DeepSeek V3.1 Terminus vs Kimi K2.5
Kimi K2.5 leads DeepSeek V3.1 Terminus on the Artificial Analysis Intelligence Index, 23.5 to 14.8, and DeepSeek V3.1 Terminus costs 2.8x less per output token ($1.0142 vs $2.85 per million). Updated October 22, 2026; 37 benchmarks have a result for both.
DeepSeek V3.1 Terminus or Kimi K2.5: which to pick
Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 Terminus for output tokens 2.8x cheaper ($1.0142 vs $2.85 per million) and work measured by LMArena Text: medicine and healthcare or LMArena Text: legal and government, where it leads.
- Shared results
- 37
- DeepSeek V3.1 Terminus only
- 8
- Kimi K2.5 only
- 62
- 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
Only Kimi K2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2.5
Kimi K2.5 leads, 23.5 against 14.8.
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 K2.5 has a GPQA Diamond result, 84.1%.
Directional only
Math
AIME
No call
Only Kimi K2.5 has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2.5 has a MMLU Pro result, 85.9%.
Directional only
Web design
Design Arena: websites
Kimi K2.5
Kimi K2.5 leads, 1248 against 1187.
Same board, both measured
Long documents
Listed context window
Kimi K2.5
Kimi K2.5 takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus $0.0008, Kimi K2.5 $0.0020 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2.5 has the number, $0.24.
Directional only
At a glance
- Coding index
- DeepSeek V3.1 Terminus not benchmarked, Kimi K2.5 38.6 from 3 benchmarks.
- Widest category
- Agentic work, 58.8 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: DeepSeek V3.1 Terminus 37.1% against Kimi K2.5 95.9%, 58.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 Terminus $1.0142 against Kimi K2.5 $2.85 per million output tokens, 2.8x apart.
- Context window
- DeepSeek V3.1 Terminus takes 164K tokens, Kimi K2.5 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 V3.1 Terminus | Bars | Kimi K2.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 1 | ||
| Knowledge | 2 | 2 | ||
| Web design | 0 | 7 | ||
| General | 0 | 13 | ||
| All shared boards | 2 | 35 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 70.8% | Only Kimi K2.5 measured |
| SWE-bench Multilingual | Not measured | 67.3% | Only Kimi K2.5 measured |
| LMArena WebDev | Not measured | 1437 | Only Kimi K2.5 measured |
| AA Coding Index | 43.5 | 46.8 | Kimi K2.5 |
| LiveCodeBench (Vals AI) | Not measured | 83.9% | Only Kimi K2.5 measured |
| SWE-bench Verified (Vals AI) | Not measured | 70.0% | Only Kimi K2.5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 17.5% | Only Kimi K2.5 measured |
| Code migration (Vals AI) | Not measured | 7.0% | Only Kimi K2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 42.0% | Only Kimi K2.5 measured |
| LiveCodeBench (Artificial Analysis run) | 79.8% | Not measured | Only DeepSeek V3.1 Terminus measured |
| SciCode | 38.0% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.8% | 34.8% | Kimi K2.5 |
| Terminal-Bench | Not measured | 43.2% | Only Kimi K2.5 measured |
| WeirdML | Not measured | 45.6% | Only Kimi K2.5 measured |
| ALE-Bench | 745.2 | 821.6 | Kimi K2.5 |
| LMArena Text: coding | 1425 | 1483 | Kimi K2.5 |
| LMArena Text: software and IT | 1426 | 1471 | Kimi K2.5 |
| LMArena WebDev: React | Not measured | 1429 | Only Kimi K2.5 measured |
| LMArena WebDev: HTML | Not measured | 1426 | Only Kimi K2.5 measured |
| LMArena WebDev: from an image | Not measured | 1439 | Only Kimi K2.5 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.8 | 23.5 | Kimi K2.5 |
