DeepSeek V4 Pro 0423 vs Kimi K2 Thinking
DeepSeek V4 Pro 0423 leads Kimi K2 Thinking on the Artificial Analysis Intelligence Index, 30.4 to 22.0, at about the same output price ($2.716 vs $2.50 per million). Updated October 21, 2026; 13 benchmarks have a result for both.
DeepSeek V4 Pro 0423 or Kimi K2 Thinking: which to pick
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Kimi K2 Thinking has none, so the two cannot be ranked on coding.
Pick Kimi K2 Thinking for output tokens 1.1x cheaper ($2.50 vs $2.716 per million) and work measured by CaseLaw (Vals AI), where it leads.
- Shared results
- 13
- DeepSeek V4 Pro 0423 only
- 71
- Kimi K2 Thinking only
- 17
- Like-for-like categories
- 5 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
Only DeepSeek V4 Pro 0423 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 30.4 against 22.0.
Same board, both measured
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
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 89.4% against 78.5%.
Same board, both measured
Math
AIME
No call
Only Kimi K2 Thinking has a AIME result, 85.4%.
Directional only
Knowledge
MMLU Pro
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 87.3% against 81.1%.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 leads, 1234 against 1113.
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
Kimi K2 Thinking
DeepSeek V4 Pro 0423 $0.0026, Kimi K2 Thinking $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Pro 0423
DeepSeek V4 Pro 0423 $0.57, Kimi K2 Thinking $0.61.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Pro 0423 38.7 from 5 benchmarks, Kimi K2 Thinking not benchmarked.
- Widest category
- Coding, 15.3 points apart on average over 4 shared benchmarks.
- Widest single gap
- LiveCodeBench (Vals AI): DeepSeek V4 Pro 0423 87.5% against Kimi K2 Thinking 63.1%, 24.3 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0423 $2.716 against Kimi K2 Thinking $2.50 per million output tokens, 1.1x apart.
- Context window
- DeepSeek V4 Pro 0423 takes 1.05M tokens, Kimi K2 Thinking 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 | Kimi K2 Thinking | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 1 | 0 | ||
| Knowledge | 4 | 1 | ||
| Web design | 1 | 0 | ||
| All shared boards | 12 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 63.4% | Only Kimi K2 Thinking measured |
| LMArena WebDev | 1447 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| AA Coding Index | 59.4 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LiveCodeBench (Vals AI) | 87.5% | 63.1% | DeepSeek V4 Pro 0423 |
| SWE-bench Verified (Vals AI) | 77.4% | 60.2% | DeepSeek V4 Pro 0423 |
| 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 85.3% | Only Kimi K2 Thinking measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 31.1% | Only Kimi K2 Thinking measured |
| Terminal-Bench | Not measured | 35.7% | Only Kimi K2 Thinking measured |
| FrontierCode | 17.6% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| WeirdML | 48.9% | 42.8% | DeepSeek V4 Pro 0423 |
| ALE-Bench | 1006.1 | 597.5 | DeepSeek V4 Pro 0423 |
| LMArena Text: coding | 1470 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: software and IT | 1469 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena WebDev: React | 1441 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena WebDev: HTML | 1435 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Intelligence Index | 30.4 | 22.0 | DeepSeek V4 Pro 0423 |
| Epoch Capabilities Index | 149.1 | 145.8 | DeepSeek V4 Pro 0423 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | 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 |
| τ²-Bench Telecom | Not measured | 93.0% | Only Kimi K2 Thinking measured |
| METR time horizons | Not measured | 59.2% | Only Kimi K2 Thinking 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 index10
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| GPQA Diamond | 89.4% | 78.5% | DeepSeek V4 Pro 0423 |
| GPQA Diamond (Artificial Analysis run) | Not measured | 83.8% | Only Kimi K2 Thinking measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.8% | Only Kimi K2 Thinking 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 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: expert | 1463 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: hard prompts in English | 1466 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Kagi LLM Benchmark | 53.5% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AIME | Not measured | 85.4% | Only Kimi K2 Thinking measured |
| MGSM (Vals AI) | Not measured | 90.2% | Only Kimi K2 Thinking measured |
| AA Math Index | Not measured | 94.7 | Only Kimi K2 Thinking measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 94.7% | Only Kimi K2 Thinking measured |
| 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 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: mathematical work | 1455 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| MMLU Pro | 87.3% | 81.1% | DeepSeek V4 Pro 0423 |
