DeepSeek V4 Pro 0423 vs Inkling
DeepSeek V4 Pro 0423 leads Inkling on coding, 38.7 to 31.5 on the Vibe Coding Index, and DeepSeek V4 Pro 0423 costs 1.4x less per output token ($2.976 vs $4.05 per million). Updated October 22, 2026; 76 benchmarks have a result for both.
DeepSeek V4 Pro 0423 or Inkling: which to pick
Pick DeepSeek V4 Pro 0423 for coding: it scores 38.7 on the Vibe Coding Index against 31.5 for Inkling, though on 5 benchmarks against 6.
Pick Inkling for work measured by SWE-bench Verified (Vals AI) or Design Arena: agents building web apps, where it leads.
- Shared results
- 76
- DeepSeek V4 Pro 0423 only
- 8
- Inkling only
- 26
- Like-for-like categories
- 8 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
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 scores 38.7 against 31.5.
5 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 30.4 against 25.0.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 26.3 against 22.5.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 89.4% against 87.1%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 87.3% against 86.3%.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 1234 against 1224.
Same board, both measured
General
Vals Index
No call
Only Inkling has a Vals Index result, 29.0%.
Directional only
Long documents
Listed context window
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 takes 1.05M tokens against 524K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 $0.0028, Inkling $0.0030 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 $0.57, Inkling $0.76.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Pro 0423 38.7 from 5 benchmarks, Inkling 31.5 from 6 benchmarks.
- Widest category
- Agentic work, 9.9 points apart on average over 6 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): DeepSeek V4 Pro 0423 49.9% against Inkling 19.2%, 30.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0423 $2.976 against Inkling $4.05 per million output tokens, 1.4x apart.
- Context window
- DeepSeek V4 Pro 0423 takes 1.05M tokens, Inkling 524K.
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 | Inkling | Ties |
|---|---|---|---|---|
| Coding | 15 | 1 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 3 | 3 | ||
| Reasoning | 4 | 2 | ||
| Math | 3 | 3 | ||
| Knowledge | 6 | 4 | ||
| Web design | 8 | 0 | ||
| General | 19 | 2 | ||
| All shared boards | 60 | 15 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index151
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 64.0% | Only Inkling measured |
| LMArena WebDev | 1447 | 1414 | DeepSeek V4 Pro 0423 |
| AA Coding Index | 59.4 | 52.1 | DeepSeek V4 Pro 0423 |
| LiveCodeBench (Vals AI) | 87.5% | 85.5% | DeepSeek V4 Pro 0423 |
| SWE-bench Verified (Vals AI) | 77.4% | 77.6% | Inkling |
| Terminal-Bench 4 (Vals AI) | 11.1% | 0.5% | DeepSeek V4 Pro 0423 |
| Vibe Code Bench (Vals AI) | 49.9% | 19.2% | DeepSeek V4 Pro 0423 |
| Code migration (Vals AI) | 26.2% | 11.8% | DeepSeek V4 Pro 0423 |
| ProgramBench (Vals AI) | 0.0% | 0.0% | Tie |
| IOI (Vals AI) | Not measured | 14.9% | Only Inkling measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | 47.6% | DeepSeek V4 Pro 0423 |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 7.3% | Only Inkling measured |
| SkillsBench (Vals AI) | 51.3% | 26.1% | DeepSeek V4 Pro 0423 |
| CyberBench (Vals AI) | Not measured | 66.8% | Only Inkling measured |
| SciCode | Not measured | 47.0% | Only Inkling measured |
| FrontierCode | 17.6% | 14.0% | DeepSeek V4 Pro 0423 |
| FrontierSWE | Not measured | 4.1% | Only Inkling measured |
| WeirdML | 48.9% | 32.3% | DeepSeek V4 Pro 0423 |
| ALE-Bench | 1006.1 | 946.0 | DeepSeek V4 Pro 0423 |
| LMArena Text: coding | 1470 | 1466 | DeepSeek V4 Pro 0423 |
| LMArena Text: software and IT | 1469 | 1465 | DeepSeek V4 Pro 0423 |
| LMArena WebDev: React | 1441 | 1404 | DeepSeek V4 Pro 0423 |
