Model comparison
DeepSeek-R1-Distill-Qwen-32B vs Qwen3.6 35B-A3B
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 35.5 on the Noometry Index.
Last verified . 4 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both. DeepSeek-R1-Distill-Qwen-32B scores higher in 1 category and Qwen3.6 35B-A3B in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 35B-A3B leads 51.3 to 35.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 55.6% for DeepSeek-R1-Distill-Qwen-32B and 86.7% for Qwen3.6 35B-A3B.
Side by side
| DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 35.5 | 37.6 |
| Released | 2025-01-20 | 2026-04-01 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.25 |
| Output $ / M tokens | — | $1.49 |
| Results tracked | 14 | 14 |
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Category by category
Coding Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-32B: 36.1 (#212), Qwen3.6 35B-A3B: 37.2 (#196)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B |
|---|---|---|
| SciCode | — | 35.8% |
| WeirdML | — | 34.5% |
| BigCodeBench Instruct | 43.9% | — |
| LiveBench Coding | 33.7% | — |
| BigCodeBench Complete | 54.9% | — |
Agentic & Tool Use DeepSeek-R1-Distill-Qwen-32B leads
DeepSeek-R1-Distill-Qwen-32B: 28.1 (#94), Qwen3.6 35B-A3B: 22.1 (#134)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
| BALROG | 19.5% | — |
Reasoning Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-32B: 18.2 (#284), Qwen3.6 35B-A3B: 28.0 (#109)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B |
|---|---|---|
| Chess Puzzles | 1% | 26% |
| Epoch Capabilities Index | 137.44 | 143.93 |
| NYT Connections (extended) | — | 41.6% |
| CritPt | — | 0.3% |
| LiveBench Reasoning | 52.3% | — |
| Mystery Game Puzzles | — | 22% |
| DTBench | — | 73.9% |
| LiveBench Data Analysis | 45.4% | — |
| LMCA | — | 29.7% |
| Surface Evolver Bench | — | 44.4% |
| LiveBench | 45.5% | — |
Math Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-32B: 34.5 (#194), Qwen3.6 35B-A3B: 38.9 (#121)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 55.6% | 86.7% |
| FrontierMath (Tiers 1-3) | — | 20.4% |
| LiveBench Math | 59.4% | — |
Knowledge Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-32B: 35.7 (#182), Qwen3.6 35B-A3B: 51.3 (#68)
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | 64.1% | 84.8% |
Instruction Following Not comparable
DeepSeek-R1-Distill-Qwen-32B: 61.6 (#243), Qwen3.6 35B-A3B: —
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B |
|---|---|---|
| LiveBench Instruction Following | 55.7% | — |
Writing & Preference Not comparable
DeepSeek-R1-Distill-Qwen-32B: 49.6 (#188), Qwen3.6 35B-A3B: —
| Benchmark | DeepSeek-R1-Distill-Qwen-32B | Qwen3.6 35B-A3B |
|---|---|---|
| LiveBench Language | 26.8% | — |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-32B better than Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 35.5 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-32B or Qwen3.6 35B-A3B better for coding?
Qwen3.6 35B-A3B scores higher on coding benchmarks: 37.2 versus 36.1 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Qwen-32B and Qwen3.6 35B-A3B share?
4 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-32B has 14 scored results on Noometry and Qwen3.6 35B-A3B has 14.