DeepSeek V3.1 Terminus vs Qwen3.5 Plus 2026-02-15
DeepSeek V3.1 Terminus costs 1.5x less per output token than Qwen3.5 Plus 2026-02-15 ($1.0142 vs $1.56 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
DeepSeek V3.1 Terminus or Qwen3.5 Plus 2026-02-15: 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 1.5x cheaper ($1.0142 vs $1.56 per million) and work measured by Design Arena: SVG, where it leads.
- Shared results
- 7
- DeepSeek V3.1 Terminus only
- 38
- Qwen3.5 Plus 2026-02-15 only
- 1
- Like-for-like categories
- 1 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
No call
Only DeepSeek V3.1 Terminus has a AA Intelligence Index result, 14.8.
Directional only
Agentic work
AA Agentic Index
No call
Only DeepSeek V3.1 Terminus has a AA Agentic Index result, 6.8.
Directional only
Web design
Design Arena: websites
No call
Tied at 1187.
Same board, both measured
Long documents
Listed context window
Qwen3.5 Plus 2026-02-15
Qwen3.5 Plus 2026-02-15 takes 1M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus $0.0008, Qwen3.5 Plus 2026-02-15 $0.0010 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 Terminus not benchmarked, Qwen3.5 Plus 2026-02-15 not benchmarked.
- Widest category
- Web design, 2.5 points apart on average over 7 shared benchmarks.
- Widest single gap
- Design Arena: SVG: DeepSeek V3.1 Terminus 1065 against Qwen3.5 Plus 2026-02-15 1107, 5.3 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 Terminus $1.0142 against Qwen3.5 Plus 2026-02-15 $1.56 per million output tokens, 1.5x apart.
- Context window
- DeepSeek V3.1 Terminus takes 164K tokens, Qwen3.5 Plus 2026-02-15 1M.
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 | Qwen3.5 Plus 2026-02-15 | Ties |
|---|---|---|---|---|
| Web design | 5 | 1 | 1 tie | |
| All shared boards | 5 | 1 | 1 tie |
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| AA Coding Index | 43.5 | Not measured | Only DeepSeek V3.1 Terminus 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% | Not measured | Only DeepSeek V3.1 Terminus 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 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.8 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| AA Agentic Index | 6.8 | Not measured | Only DeepSeek V3.1 Terminus measured |
| τ²-Bench Telecom | 37.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.2% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Humanity's Last Exam (Artificial Analysis run) | 16.4% | Not measured | Only DeepSeek V3.1 Terminus 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% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| 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 | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 85.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| 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 15 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | 1187 | Tie |
| Design Arena: UI components | 1180 | 1175 | DeepSeek V3.1 Terminus |
| Design Arena: game dev | 1131 | 1105 | DeepSeek V3.1 Terminus |
| Design Arena: data viz | 1168 | 1135 | DeepSeek V3.1 Terminus |
| Design Arena: 3D | 1141 | 1118 | DeepSeek V3.1 Terminus |
| Design Arena: all code categories | 1175 | 1166 | DeepSeek V3.1 Terminus |
| Design Arena: SVG | 1065 | 1107 | Qwen3.5 Plus 2026-02-15 |
| Design Arena: ASCII art | Not measured | 1094 | Only Qwen3.5 Plus 2026-02-15 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | Leader |
|---|---|---|---|
| IFBench | 57.0% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Long context reasoning (AA-LCR) | 69.3% | Not measured | Only DeepSeek V3.1 Terminus measured |
| DTBench | 81.3% | Not measured | Only DeepSeek V3.1 Terminus measured |
| LMCA | 28.6% | Not measured | Only DeepSeek V3.1 Terminus 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 33 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Qwen3.5 Plus 2026-02-15 | 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
Qwen3.5 Plus 2026-02-15 costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 Plus 2026-02-15 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 | Qwen3.5 Plus 2026-02-15 |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | No public weights listed |
| Released | September 22, 2025 | February 16, 2026 |
| Context window | 164K | 1M |
| Input $/Mtok | $0.3063 | $0.26 |
| Output $/Mtok | $1.0142 | $1.56 |
| 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 Qwen3.5 Plus 2026-02-15 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 1.5x cheaper ($1.0142 vs $1.56 per million) and work measured by Design Arena: SVG, where it leads.
Which is cheaper, DeepSeek V3.1 Terminus or Qwen3.5 Plus 2026-02-15?
DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 per million output tokens; Qwen3.5 Plus 2026-02-15 costs $0.26 and $1.56. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.1 Terminus or Qwen3.5 Plus 2026-02-15?
Qwen3.5 Plus 2026-02-15, with 1M tokens against 164K.
How many benchmarks is the DeepSeek V3.1 Terminus vs Qwen3.5 Plus 2026-02-15 comparison based on?
7 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 Qwen3.5 Plus 2026-02-15's on 0. Where only one model has a result, the page says so instead of naming a winner.