| LMArena WebDev: HTML | 1435 | 1399 | DeepSeek V4 Pro 0423 |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| AA Intelligence Index | 30.4 | 25.0 | DeepSeek V4 Pro 0423 |
| Epoch Capabilities Index | 149.1 | 148.4 | DeepSeek V4 Pro 0423 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| AA Agentic Index | 26.3 | 22.5 | DeepSeek V4 Pro 0423 |
| Design Arena: agents building web apps | 1000 | 1196 | Inkling |
| 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 |
| LiveBench research | Not measured | 59.9% | Only Inkling measured |
| LiveBench browser | Not measured | 16.0% | Only Inkling measured |
| LiveBench long agentic | Not measured | 14.1% | Only Inkling measured |
| SREBench (Vals AI) | Not measured | 0.0% | Only Inkling measured |
| Finance Agent (Vals AI) | 44.1% | 46.6% | Inkling |
| Tax Agent Bench (Vals AI) | 25.2% | 15.3% | DeepSeek V4 Pro 0423 |
| Legal Research Bench (Vals AI) | 23.1% | 28.4% | Inkling |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 3.8% | Only Inkling measured |
| Excel Modeling Benchmark (Vals AI) | 51.6% | 38.4% | DeepSeek V4 Pro 0423 |
| APEX-Agents | Not measured | 33.8% | Only Inkling measured |
| Vending-Bench 2 | $3,285 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index42
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| GPQA Diamond | 89.4% | 87.1% | DeepSeek V4 Pro 0423 |
| LiveBench reasoning | Not measured | 78.3% | Only Inkling measured |
| MMMU Pro (Vals AI) | Not measured | 78.5% | Only Inkling measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 87.2% | Only Inkling measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 31.9% | Only Inkling measured |
| GPQA Diamond (Epoch AI run) | 90.9% | 88.3% | DeepSeek V4 Pro 0423 |
| ARC-AGI | Not measured | 79.5% | Only Inkling measured |
| ARC-AGI-2 | Not measured | 36.5% | Only Inkling measured |
| SimpleBench | Not measured | 50.0% | Only Inkling measured |
| Chess puzzles | 19.0% | 21.0% | Inkling |
| Mystery game puzzles | 17.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts | 1461 | 1451 | DeepSeek V4 Pro 0423 |
| LMArena Text: expert | 1463 | 1466 | Inkling |
| LMArena Text: hard prompts in English | 1466 | 1448 | DeepSeek V4 Pro 0423 |
| Kagi LLM Benchmark | 53.5% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| OTIS Mock AIME | 96.7% | 88.9% | DeepSeek V4 Pro 0423 |
| FrontierMath, tiers 1 to 3 | 45.3% | 33.3% | DeepSeek V4 Pro 0423 |
| FrontierMath, tier 4 | 2.4% | 4.9% | Inkling |
| ProofBench | 16.0% | 0.0% | DeepSeek V4 Pro 0423 |
| LMArena Text: math | 1443 | 1479 | Inkling |
| LMArena Text: mathematical work | 1455 | 1460 | Inkling |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index64
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| MMLU Pro | 87.3% | 86.3% | DeepSeek V4 Pro 0423 |
| LegalBench (Vals AI) | 80.3% | 83.0% | Inkling |
| CaseLaw (Vals AI) | 59.4% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| CorpFin (Vals AI) | 61.4% | 68.6% | Inkling |
| TaxEval (Vals AI) | 72.1% | 75.3% | Inkling |
| MortgageTax (Vals AI) | Not measured | 64.0% | Only Inkling measured |
| MedCode (Vals AI) | 40.5% | 41.2% | Inkling |
| SimpleQA Verified | 47.0% | 40.3% | DeepSeek V4 Pro 0423 |
| LMArena Text: science | 1470 | 1455 | DeepSeek V4 Pro 0423 |
| LMArena Text: medicine and healthcare | 1466 | 1447 | DeepSeek V4 Pro 0423 |
| LMArena Text: legal and government | 1464 | 1448 | DeepSeek V4 Pro 0423 |
| LMArena Text: business and finance | 1443 | 1438 | 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 index80
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| Design Arena: websites | 1234 | 1224 | DeepSeek V4 Pro 0423 |
| Design Arena: UI components | 1219 | 1198 | DeepSeek V4 Pro 0423 |
| Design Arena: game dev | 1228 | 1165 | DeepSeek V4 Pro 0423 |
| Design Arena: data viz | 1203 | 1156 | DeepSeek V4 Pro 0423 |
| Design Arena: 3D | 1253 | 1160 | DeepSeek V4 Pro 0423 |
