DeepSeek V3.2 Exp vs Kimi K3
Kimi K3 leads DeepSeek V3.2 Exp on the Artificial Analysis Intelligence Index, 43.6 to 16.6, and DeepSeek V3.2 Exp costs 36.6x less per output token ($0.41 vs $15.00 per million). Updated October 21, 2026; 45 benchmarks have a result for both.
DeepSeek V3.2 Exp or Kimi K3: which to pick
Only Kimi K3 has a coding score, 62.3 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.2 Exp for output tokens 36.6x cheaper ($0.41 vs $15.00 per million).
- Shared results
- 45
- DeepSeek V3.2 Exp only
- 14
- Kimi K3 only
- 72
- 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
Only Kimi K3 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K3
Kimi K3 leads, 43.6 against 16.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Kimi K3 has a AA Agentic Index result, 50.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Kimi K3 has a GPQA Diamond result, 92.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K3 has a MMLU Pro result, 88.0%.
Directional only
Web design
Design Arena: websites
Kimi K3
Kimi K3 leads, 1335 against 1179.
Same board, both measured
General
Vals Index
No call
Only Kimi K3 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
Kimi K3
Kimi K3 takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.2 Exp
DeepSeek V3.2 Exp $0.0005, Kimi K3 $0.011 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K3 has the number, $0.81.
Directional only
At a glance
- Coding index
- DeepSeek V3.2 Exp not benchmarked, Kimi K3 62.3 from 6 benchmarks.
- Widest category
- Coding, 34.6 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: DeepSeek V3.2 Exp 1272 against Kimi K3 1655, 54.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.2 Exp $0.41 against Kimi K3 $15.00 per million output tokens, 36.6x apart.
- Context window
- DeepSeek V3.2 Exp takes 164K tokens, Kimi K3 1.05M.
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 V3.2 Exp | Bars | Kimi K3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 7 | ||
| General | 0 | 20 | ||
| All shared boards | 0 | 45 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| Aider polyglot | 74.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| LiveBench coding | Not measured | 59.3% | Only Kimi K3 measured |
| LMArena WebDev | 1272 | 1655 | Kimi K3 |
| AA Coding Index | Not measured | 76.2 | Only Kimi K3 measured |
| LiveCodeBench (Vals AI) | Not measured | 87.2% | Only Kimi K3 measured |
| SWE-bench Verified (Vals AI) | Not measured | 93.4% | Only Kimi K3 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 17.2% | Only Kimi K3 measured |
| Vibe Code Bench (Vals AI) | Not measured | 85.0% | Only Kimi K3 measured |
| Code migration (Vals AI) | Not measured | 16.1% | Only Kimi K3 measured |
| ProgramBench (Vals AI) | Not measured | 2.0% | Only Kimi K3 measured |
| IOI (Vals AI) | Not measured | 48.9% | Only Kimi K3 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 80.9% | Only Kimi K3 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 44.2% | Only Kimi K3 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 18.2% | Only Kimi K3 measured |
| CyberBench (Vals AI) | Not measured | 75.2% | Only Kimi K3 measured |
| LiveCodeBench (Artificial Analysis run) | 78.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| SciCode | Not measured | 59.5% | Only Kimi K3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.1% | Not measured | Only DeepSeek V3.2 Exp measured |
| FrontierCode | Not measured | 44.2% | Only Kimi K3 measured |
| FrontierSWE | Not measured | 25.9% | Only Kimi K3 measured |
| WeirdML | 39.5% | 82.6% | Kimi K3 |
| ALE-Bench | Not measured | 1524.5 | Only Kimi K3 measured |
| LMArena Text: coding | 1438 | 1508 | Kimi K3 |
| LMArena Text: software and IT | 1438 | 1499 | Kimi K3 |
| LMArena WebDev: React | Not measured | 1670 | Only Kimi K3 measured |
| LMArena WebDev: HTML | 1281 | 1644 | Kimi K3 |
| LMArena WebDev: from an image | Not measured | 1579 | Only Kimi K3 measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.6 | 43.6 | Kimi K3 |
| Epoch Capabilities Index | 144.9 | 157.9 | Kimi K3 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index27 boards, none shared
