Model comparison
DeepSeek-R1-Distill-Qwen-1.5B vs Qwen3.6 35B-A3B
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 26.1 on the Noometry Index.
Last verified . 3 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both. DeepSeek-R1-Distill-Qwen-1.5B scores higher in 0 categories and Qwen3.6 35B-A3B in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 35B-A3B leads 51.3 to 16.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 21.4% for DeepSeek-R1-Distill-Qwen-1.5B and 86.7% for Qwen3.6 35B-A3B.
Side by side
| DeepSeek-R1-Distill-Qwen-1.5B | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 26.1 | 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 | 5 | 14 |
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Category by category
Coding Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-1.5B: 21.8 (#336), Qwen3.6 35B-A3B: 37.2 (#196)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3.6 35B-A3B |
|---|---|---|
| SciCode | — | 35.8% |
| WeirdML | — | 34.5% |
| BigCodeBench Instruct | 7% | — |
| BigCodeBench Complete | 7.9% | — |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Qwen3.6 35B-A3B: 22.1 (#134)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
Reasoning Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-1.5B: 19.2 (#262), Qwen3.6 35B-A3B: 28.0 (#109)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3.6 35B-A3B |
|---|---|---|
| Chess Puzzles | 0% | 26% |
| NYT Connections (extended) | — | 41.6% |
| CritPt | — | 0.3% |
| Mystery Game Puzzles | — | 22% |
| DTBench | — | 73.9% |
| LMCA | — | 29.7% |
| Surface Evolver Bench | — | 44.4% |
| Epoch Capabilities Index | — | 143.93 |
Math Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-1.5B: 23.0 (#274), Qwen3.6 35B-A3B: 38.9 (#121)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3.6 35B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 21.4% | 86.7% |
| FrontierMath (Tiers 1-3) | — | 20.4% |
Knowledge Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-1.5B: 16.0 (#290), Qwen3.6 35B-A3B: 51.3 (#68)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | 33.6% | 84.8% |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-1.5B better than Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 26.1 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-1.5B or Qwen3.6 35B-A3B better for coding?
Qwen3.6 35B-A3B scores higher on coding benchmarks: 37.2 versus 21.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Qwen-1.5B and Qwen3.6 35B-A3B share?
3 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-1.5B has 5 scored results on Noometry and Qwen3.6 35B-A3B has 14.