| Design Arena: all code categories | 1240 | 1205 | DeepSeek V4 Pro 0423 |
| Design Arena: SVG | 1139 | 1108 | DeepSeek V4 Pro 0423 |
| Design Arena: ASCII art | 1149 | 1089 | DeepSeek V4 Pro 0423 |
| LiveBench design | Not measured | 58.3% | Only Inkling measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index192
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | Leader |
|---|---|---|---|
| Vals Index | Not measured | 29.0% | Only Inkling measured |
| LiveBench data analysis | Not measured | 72.8% | Only Inkling measured |
| Public Benefits Bench (Vals AI) | 62.9% | 58.5% | DeepSeek V4 Pro 0423 |
| SAGE (Vals AI) | Not measured | 36.5% | Only Inkling measured |
| MedScribe (Vals AI) | 75.1% | 85.4% | Inkling |
| Vals Multimodal Index | Not measured | 49.4% | Only Inkling measured |
| Long context reasoning (AA-LCR) | Not measured | 77.3% | Only Inkling measured |
| DTBench | 90.7% | 87.5% | DeepSeek V4 Pro 0423 |
| LMCA | 41.2% | 37.6% | DeepSeek V4 Pro 0423 |
| 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 | 1442 | DeepSeek V4 Pro 0423 |
| LMArena Text: instruction following | 1445 | 1425 | DeepSeek V4 Pro 0423 |
| LMArena Text: creative writing | 1446 | 1390 | DeepSeek V4 Pro 0423 |
| LMArena Text: English | 1459 | 1442 | DeepSeek V4 Pro 0423 |
| LMArena Text: non-English | 1439 | 1434 | DeepSeek V4 Pro 0423 |
| LMArena Text: Chinese | 1481 | 1493 | Inkling |
| LMArena Text: German | 1458 | 1445 | DeepSeek V4 Pro 0423 |
| LMArena Text: Japanese | 1446 | 1429 | DeepSeek V4 Pro 0423 |
| LMArena Text: Korean | 1409 | 1403 | DeepSeek V4 Pro 0423 |
| LMArena Text: French | 1473 | 1455 | DeepSeek V4 Pro 0423 |
| LMArena Text: Spanish | 1457 | 1449 | DeepSeek V4 Pro 0423 |
| LMArena Text: Russian | 1453 | 1430 | DeepSeek V4 Pro 0423 |
| LMArena Text: Polish | 1461 | 1450 | DeepSeek V4 Pro 0423 |
| LMArena Text: multi-turn | 1468 | 1437 | DeepSeek V4 Pro 0423 |
| LMArena Text: longer queries | 1458 | 1435 | DeepSeek V4 Pro 0423 |
| LMArena Text: writing and language | 1447 | 1404 | DeepSeek V4 Pro 0423 |
| LMArena Text: entertainment and media | 1431 | 1394 | DeepSeek V4 Pro 0423 |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Inkling | 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 Pro 0423 costs less
Repository review
50K input + 3K output tokens
Inkling costs less
Agent loop
200K input + 10K output tokens
Inkling 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 | Thinking Machines Inkling |
|---|---|---|
| Maker | DeepSeek | Thinking Machines |
| Weights | Open weights | Open weights |
| Released | April 24, 2026 | July 17, 2026 |
| Context window | 1.05M | 524K |
| Input $/Mtok | $1.358 | $0.975 |
| Output $/Mtok | $2.976 | $4.05 |
| Coding index | 38.7 | 31.5 |
| Independent measurements behind it | 5 | 6 |
| Cost per solved task | $0.57 | $0.76 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0423 better than Inkling for coding?
Pick DeepSeek V4 Pro 0423 for coding: it scores 38.7 on the Vibe Coding Index against 31.5 for Inkling, though on 5 benchmarks against 6. Pick Inkling for work measured by SWE-bench Verified (Vals AI) or Design Arena: agents building web apps, where it leads.
Which is cheaper, DeepSeek V4 Pro 0423 or Inkling?
DeepSeek V4 Pro 0423 costs $1.358 per million input tokens and $2.976 per million output tokens; Inkling costs $0.975 and $4.05. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0423 costs $0.57 and Inkling $0.76.
Which has the bigger context window, DeepSeek V4 Pro 0423 or Inkling?
DeepSeek V4 Pro 0423, with 1.05M tokens against 524K.
How many benchmarks is the DeepSeek V4 Pro 0423 vs Inkling comparison based on?
76 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0423's coding index rests on 5 independent benchmarks and Inkling's on 6. Where only one model has a result, the page says so instead of naming a winner.