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DeepSeek DeepSeek V3.1 Terminus VS Qwen Qwen3.5 Plus 2026-02-15

DeepSeek V3.1 Terminus vs Qwen3.5 Plus 2026-02-15: which wins at real work?

22 task areas · same graded test runs · rank comparison only, so 0–100 and Elo collections never mix raw scores.

Qwen3.5 Plus 2026-02-15 wins 18 of 22 task areas we tested; DeepSeek V3.1 Terminus takes 4. DeepSeek V3.1 Terminus costs 1.5× less per token ($1.22 vs $1.82 per 1M).

4
Task areas won
18
36
Avg percentile
68
0
Top-3 finishes
1
$1.22
Price / 1M tokens
$1.82
DeepSeek
Provider
Qwen

DeepSeek V3.1 Terminus costs 1.5× less per token ($1.22 vs $1.82 per 1M).

Task by task

Task area DeepSeek V3.1 Terminus Qwen3.5 Plus 2026-02-15 Winner
Translation & Localization #101 / 110
Strong
#10 / 110
Excellent
Qwen3.5 Plus 2026-02-15
Legal & HR #95 / 110
Strong
#13 / 110
Excellent
Qwen3.5 Plus 2026-02-15
RAG, Safety & Grounding #85 / 113
Excellent
#7 / 113
Excellent
Qwen3.5 Plus 2026-02-15
Sales #97 / 110
Needs editing
#27 / 110
Strong
Qwen3.5 Plus 2026-02-15
AI Strategy #101 / 126
Usable
#32 / 126
Strong
Qwen3.5 Plus 2026-02-15
Chef / Home Cooking #95 / 126
Usable
#40 / 126
Usable
Qwen3.5 Plus 2026-02-15
Content & Brand #100 / 124
Usable
#45 / 124
Strong
Qwen3.5 Plus 2026-02-15
Customer Support #69 / 113
Usable
#18 / 113
Strong
Qwen3.5 Plus 2026-02-15
Presentations & Decks #91 / 110
Strong
#40 / 110
Excellent
Qwen3.5 Plus 2026-02-15
Structured Output #63 / 113
Excellent
#18 / 113
Excellent
Qwen3.5 Plus 2026-02-15
Data & Analytics #56 / 110
Excellent
#26 / 110
Excellent
Qwen3.5 Plus 2026-02-15
Frontend & Landing Pages #33 / 109
Needs editing
#3 / 109
Usable
Qwen3.5 Plus 2026-02-15
Investor & Pitch #64 / 66
Needs editing
#36 / 66
Usable
Qwen3.5 Plus 2026-02-15
Research & Competitive Analysis #46 / 110
Strong
#73 / 110
Usable
DeepSeek V3.1 Terminus
Training & Education #31 / 110
Excellent
#6 / 110
Excellent
Qwen3.5 Plus 2026-02-15
Coding #92 / 115
Usable
#71 / 115
Strong
Qwen3.5 Plus 2026-02-15
Creative & Comedy #89 / 110 #71 / 110 Qwen3.5 Plus 2026-02-15
Executive Assistant #77 / 112
Usable
#61 / 112
Strong
Qwen3.5 Plus 2026-02-15
Summarization & Meeting Notes #32 / 110
Excellent
#46 / 110
Excellent
DeepSeek V3.1 Terminus
Landing Pages #44 / 72
Strong
#36 / 72
Strong
Qwen3.5 Plus 2026-02-15
Product & Project Management #36 / 110
Strong
#40 / 110
Strong
DeepSeek V3.1 Terminus
Knowledge & Docs #50 / 110
Usable
#51 / 110
Usable
DeepSeek V3.1 Terminus

Rank = position among every model config we tested in that task area (lower is better). Sorted by biggest gap first.

Frequently asked

Is DeepSeek V3.1 Terminus better than Qwen3.5 Plus 2026-02-15?

Across 22 task areas we benchmarked, Qwen3.5 Plus 2026-02-15 ranks higher in 18 and DeepSeek V3.1 Terminus in 4.

Which is cheaper, DeepSeek V3.1 Terminus or Qwen3.5 Plus 2026-02-15?

DeepSeek V3.1 Terminus costs 1.5× less per token ($1.22 vs $1.82 per 1M).

What is DeepSeek V3.1 Terminus better at?

DeepSeek V3.1 Terminus out-ranks Qwen3.5 Plus 2026-02-15 at Research & Competitive Analysis, Summarization & Meeting Notes, Product & Project Management.

What is Qwen3.5 Plus 2026-02-15 better at?

Qwen3.5 Plus 2026-02-15 out-ranks DeepSeek V3.1 Terminus at Translation & Localization, Legal & HR, RAG, Safety & Grounding.

Full DeepSeek V3.1 Terminus review → Full Qwen3.5 Plus 2026-02-15 review → Full model leaderboard →

More comparisons

This page is Spring Prompt, running in public

We just did this for every model. Do it for your prompt.

The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.

  • Generate test cases from your prompt — no eval set required to start.
  • Compare models side by side with quality, cost and latency in one matrix.
  • Optimise the winner until the scores say it's ready to ship.
Experiment · Cold outreach email

Prompt × model results

12 test cases · 3 evals
Claude Opus
GPT-5
Gemini
v1
7.1
6.8
7.4
v2
8.3
7.9
8.0
v3
9.2
8.6
8.4
Best combo: v3 × Claude Opus
9.2 quality · $0.004/run · 1.8s