 only.
Which has the bigger context window, DeepSeek V4 Pro 0423 or Hy3?
DeepSeek V4 Pro 0423, with 1.05M tokens against 262K.
How many benchmarks is the DeepSeek V4 Pro 0423 vs Hy3 comparison based on?
40 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0423's coding index rests on 1 independent benchmark and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.