DeepSeek V3.1 Terminus vs Kimi K2 0711
DeepSeek V3.1 Terminus leads Kimi K2 0711 on the Artificial Analysis Intelligence Index, 14.8 to 12.7, and DeepSeek V3.1 Terminus costs 2.3x less per output token ($1.0142 vs $2.30 per million). Updated October 21, 2026; 17 benchmarks have a result for both.
DeepSeek V3.1 Terminus or Kimi K2 0711: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 Terminus for output tokens 2.3x cheaper ($1.0142 vs $2.30 per million) and a larger context window (164K against 131K tokens).
- Shared results
- 17
- DeepSeek V3.1 Terminus only
- 28
- Kimi K2 0711 only
- 20
- 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus leads, 14.8 against 12.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V3.1 Terminus has a AA Agentic Index result, 6.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Kimi K2 0711 has a GPQA Diamond result, 71.5%.
Directional only
Math
AIME
No call
Only Kimi K2 0711 has a AIME result, 62.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 0711 has a MMLU Pro result, 79.4%.
Directional only
Web design
Design Arena: websites
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus leads, 1187 against 1050.
Same board, both measured
Long documents
Listed context window
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus takes 164K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus $0.0008, Kimi K2 0711 $0.0017 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 Terminus not benchmarked, Kimi K2 0711 not benchmarked.
- Widest category
- Math, 32.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: DeepSeek V3.1 Terminus 89.7 against Kimi K2 0711 57.0, 32.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 Terminus $1.0142 against Kimi K2 0711 $2.30 per million output tokens, 2.3x apart.
- Context window
- DeepSeek V3.1 Terminus 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 V3.1 Terminus | Bars | Kimi K2 0711 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 5 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 15 | 2 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 59.1% | Only Kimi K2 0711 measured |
| SWE-bench Verified | Not measured | 71.2% | Only Kimi K2 0711 measured |
| AA Coding Index | 43.5 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LiveCodeBench (Vals AI) | Not measured | 70.5% | Only Kimi K2 0711 measured |
| LiveCodeBench (Artificial Analysis run) | 79.8% | 55.6% | DeepSeek V3.1 Terminus |
| SciCode | 38.0% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.8% | 15.9% | DeepSeek V3.1 Terminus |
| Terminal-Bench | Not measured | 27.8% | Only Kimi K2 0711 measured |
| GSO-Bench | Not measured | 4.9% | Only Kimi K2 0711 measured |
| WeirdML | Not measured | 39.4% | Only Kimi K2 0711 measured |
| ALE-Bench | 745.2 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: coding | 1425 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: software and IT | 1426 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.8 | 12.7 | DeepSeek V3.1 Terminus |
| 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 V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| AA Agentic Index | 6.8 | Not measured | Only DeepSeek V3.1 Terminus measured |
| τ²-Bench Telecom | 37.1% | 61.1% | Kimi K2 0711 |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 71.5% | Only Kimi K2 0711 measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 76.6% | DeepSeek V3.1 Terminus |
| Humanity's Last Exam (Artificial Analysis run) | 16.4% | 7.4% | DeepSeek V3.1 Terminus |
| SimpleBench | Not measured | 26.3% | Only Kimi K2 0711 measured |
| LMArena Text: hard prompts | 1426 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: hard prompts in English | 1432 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Kagi LLM Benchmark | 57.4% | 64.4% | Kimi K2 0711 |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| AIME | Not measured | 62.7% | Only Kimi K2 0711 measured |
| MATH 500 (Vals AI) | Not measured | 94.2% | Only Kimi K2 0711 measured |
| MGSM (Vals AI) | Not measured | 91.0% | Only Kimi K2 0711 measured |
| AA Math Index | 89.7 | 57.0 | DeepSeek V3.1 Terminus |
| AIME 2025 (Artificial Analysis run) | 89.7% | 57.0% | DeepSeek V3.1 Terminus |
| LMArena Text: math | 1402 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 79.4% | Only Kimi K2 0711 measured |
| LegalBench (Vals AI) | Not measured | 81.5% | Only Kimi K2 0711 measured |
| CorpFin (Vals AI) | Not measured | 50.4% | Only Kimi K2 0711 measured |
| TaxEval (Vals AI) | Not measured | 70.2% | Only Kimi K2 0711 measured |
| MedQA (Vals AI) | Not measured | 84.0% | Only Kimi K2 0711 measured |
| MMLU Pro (Artificial Analysis run) | 85.1% | 82.4% | DeepSeek V3.1 Terminus |
| LMArena Text: science | 1451 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: medicine and healthcare | 1468 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: legal and government | 1457 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: business and finance | 1414 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | 1050 | DeepSeek V3.1 Terminus |
| Design Arena: UI components | 1182 | 1030 | DeepSeek V3.1 Terminus |
| Design Arena: game dev | 1131 | 974 | DeepSeek V3.1 Terminus |
| Design Arena: data viz | 1167 | 1018 | DeepSeek V3.1 Terminus |
| Design Arena: 3D | 1141 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: all code categories | 1175 | 1033 | DeepSeek V3.1 Terminus |
| Design Arena: SVG | 1065 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2 0711 | Leader |
|---|---|---|---|
| IFBench | 57.0% | 41.5% | DeepSeek V3.1 Terminus |
| Long context reasoning (AA-LCR) | 69.3% | 53.0% | DeepSeek V3.1 Terminus |
| DTBench | 81.3% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMCA | 28.6% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Fiction.LiveBench | Not measured | 61.1% | Only Kimi K2 0711 measured |
| Creative writing (Lech Mazur) | Not measured | 85.6% | Only Kimi K2 0711 measured |
| CL-bench | Not measured | 11.9% | Only Kimi K2 0711 measured |
| LMArena Text | 1419 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: instruction following | 1404 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: creative writing | 1403 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: English | 1429 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: non-English | 1408 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: Russian | 1435 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: Polish | 1427 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: multi-turn | 1411 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: longer queries | 1422 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: writing and language | 1409 | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: entertainment and media | 1391 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | 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 V3.1 Terminus costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 Terminus costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 Terminus 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 V3.1 Terminus | MoonshotAI Kimi K2 0711 |
|---|---|---|
| Maker | DeepSeek | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | September 22, 2025 | July 11, 2025 |
| Context window | 164K | 131K |
| Input $/Mtok | $0.3063 | $0.57 |
| Output $/Mtok | $1.0142 | $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 V3.1 Terminus better than Kimi K2 0711 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.1 Terminus for output tokens 2.3x cheaper ($1.0142 vs $2.30 per million) and a larger context window (164K against 131K tokens).
Which is cheaper, DeepSeek V3.1 Terminus or Kimi K2 0711?
DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 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 V3.1 Terminus or Kimi K2 0711?
DeepSeek V3.1 Terminus, with 164K tokens against 131K.
How many benchmarks is the DeepSeek V3.1 Terminus vs Kimi K2 0711 comparison based on?
17 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1 Terminus'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.