DeepSeek V3 vs Kimi K2.7 Code
DeepSeek V3 costs 4.2x less per output token than Kimi K2.7 Code ($0.9594 vs $4.00 per million). Updated October 22, 2026; 9 benchmarks have a result for both.
DeepSeek V3 or Kimi K2.7 Code: which to pick
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; DeepSeek V3 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3 for output tokens 4.2x cheaper ($0.9594 vs $4.00 per million).
- Shared results
- 9
- DeepSeek V3 only
- 5
- Kimi K2.7 Code only
- 42
- Like-for-like categories
- 3 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 Kimi K2.7 Code has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Kimi K2.7 Code has a AA Intelligence Index result, 25.8.
Directional only
Agentic work
AA Agentic Index
No call
Only Kimi K2.7 Code has a AA Agentic Index result, 21.0.
Directional only
Web design
Design Arena: websites
Kimi K2.7 Code
Kimi K2.7 Code leads, 1263 against 1120.
Same board, both measured
Long documents
Listed context window
Kimi K2.7 Code
Kimi K2.7 Code takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3
DeepSeek V3 $0.0008, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2.7 Code has the number, $0.35.
Directional only
At a glance
- Coding index
- DeepSeek V3 not benchmarked, Kimi K2.7 Code 53.4 from 4 benchmarks.
- Widest category
- Math, 46.7 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: DeepSeek V3 48.9% against Kimi K2.7 Code 95.6%, 46.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 $0.9594 against Kimi K2.7 Code $4.00 per million output tokens, 4.2x apart.
- Context window
- DeepSeek V3 takes 164K tokens, Kimi K2.7 Code 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 V3 | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Reasoning | 0 | 1 | ||
| Math | 0 | 1 | ||
| Web design | 0 | 7 | ||
| All shared boards | 0 | 9 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index19 boards, none shared
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Aider polyglot | 70.2% | Not measured | Only DeepSeek V3 measured |
| SWE-bench Lite | 30.7% | Not measured | Only DeepSeek V3 measured |
| LMArena WebDev | Not measured | 1474 | Only Kimi K2.7 Code measured |
| AA Coding Index | Not measured | 60.8 | Only Kimi K2.7 Code measured |
| LiveCodeBench (Vals AI) | Not measured | 82.0% | Only Kimi K2.7 Code measured |
| SWE-bench Verified (Vals AI) | Not measured | 78.2% | Only Kimi K2.7 Code measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.2% | Only Kimi K2.7 Code measured |
| Code migration (Vals AI) | Not measured | 25.4% | Only Kimi K2.7 Code measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Kimi K2.7 Code measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.0% | Only Kimi K2.7 Code measured |
| SkillsBench (Vals AI) | Not measured | 50.0% | Only Kimi K2.7 Code measured |
| SciCode | Not measured | 47.8% | Only Kimi K2.7 Code measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 44.7% | Only Kimi K2.7 Code measured |
| FrontierCode | Not measured | 30.1% | Only Kimi K2.7 Code measured |
| WeirdML | Not measured | 54.1% | Only Kimi K2.7 Code measured |
| ALE-Bench | Not measured | 886.2 | Only Kimi K2.7 Code measured |
| LMArena WebDev: React | Not measured | 1475 | Only Kimi K2.7 Code measured |
| LMArena WebDev: HTML | Not measured | 1451 | Only Kimi K2.7 Code measured |
| LMArena WebDev: from an image | Not measured | 1513 | Only Kimi K2.7 Code measured |
| 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 V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 25.8 | Only Kimi K2.7 Code measured |
| Epoch Capabilities Index | Not measured | 150.1 | Only Kimi K2.7 Code measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.0 | Only Kimi K2.7 Code measured |
| Design Arena: agents building web apps | Not measured | 1176 | Only Kimi K2.7 Code measured |
| Design Arena: agents building full-stack apps | Not measured | 1175 | Only Kimi K2.7 Code measured |
| Design Arena: agents building mobile apps | Not measured | 1143 | Only Kimi K2.7 Code measured |
| Design Arena: agents building Android apps | Not measured | 1138 | Only Kimi K2.7 Code measured |
| Design Arena: agents building Godot games | Not measured | 1147 | Only Kimi K2.7 Code measured |
| Design Arena: agents building games | Not measured | 1130 | Only Kimi K2.7 Code measured |
| Design Arena: HTML slides | Not measured | 1151 | Only Kimi K2.7 Code measured |
| Design Arena: PowerPoint slides | Not measured | 1129 | Only Kimi K2.7 Code measured |
| τ²-Bench Telecom | Not measured | 90.1% | Only Kimi K2.7 Code measured |
| APEX-Agents | Not measured | 37.6% | Only Kimi K2.7 Code measured |
| Vending-Bench 2 | Not measured | $5,083 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.6% | Only Kimi K2.7 Code measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 35.0% | Only Kimi K2.7 Code measured |
| GPQA Diamond (Epoch AI run) | 71.2% | 87.9% | Kimi K2.7 Code |
| SimpleBench | Not measured | 57.9% | Only Kimi K2.7 Code measured |
| Chess puzzles | Not measured | 14.0% | Only Kimi K2.7 Code measured |
| Kagi LLM Benchmark | 52.3% | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| OTIS Mock AIME | 48.9% | 95.6% | Kimi K2.7 Code |
| FrontierMath, tiers 1 to 3 | Not measured | 54.0% | Only Kimi K2.7 Code measured |
| FrontierMath, tier 4 | Not measured | 12.2% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| SimpleQA Verified | Not measured | 36.5% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | 1120 | 1263 | Kimi K2.7 Code |
| Design Arena: UI components | 1090 | 1255 | Kimi K2.7 Code |
| Design Arena: game dev | 1053 | 1220 | Kimi K2.7 Code |
| Design Arena: data viz | 1089 | 1227 | Kimi K2.7 Code |
| Design Arena: 3D | 1086 | 1240 | Kimi K2.7 Code |
| Design Arena: all code categories | 1108 | 1252 | Kimi K2.7 Code |
| Design Arena: SVG | 976 | 1176 | Kimi K2.7 Code |
| Design Arena: ASCII art | Not measured | 1196 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| IFBench | Not measured | 63.1% | Only Kimi K2.7 Code measured |
| Long context reasoning (AA-LCR) | Not measured | 79.3% | Only Kimi K2.7 Code measured |
| DTBench | 62.7% | Not measured | Only DeepSeek V3 measured |
| LMCA | 15.2% | Not measured | Only DeepSeek V3 measured |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 | Kimi K2.7 Code | 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 | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | DeepSeek | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | December 26, 2024 | June 12, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.2887 | $0.95 |
| Output $/Mtok | $0.9594 | $4.00 |
| Coding index | Not benchmarked | 53.4 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 better than Kimi K2.7 Code for coding?
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; DeepSeek V3 has none, so the two cannot be ranked on coding. Pick DeepSeek V3 for output tokens 4.2x cheaper ($0.9594 vs $4.00 per million).
Which is cheaper, DeepSeek V3 or Kimi K2.7 Code?
DeepSeek V3 costs $0.2887 per million input tokens and $0.9594 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Cost per solved task is known for Kimi K2.7 Code only.
Which has the bigger context window, DeepSeek V3 or Kimi K2.7 Code?
Kimi K2.7 Code, with 262K tokens against 164K.
How many benchmarks is the DeepSeek V3 vs Kimi K2.7 Code comparison based on?
9 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3's coding index rests on 0 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.