Model comparison
DeepSeek-V3.1-Terminus vs Qwen3.6 Plus
Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 43.1 on the Noometry Index. DeepSeek-V3.1-Terminus costs 2.5× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Last verified . 15 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 15 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 1 category and Qwen3.6 Plus in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.6 Plus leads 51.8 to 38.5.
- DeepSeek-V3.1-Terminus is cheaper at $0.27 / $1 per million input/output tokens, against $0.50 / $3 for Qwen3.6 Plus.
- Qwen3.6 Plus accepts more context: 1M tokens versus 164K.
- DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1-Terminus | Qwen3.6 Plus | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 43.1 | 47.5 |
| Released | 2025-09-22 | 2026-03-31 |
| Weights | Open | Proprietary |
| Context window | 164K | 1M |
| Max output | 147K | 66K |
| Input $ / M tokens | $0.27 | $0.50 |
| Output $ / M tokens | $1 | $3 |
| Results tracked | 16 | 37 |
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Category by category
Coding DeepSeek-V3.1-Terminus leads
DeepSeek-V3.1-Terminus: 42.0 (#113), Qwen3.6 Plus: 40.8 (#130)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| SciCode | 40.6% | 40.7% |
| LMArena Coding | 1426 | 1467 |
| ALE-Bench | 745.17 | 670.15 |
| SWE-bench Verified | — | 57.9% |
| LMArena WebDev | — | 1461 |
Agentic & Tool Use Not comparable
DeepSeek-V3.1-Terminus: —, Qwen3.6 Plus: —
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| Vending-Bench 2 | — | 5,115 |
Reasoning Qwen3.6 Plus leads
DeepSeek-V3.1-Terminus: 26.4 (#133), Qwen3.6 Plus: 29.3 (#93)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| CritPt | 1.7% | 2.9% |
| LMArena Hard Prompts | 1426 | 1449 |
| DTBench | 81.3% | 81.9% |
| LMCA | 28.6% | 33.1% |
| Kagi LLM Benchmark | 57.4% | — |
| NYT Connections (extended) | — | 60.3% |
| Chess Puzzles | — | 17% |
| Thematic Generalization | — | 59.5% |
| Mystery Game Puzzles | — | 12% |
| Epoch Capabilities Index | — | 147.65 |
Math Qwen3.6 Plus leads
DeepSeek-V3.1-Terminus: 38.5 (#137), Qwen3.6 Plus: 51.8 (#54)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| LMArena Math | 1402 | 1450 |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| OTIS Mock AIME 2024-2025 | — | 93.3% |
| FrontierMath (Feb 2025 set) | — | 26.2% |
| FrontierMath Tier 4 (v1) | — | 8.3% |
Knowledge Not comparable
DeepSeek-V3.1-Terminus: —, Qwen3.6 Plus: 56.1 (#45)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | — | 88.4% |
| SimpleQA Verified | — | 44.1% |
| LMArena Expert | — | 1454 |
Multilingual Qwen3.6 Plus leads
DeepSeek-V3.1-Terminus: 52.1 (#92), Qwen3.6 Plus: 53.3 (#70)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 1407 | 1424 |
| LMArena Russian | 1436 | 1434 |
| LMArena Chinese | — | 1477 |
| LMArena French | — | 1455 |
| LMArena German | — | 1452 |
| LMArena Japanese | — | 1389 |
| LMArena Korean | — | 1379 |
| LMArena Spanish | — | 1432 |
Instruction Following Qwen3.6 Plus leads
DeepSeek-V3.1-Terminus: 74.0 (#106), Qwen3.6 Plus: 75.0 (#74)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1404 | 1425 |
Long Context Qwen3.6 Plus leads
DeepSeek-V3.1-Terminus: 43.4 (#97), Qwen3.6 Plus: 45.2 (#49)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| LMArena Longer Query | 1421 | 1439 |
| CL-bench | — | 20.3% |
Writing & Preference Qwen3.6 Plus leads
DeepSeek-V3.1-Terminus: 61.0 (#92), Qwen3.6 Plus: 62.2 (#82)
| Benchmark | DeepSeek-V3.1-Terminus | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1419 | 1437 |
| LMArena Creative Writing | 1403 | 1404 |
| LMArena Multi-Turn | 1411 | 1438 |
Frequently asked questions
Is DeepSeek-V3.1-Terminus better than Qwen3.6 Plus?
Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 43.1 on the Noometry Index. DeepSeek-V3.1-Terminus costs 2.5× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.1-Terminus or Qwen3.6 Plus?
DeepSeek-V3.1-Terminus is cheaper. It lists at $0.27 per million input tokens and $1 per million output tokens; Qwen3.6 Plus lists at $0.50 and $3.
Is DeepSeek-V3.1-Terminus or Qwen3.6 Plus better for coding?
DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 42.0 versus 40.8 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 Plus does, with 1M tokens against 164K.
How many benchmarks do DeepSeek-V3.1-Terminus and Qwen3.6 Plus share?
15 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Qwen3.6 Plus has 37.