DeepSeek V3 0324 vs Kimi K2 0711
Kimi K2 0711 leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 12.7 to 9.7, and DeepSeek V3 0324 costs 2.1x less per output token ($1.07 vs $2.30 per million). Updated October 21, 2026; 26 benchmarks have a result for both.
DeepSeek V3 0324 or Kimi K2 0711: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3 0324 for output tokens 2.1x cheaper ($1.07 vs $2.30 per million) and a larger context window (164K against 131K tokens).
- Shared results
- 26
- DeepSeek V3 0324 only
- 9
- Kimi K2 0711 only
- 11
- Like-for-like categories
- 7 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2 0711
Kimi K2 0711 leads, 12.7 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V3 0324 has a AA Agentic Index result, 0.8.
Directional only
Reasoning
GPQA Diamond
Kimi K2 0711
Kimi K2 0711 leads, 71.5% against 61.6%.
Same board, both measured
Math
AIME
Kimi K2 0711
Kimi K2 0711 leads, 62.7% against 52.2%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V3 0324
DeepSeek V3 0324 leads, 79.5% against 79.4%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Kimi K2 0711 has a Design Arena: websites result, 1050.
Directional only
Long documents
Listed context window
DeepSeek V3 0324
DeepSeek V3 0324 takes 164K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3 0324
DeepSeek V3 0324 $0.0008, Kimi K2 0711 $0.0017 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, Kimi K2 0711 not benchmarked.
- Widest category
- Agentic work, 14.0 points apart on average over 1 shared benchmark.
- Widest single gap
- SWE-bench Verified: DeepSeek V3 0324 42.0% against Kimi K2 0711 71.2%, 29.2 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against Kimi K2 0711 $2.30 per million output tokens, 2.1x apart.
- Context window
- DeepSeek V3 0324 takes 164K tokens, Kimi K2 0711 131K.
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 0324 | Bars | Kimi K2 0711 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 3 | ||
| Math | 1 | 4 | ||
| Knowledge | 3 | 3 | ||
| General | 0 | 4 | ||
| All shared boards | 5 | 21 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 59.1% | Only Kimi K2 0711 measured |
| SWE-bench Verified | 42.0% | 71.2% | Kimi K2 0711 |
| AA Coding Index | 21.2 | Not measured | Only DeepSeek V3 0324 measured |
| LiveCodeBench (Vals AI) | 65.5% | 70.5% | Kimi K2 0711 |
| LiveCodeBench (Artificial Analysis run) | 40.5% | 55.6% | Kimi K2 0711 |
| SciCode | 39.0% | Not measured | Only DeepSeek V3 0324 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 15.9% | Kimi K2 0711 |
| Terminal-Bench | Not measured | 27.8% | Only Kimi K2 0711 measured |
| GSO-Bench | Not measured | 4.9% | Only Kimi K2 0711 measured |
| WeirdML | 36.1% | 39.4% | Kimi K2 0711 |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 12.7 | Kimi K2 0711 |
| Epoch Capabilities Index | Not measured | 140.0 | Only Kimi K2 0711 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | Not measured | Only DeepSeek V3 0324 measured |
| τ²-Bench Telecom | 47.1% | 61.1% | Kimi K2 0711 |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | 71.5% | Kimi K2 0711 |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 76.6% | Kimi K2 0711 |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 7.4% | Kimi K2 0711 |
| GPQA Diamond (Epoch AI run) | 67.6% | Not measured | Only DeepSeek V3 0324 measured |
| SimpleBench | 27.2% | 26.3% | DeepSeek V3 0324 |
| Kagi LLM Benchmark | Not measured | 64.4% | Only Kimi K2 0711 measured |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| AIME | 52.2% | 62.7% | Kimi K2 0711 |
| MATH 500 (Vals AI) | 88.6% | 94.2% | Kimi K2 0711 |
| MGSM (Vals AI) | 91.7% | 91.0% | DeepSeek V3 0324 |
| AA Math Index | 41.0 | 57.0 | Kimi K2 0711 |
| AIME 2025 (Artificial Analysis run) | 41.0% | 57.0% | Kimi K2 0711 |
| OTIS Mock AIME | 37.8% | Not measured | Only DeepSeek V3 0324 measured |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | 79.4% | DeepSeek V3 0324 |
| LegalBench (Vals AI) | 77.7% | 81.5% | Kimi K2 0711 |
| CorpFin (Vals AI) | 54.7% | 50.4% | DeepSeek V3 0324 |
| TaxEval (Vals AI) | 71.1% | 70.2% | DeepSeek V3 0324 |
| MedQA (Vals AI) | 82.0% | 84.0% | Kimi K2 0711 |
| MMLU Pro (Artificial Analysis run) | 81.9% | 82.4% | Kimi K2 0711 |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1050 | Only Kimi K2 0711 measured |
| Design Arena: UI components | Not measured | 1030 | Only Kimi K2 0711 measured |
| Design Arena: game dev | Not measured | 974 | Only Kimi K2 0711 measured |
| Design Arena: data viz | Not measured | 1018 | Only Kimi K2 0711 measured |
| Design Arena: all code categories | Not measured | 1033 | Only Kimi K2 0711 measured |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | Leader |
|---|---|---|---|
| IFBench | 41.0% | 41.5% | Kimi K2 0711 |
| Long context reasoning (AA-LCR) | 40.7% | 53.0% | Kimi K2 0711 |
| DTBench | 64.8% | Not measured | Only DeepSeek V3 0324 measured |
| LMCA | 15.5% | Not measured | Only DeepSeek V3 0324 measured |
| Fiction.LiveBench | 50.0% | 61.1% | Kimi K2 0711 |
| Creative writing (Lech Mazur) | 77.0% | 85.6% | Kimi K2 0711 |
| CL-bench | Not measured | 11.9% | Only Kimi K2 0711 measured |
| Neither model has a result on the other 39 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | Kimi K2 0711 | 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 0324 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3 0324 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3 0324 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 0324 | MoonshotAI Kimi K2 0711 |
|---|---|---|
| Maker | DeepSeek | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | March 24, 2025 | July 11, 2025 |
| Context window | 164K | 131K |
| Input $/Mtok | $0.27 | $0.57 |
| Output $/Mtok | $1.07 | $2.30 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than Kimi K2 0711 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for output tokens 2.1x cheaper ($1.07 vs $2.30 per million) and a larger context window (164K against 131K tokens).
Which is cheaper, DeepSeek V3 0324 or Kimi K2 0711?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 0324 or Kimi K2 0711?
DeepSeek V3 0324, with 164K tokens against 131K.
How many benchmarks is the DeepSeek V3 0324 vs Kimi K2 0711 comparison based on?
26 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3 0324's coding index rests on 0 independent benchmarks and Kimi K2 0711's on 0. Where only one model has a result, the page says so instead of naming a winner.