| Epoch Capabilities Index | Not measured | 148.1 | Only Kimi K2.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 6.8 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Design Arena: agents building web apps | Not measured | 1136 | Only Kimi K2.5 measured |
| Design Arena: agents building full-stack apps | Not measured | 1114 | Only Kimi K2.5 measured |
| Design Arena: agents building mobile apps | Not measured | 1147 | Only Kimi K2.5 measured |
| Design Arena: agents building Android apps | Not measured | 1118 | Only Kimi K2.5 measured |
| Design Arena: agents building Godot games | Not measured | 1219 | Only Kimi K2.5 measured |
| Finance Agent (Vals AI) | Not measured | 35.8% | Only Kimi K2.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 15.9% | Only Kimi K2.5 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 28.5% | Only Kimi K2.5 measured |
| τ²-Bench Telecom | 37.1% | 95.9% | Kimi K2.5 |
| OSWorld | Not measured | 63.3% | Only Kimi K2.5 measured |
| Vending-Bench 2 | Not measured | $1,198 | Only Kimi K2.5 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.1% | Only Kimi K2.5 measured |
| MMMU Pro (Vals AI) | Not measured | 84.3% | Only Kimi K2.5 measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 87.9% | Kimi K2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 16.4% | 30.7% | Kimi K2.5 |
| ARC-AGI | Not measured | 65.3% | Only Kimi K2.5 measured |
| ARC-AGI-2 | Not measured | 11.8% | Only Kimi K2.5 measured |
| SimpleBench | Not measured | 46.8% | Only Kimi K2.5 measured |
| LMArena Text: hard prompts | 1426 | 1453 | Kimi K2.5 |
| LMArena Text: expert | Not measured | 1466 | Only Kimi K2.5 measured |
| LMArena Text: hard prompts in English | 1432 | 1460 | Kimi K2.5 |
| LMArena Vision: diagrams | Not measured | 1282 | Only Kimi K2.5 measured |
| LMArena Vision: homework | Not measured | 1297 | Only Kimi K2.5 measured |
| Kagi LLM Benchmark | 57.4% | 78.5% | Kimi K2.5 |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| AIME | Not measured | 95.6% | Only Kimi K2.5 measured |
| AA Math Index | 89.7 | Not measured | Only DeepSeek V3.1 Terminus measured |
| AIME 2025 (Artificial Analysis run) | 89.7% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMArena Text: math | 1402 | 1470 | Kimi K2.5 |
| LMArena Text: mathematical work | Not measured | 1473 | Only Kimi K2.5 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 85.9% | Only Kimi K2.5 measured |
| CaseLaw (Vals AI) | Not measured | 58.7% | Only Kimi K2.5 measured |
| CorpFin (Vals AI) | Not measured | 68.3% | Only Kimi K2.5 measured |
| TaxEval (Vals AI) | Not measured | 74.2% | Only Kimi K2.5 measured |
| MortgageTax (Vals AI) | Not measured | 66.5% | Only Kimi K2.5 measured |
| MedQA (Vals AI) | Not measured | 94.4% | Only Kimi K2.5 measured |
| MedCode (Vals AI) | Not measured | 39.3% | Only Kimi K2.5 measured |
| MMLU Pro (Artificial Analysis run) | 85.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| SimpleQA Verified | Not measured | 34.3% | Only Kimi K2.5 measured |
| LMArena Text: science | 1451 | 1459 | Kimi K2.5 |
| LMArena Text: medicine and healthcare | 1468 | 1448 | DeepSeek V3.1 Terminus |
| LMArena Text: legal and government | 1457 | 1441 | DeepSeek V3.1 Terminus |
| LMArena Text: business and finance | 1414 | 1427 | Kimi K2.5 |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | 1248 | Kimi K2.5 |
| Design Arena: UI components | 1182 | 1234 | Kimi K2.5 |
| Design Arena: game dev | 1131 | 1206 | Kimi K2.5 |
| Design Arena: data viz | 1168 | 1219 | Kimi K2.5 |
| Design Arena: 3D | 1141 | 1204 | Kimi K2.5 |
| Design Arena: all code categories | 1175 | 1236 | Kimi K2.5 |
| Design Arena: SVG | 1065 | 1149 | Kimi K2.5 |