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.0 | Only Kimi K3 measured |
| Design Arena: agents building web apps | Not measured | 1295 | Only Kimi K3 measured |
| Design Arena: agents building full-stack apps | Not measured | 1315 | Only Kimi K3 measured |
| Design Arena: agents building mobile apps | Not measured | 1269 | Only Kimi K3 measured |
| Design Arena: agents building Android apps | Not measured | 1250 | Only Kimi K3 measured |
| Design Arena: agents building Godot games | Not measured | 1223 | Only Kimi K3 measured |
| Design Arena: agents building games | Not measured | 1252 | Only Kimi K3 measured |
| Design Arena: HTML slides | Not measured | 1256 | Only Kimi K3 measured |
| Design Arena: PowerPoint slides | Not measured | 1273 | Only Kimi K3 measured |
| Design Arena: spreadsheets | Not measured | 1058 | Only Kimi K3 measured |
| LiveBench research | Not measured | 79.0% | Only Kimi K3 measured |
| LiveBench browser | Not measured | 16.0% | Only Kimi K3 measured |
| LiveBench long agentic | Not measured | 42.8% | Only Kimi K3 measured |
| Finance Agent (Vals AI) | Not measured | 53.1% | Only Kimi K3 measured |
| Tax Agent Bench (Vals AI) | Not measured | 33.4% | Only Kimi K3 measured |
| Legal Research Bench (Vals AI) | Not measured | 46.1% | Only Kimi K3 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.9% | Only Kimi K3 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 66.7% | Only Kimi K3 measured |
| BioMysteryBench (Vals AI) | Not measured | 72.6% | Only Kimi K3 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 1.4% | Only Kimi K3 measured |
| Time Horizon Index (Vals AI) | Not measured | 10.5% | Only Kimi K3 measured |
| τ²-Bench Telecom | 33.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| APEX-Agents | Not measured | 47.8% | Only Kimi K3 measured |
| PostTrainBench | Not measured | 32.0% | Only Kimi K3 measured |
| TheAgentCompany | 42.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| Vending-Bench 2 | Not measured | $5,165 | Only Kimi K3 measured |
| Berkeley Function Calling Leaderboard (BFCL) | 56.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 14 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 92.9% | Only Kimi K3 measured |
| LiveBench reasoning | Not measured | 90.7% | Only Kimi K3 measured |
| MMMU Pro (Vals AI) | Not measured | 88.2% | Only Kimi K3 measured |
| GPQA Diamond (Artificial Analysis run) | 79.7% | 93.5% | Kimi K3 |
| Humanity's Last Exam (Artificial Analysis run) | 14.9% | 46.9% | Kimi K3 |
| GPQA Diamond (Epoch AI run) | Not measured | 93.1% | Only Kimi K3 measured |
| ARC-AGI | Not measured | 94.5% | Only Kimi K3 measured |
| ARC-AGI-2 | Not measured | 60.4% | Only Kimi K3 measured |
| SimpleBench | Not measured | 60.7% | Only Kimi K3 measured |
| Chess puzzles | Not measured | 37.0% | Only Kimi K3 measured |
| Mystery game puzzles | Not measured | 26.0% | Only Kimi K3 measured |
| LMArena Text: hard prompts | 1429 | 1495 | Kimi K3 |
| LMArena Text: expert | 1422 | 1520 | Kimi K3 |
| LMArena Text: hard prompts in English | 1444 | 1496 | Kimi K3 |
| Kagi LLM Benchmark | 52.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only DeepSeek V3.2 Exp measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| OTIS Mock AIME | Not measured | 97.2% | Only Kimi K3 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 72.2% | Only Kimi K3 measured |
| FrontierMath, tier 4 | Not measured | 39.0% | Only Kimi K3 measured |
| ProofBench | Not measured | 87.0% | Only Kimi K3 measured |
| LMArena Text: math | 1422 | 1494 | Kimi K3 |
| LMArena Text: mathematical work | 1433 | 1505 | Kimi K3 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 88.0% | Only Kimi K3 measured |
| LegalBench (Vals AI) | Not measured | 86.2% | Only Kimi K3 measured |
| CorpFin (Vals AI) | Not measured | 71.6% | Only Kimi K3 measured |
| TaxEval (Vals AI) | Not measured | 75.7% | Only Kimi K3 measured |
| MortgageTax (Vals AI) | Not measured | 66.3% | Only Kimi K3 measured |
| MedCode (Vals AI) | Not measured | 49.4% | Only Kimi K3 measured |
| MMLU Pro (Artificial Analysis run) | 85.0% | Not measured | Only DeepSeek V3.2 Exp measured |
