# DeepSeek-V3.2-Exp vs Qwen3.6 Plus

> Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 44.3 on the Noometry Index. DeepSeek-V3.2-Exp costs 3.9× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-exp-vs-qwen3-6-plus
- Last updated: 2026-10-12
- Shared benchmarks: 32

## Summary

- They share 32 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 3 categories and Qwen3.6 Plus in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.6 Plus leads 51.8 to 41.7.
- The biggest single-benchmark swing is NYT Connections (extended): 36.7% for DeepSeek-V3.2-Exp and 60.3% for Qwen3.6 Plus.
- DeepSeek-V3.2-Exp is cheaper at $0.26 / $0.38 per million input/output tokens, against $0.50 / $3 for Qwen3.6 Plus.
- Qwen3.6 Plus accepts more context: 1M tokens versus 164K.
- DeepSeek-V3.2-Exp has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 44.3 | 47.5 |
| Rank | 78 | 62 |
| Context | 164K | 1M |
| Input $/M | $0.26 | $0.50 |
| Output $/M | $0.38 | $3 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.2-Exp: 46.5 (#65)
- Qwen3.6 Plus: 40.8 (#130)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| LMArena WebDev | 1362 | 1461 |
| SciCode | 38.9% | 40.7% |
| LMArena Coding | 1454 | 1467 |
| SWE-bench Verified | — | 57.9% |
| SWE-bench Verified (bash only) | 70% | — |
| Aider Polyglot | 74.2% | — |
| SWE-bench Multilingual | 59% | — |
| WeirdML | 39.5% | — |
| ALE-Bench | — | 670.15 |

## Agentic & Tool Use

- DeepSeek-V3.2-Exp: 32.7 (#59)
- Qwen3.6 Plus: —

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| Vending-Bench 2 | 1,034 | 5,115 |
| Terminal-Bench | 39.6% | — |
| APEX-Agents | 21.3% | — |
| Berkeley Function Calling Leaderboard | 56.7% | — |
| TheAgentCompany | 42.9% | — |

## Reasoning

- DeepSeek-V3.2-Exp: 22.1 (#208)
- Qwen3.6 Plus: 29.3 (#93)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| NYT Connections (extended) | 36.7% | 60.3% |
| CritPt | 2.9% | 2.9% |
| Chess Puzzles | 14% | 17% |
| Thematic Generalization | 65% | 59.5% |
| LMArena Hard Prompts | 1434 | 1449 |
| DTBench | 87.7% | 81.9% |
| LMCA | 29.1% | 33.1% |
| Epoch Capabilities Index | 146.27 | 147.65 |
| ARC-AGI-2 | 4% | — |
| Kagi LLM Benchmark | 52.2% | — |
| ARC-AGI-1 | 57% | — |
| Mystery Game Puzzles | — | 12% |

## Math

- DeepSeek-V3.2-Exp: 41.7 (#87)
- Qwen3.6 Plus: 51.8 (#54)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 87.8% | 93.3% |
| LMArena Math | 1435 | 1450 |
| FrontierMath (Feb 2025 set) | 22.1% | 26.2% |
| FrontierMath Tier 4 (v1) | 2.1% | 8.3% |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| MathArena Final-Answer Competitions | 57.7% | — |
| ProofBench | 8% | — |

## Knowledge

- DeepSeek-V3.2-Exp: 51.7 (#66)
- Qwen3.6 Plus: 56.1 (#45)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | 83.4% | 88.4% |
| LMArena Expert | 1436 | 1454 |
| SimpleQA Verified | — | 44.1% |
| Vectara Hallucination Rate | 5.3% | — |

## Multilingual

- DeepSeek-V3.2-Exp: 52.2 (#90)
- Qwen3.6 Plus: 53.3 (#70)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 1409 | 1424 |
| LMArena Chinese | 1461 | 1477 |
| LMArena French | 1433 | 1455 |
| LMArena German | 1440 | 1452 |
| LMArena Japanese | 1374 | 1389 |
| LMArena Korean | 1371 | 1379 |
| LMArena Russian | 1424 | 1434 |
| LMArena Spanish | 1440 | 1432 |

## Instruction Following

- DeepSeek-V3.2-Exp: 74.5 (#93)
- Qwen3.6 Plus: 75.0 (#74)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1413 | 1425 |

## Long Context

- DeepSeek-V3.2-Exp: 47.6 (#16)
- Qwen3.6 Plus: 45.2 (#49)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| CL-bench | 13.2% | 20.3% |
| LMArena Longer Query | 1428 | 1439 |
| Fiction.LiveBench | 83.3% | — |
| CL-bench Life | 9.5% | — |

## Writing & Preference

- DeepSeek-V3.2-Exp: 62.4 (#77)
- Qwen3.6 Plus: 62.2 (#82)

| Benchmark | DeepSeek-V3.2-Exp | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1425 | 1437 |
| LMArena Creative Writing | 1403 | 1404 |
| LMArena Multi-Turn | 1427 | 1438 |
| EQ-Bench Creative Writing | 1515 | — |

## FAQ

### Is DeepSeek-V3.2-Exp better than Qwen3.6 Plus?

Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 44.3 on the Noometry Index. DeepSeek-V3.2-Exp costs 3.9× 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-V3.2-Exp or Qwen3.6 Plus?

DeepSeek-V3.2-Exp is cheaper. It lists at $0.26 per million input tokens and $0.38 per million output tokens; Qwen3.6 Plus lists at $0.50 and $3.

### Is DeepSeek-V3.2-Exp or Qwen3.6 Plus better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 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-V3.2-Exp and Qwen3.6 Plus share?

32 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 49 scored results on Noometry and Qwen3.6 Plus has 37.