| Design Arena: ASCII art | Not measured | 1166 | Only Kimi K2.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index013
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 49.9% | Only Kimi K2.5 measured |
| MedScribe (Vals AI) | Not measured | 76.4% | Only Kimi K2.5 measured |
| IFBench | 57.0% | 70.2% | Kimi K2.5 |
| Long context reasoning (AA-LCR) | 69.3% | 78.0% | Kimi K2.5 |
| 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 | 86.1% | Only Kimi K2.5 measured |
| CL-bench | Not measured | 19.3% | Only Kimi K2.5 measured |
| CL-bench Life | Not measured | 13.2% | Only Kimi K2.5 measured |
| LMArena Text | 1419 | 1445 | Kimi K2.5 |
| LMArena Text: instruction following | 1404 | 1431 | Kimi K2.5 |
| LMArena Text: creative writing | 1403 | 1422 | Kimi K2.5 |
| LMArena Vision | Not measured | 1269 | Only Kimi K2.5 measured |
| LMArena Text: English | 1429 | 1453 | Kimi K2.5 |
| LMArena Text: non-English | 1408 | 1433 | Kimi K2.5 |
| LMArena Text: Chinese | Not measured | 1494 | Only Kimi K2.5 measured |
| LMArena Text: German | Not measured | 1441 | Only Kimi K2.5 measured |
| LMArena Text: Japanese | Not measured | 1423 | Only Kimi K2.5 measured |
| LMArena Text: Korean | Not measured | 1412 | Only Kimi K2.5 measured |
| LMArena Text: French | Not measured | 1454 | Only Kimi K2.5 measured |
| LMArena Text: Spanish | Not measured | 1450 | Only Kimi K2.5 measured |
| LMArena Text: Russian | 1435 | 1435 | Kimi K2.5 |
| LMArena Text: Polish | 1427 | 1445 | Kimi K2.5 |
| LMArena Text: multi-turn | 1411 | 1444 | Kimi K2.5 |
| LMArena Text: longer queries | 1422 | 1445 | Kimi K2.5 |
| LMArena Text: writing and language | 1409 | 1425 | Kimi K2.5 |
| LMArena Text: entertainment and media | 1391 | 1417 | Kimi K2.5 |
| LMArena Vision: English | Not measured | 1274 | Only Kimi K2.5 measured |
| LMArena Vision: Chinese | Not measured | 1328 | Only Kimi K2.5 measured |
| LMArena Vision: reading text | Not measured | 1276 | Only Kimi K2.5 measured |
| LMArena Vision: humor | Not measured | 1284 | Only Kimi K2.5 measured |
| LMArena Vision: captioning | Not measured | 1257 | Only Kimi K2.5 measured |
| LMArena Vision: recognizing things | Not measured | 1285 | Only Kimi K2.5 measured |
| LMArena Vision: creative writing | Not measured | 1269 | Only Kimi K2.5 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Kimi K2.5 | 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 K2.5 |
|---|---|---|
| Maker | DeepSeek | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | September 22, 2025 | January 27, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.3063 | $0.532 |
| Output $/Mtok | $1.0142 | $2.85 |
| Coding index | Not benchmarked | 38.6 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $0.24 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 Terminus better than Kimi K2.5 for coding?
Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding. Pick DeepSeek V3.1 Terminus for output tokens 2.8x cheaper ($1.0142 vs $2.85 per million) and work measured by LMArena Text: medicine and healthcare or LMArena Text: legal and government, where it leads.
Which is cheaper, DeepSeek V3.1 Terminus or Kimi K2.5?
DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 per million output tokens; Kimi K2.5 costs $0.532 and $2.85. Cost per solved task is known for Kimi K2.5 only.
Which has the bigger context window, DeepSeek V3.1 Terminus or Kimi K2.5?
Kimi K2.5, with 262K tokens against 164K.
How many benchmarks is the DeepSeek V3.1 Terminus vs Kimi K2.5 comparison based on?
37 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.1 Terminus's coding index rests on 0 independent benchmarks and Kimi K2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.