| SimpleQA Verified | Not measured | 50.6% | Only Kimi K3 measured |
| LMArena Text: science | 1443 | 1508 | Kimi K3 |
| LMArena Text: medicine and healthcare | 1468 | 1489 | Kimi K3 |
| LMArena Text: legal and government | 1419 | 1503 | Kimi K3 |
| LMArena Text: business and finance | 1412 | 1470 | Kimi K3 |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1179 | 1335 | Kimi K3 |
| Design Arena: UI components | 1167 | 1344 | Kimi K3 |
| Design Arena: game dev | 1144 | 1359 | Kimi K3 |
| Design Arena: data viz | 1152 | 1351 | Kimi K3 |
| Design Arena: 3D | 1148 | 1388 | Kimi K3 |
| Design Arena: all code categories | 1171 | 1360 | Kimi K3 |
| Design Arena: SVG | 1032 | 1302 | Kimi K3 |
| LiveBench design | Not measured | 77.2% | Only Kimi K3 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index020
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.0% | Only Kimi K3 measured |
| LiveBench data analysis | Not measured | 78.7% | Only Kimi K3 measured |
| Public Benefits Bench (Vals AI) | Not measured | 68.2% | Only Kimi K3 measured |
| SAGE (Vals AI) | Not measured | 52.8% | Only Kimi K3 measured |
| MedScribe (Vals AI) | Not measured | 88.0% | Only Kimi K3 measured |
| Vals Multimodal Index | Not measured | 73.4% | Only Kimi K3 measured |
| IFBench | 54.1% | Not measured | Only DeepSeek V3.2 Exp measured |
| Long context reasoning (AA-LCR) | 72.3% | 88.7% | Kimi K3 |
| DTBench | 87.7% | 91.2% | Kimi K3 |
| LMCA | 29.1% | 52.7% | Kimi K3 |
| Fiction.LiveBench | 83.3% | Not measured | Only DeepSeek V3.2 Exp measured |
| CL-bench | 13.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| Surface Evolver Bench | Not measured | 95.0% | Only Kimi K3 measured |
| Furniture assembly | Not measured | 34.2% | Only Kimi K3 measured |
| CL-bench Life | 9.5% | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text | 1425 | 1476 | Kimi K3 |
| LMArena Text: instruction following | 1401 | 1485 | Kimi K3 |
| LMArena Text: creative writing | 1404 | 1457 | Kimi K3 |
| LMArena Text: English | 1441 | 1481 | Kimi K3 |
| LMArena Text: non-English | 1404 | 1466 | Kimi K3 |
| LMArena Text: Chinese | 1461 | 1529 | Kimi K3 |
| LMArena Text: German | 1440 | 1490 | Kimi K3 |
| LMArena Text: Japanese | 1331 | 1494 | Kimi K3 |
| LMArena Text: Korean | 1372 | 1460 | Kimi K3 |
| LMArena Text: French | 1434 | 1492 | Kimi K3 |
| LMArena Text: Spanish | 1441 | 1472 | Kimi K3 |
| LMArena Text: Russian | 1412 | 1485 | Kimi K3 |
| LMArena Text: Polish | 1435 | 1458 | Kimi K3 |
| LMArena Text: multi-turn | 1422 | 1489 | Kimi K3 |
| LMArena Text: longer queries | 1418 | 1494 | Kimi K3 |
| LMArena Text: writing and language | 1407 | 1471 | Kimi K3 |
| LMArena Text: entertainment and media | 1407 | 1453 | Kimi K3 |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.2 Exp | Kimi K3 | 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 V3.2 Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.2 Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.2 Exp 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 V3.2 Exp | MoonshotAI Kimi K3 |
|---|---|---|
| Maker | DeepSeek | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | September 29, 2025 | July 16, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.27 | $3.00 |
| Output $/Mtok | $0.41 | $15.00 |
| Coding index | Not benchmarked | 62.3 |
| Independent measurements behind it | 1 | 6 |
| Cost per solved task | Not computable | $0.81 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.2 Exp better than Kimi K3 for coding?
Only Kimi K3 has a coding score, 62.3 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding. Pick DeepSeek V3.2 Exp for output tokens 36.6x cheaper ($0.41 vs $15.00 per million).
Which is cheaper, DeepSeek V3.2 Exp or Kimi K3?
DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Kimi K3 costs $3.00 and $15.00. Cost per solved task is known for Kimi K3 only.
Which has the bigger context window, DeepSeek V3.2 Exp or Kimi K3?
Kimi K3, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.2 Exp vs Kimi K3 comparison based on?
45 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark and Kimi K3's on 6. Where only one model has a result, the page says so instead of naming a winner.