| LegalBench (Vals AI) | 80.3% | 80.2% | DeepSeek V4 Pro 0423 |
| CaseLaw (Vals AI) | 59.4% | 65.7% | Kimi K2 Thinking |
| CorpFin (Vals AI) | 61.4% | 60.6% | DeepSeek V4 Pro 0423 |
| TaxEval (Vals AI) | 72.1% | 71.7% | DeepSeek V4 Pro 0423 |
| MedQA (Vals AI) | Not measured | 92.6% | Only Kimi K2 Thinking measured |
| MedCode (Vals AI) | 40.5% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 84.8% | Only Kimi K2 Thinking measured |
| SimpleQA Verified | 47.0% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: science | 1470 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: medicine and healthcare | 1466 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: legal and government | 1464 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: business and finance | 1443 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Design Arena: websites | 1234 | 1113 | DeepSeek V4 Pro 0423 |
| Design Arena: UI components | 1222 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: game dev | 1229 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: data viz | 1203 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: 3D | 1254 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: all code categories | 1240 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: SVG | 1140 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Design Arena: ASCII art | 1149 | Not measured | 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 index26 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | 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 |
| IFBench | Not measured | 68.1% | Only Kimi K2 Thinking measured |
| Long context reasoning (AA-LCR) | Not measured | 72.0% | Only Kimi K2 Thinking measured |
| DTBench | 90.7% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMCA | 41.2% | Not measured | Only DeepSeek V4 Pro 0423 measured |
| CL-bench | Not measured | 17.6% | Only Kimi K2 Thinking 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 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: instruction following | 1445 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: creative writing | 1446 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: English | 1459 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: non-English | 1439 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Chinese | 1481 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: German | 1458 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Japanese | 1446 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Korean | 1409 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: French | 1473 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Spanish | 1457 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Russian | 1453 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: Polish | 1461 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: multi-turn | 1468 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: longer queries | 1458 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: writing and language | 1447 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| LMArena Text: entertainment and media | 1431 | Not measured | Only DeepSeek V4 Pro 0423 measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0423 | Kimi K2 Thinking | 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
Kimi K2 Thinking costs less
Repository review
50K input + 3K output tokens
Kimi K2 Thinking costs less
Agent loop
200K input + 10K output tokens
Kimi K2 Thinking 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 | MoonshotAI Kimi K2 Thinking |
|---|---|---|
| Maker | DeepSeek | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | April 24, 2026 | November 6, 2025 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $1.225 | $0.60 |
| Output $/Mtok | $2.716 | $2.50 |
| Coding index | 38.7 | Not benchmarked |
| Independent measurements behind it | 5 | 1 |
| Cost per solved task | $0.57 | $0.61 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0423 better than Kimi K2 Thinking for coding?
Only DeepSeek V4 Pro 0423 has a coding score, 38.7 on the Vibe Coding Index; Kimi K2 Thinking has none, so the two cannot be ranked on coding. Pick Kimi K2 Thinking for output tokens 1.1x cheaper ($2.50 vs $2.716 per million) and work measured by CaseLaw (Vals AI), where it leads.
Which is cheaper, DeepSeek V4 Pro 0423 or Kimi K2 Thinking?
DeepSeek V4 Pro 0423 costs $1.225 per million input tokens and $2.716 per million output tokens; Kimi K2 Thinking costs $0.60 and $2.50. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0423 costs $0.57 and Kimi K2 Thinking $0.61.
Which has the bigger context window, DeepSeek V4 Pro 0423 or Kimi K2 Thinking?
DeepSeek V4 Pro 0423, with 1.05M tokens against 262K.
How many benchmarks is the DeepSeek V4 Pro 0423 vs Kimi K2 Thinking comparison based on?
13 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0423's coding index rests on 5 independent benchmarks and Kimi K2 Thinking's on 1. Where only one model has a result, the page says so instead of naming a winner.