Model comparison
DeepSeek-R1-Distill-Qwen-14B vs Qwen3.6 35B-A3B
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 32.7 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-14B scores higher in 0 categories and Qwen3.6 35B-A3B in 4 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 35B-A3B leads 51.3 to 24.1.
- The biggest single-benchmark swing is GPQA Diamond: 44.7% for DeepSeek-R1-Distill-Qwen-14B and 84.8% for Qwen3.6 35B-A3B.
Side by side
| DeepSeek-R1-Distill-Qwen-14B | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 32.7 | 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 | 7 | 14 |
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Category by category
Coding Too close to call
DeepSeek-R1-Distill-Qwen-14B: 36.9 (#200), Qwen3.6 35B-A3B: 37.2 (#196)
| Benchmark | DeepSeek-R1-Distill-Qwen-14B | Qwen3.6 35B-A3B |
|---|---|---|
| SciCode | — | 35.8% |
| WeirdML | — | 34.5% |
| BigCodeBench Instruct | 38.1% | — |
| BigCodeBench Complete | 48.4% | — |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Qwen-14B: —, Qwen3.6 35B-A3B: 22.1 (#134)
| Benchmark | DeepSeek-R1-Distill-Qwen-14B | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
Reasoning Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-14B: 19.2 (#263), Qwen3.6 35B-A3B: 28.0 (#109)
| Benchmark | DeepSeek-R1-Distill-Qwen-14B | Qwen3.6 35B-A3B |
|---|---|---|
| Chess Puzzles | 1% | 26% |
| Epoch Capabilities Index | 135.43 | 143.93 |
| NYT Connections (extended) | — | 41.6% |
| CritPt | — | 0.3% |
| Mystery Game Puzzles | — | 22% |
| DTBench | — | 73.9% |
| LMCA | — | 29.7% |
| Surface Evolver Bench | — | 44.4% |
Math Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-14B: 35.5 (#184), Qwen3.6 35B-A3B: 38.9 (#121)
| Benchmark | DeepSeek-R1-Distill-Qwen-14B | Qwen3.6 35B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 50.6% | 86.7% |
| FrontierMath (Tiers 1-3) | — | 20.4% |
| MATH Level 5 | 87.1% | — |
Knowledge Qwen3.6 35B-A3B leads
DeepSeek-R1-Distill-Qwen-14B: 24.1 (#270), Qwen3.6 35B-A3B: 51.3 (#68)
| Benchmark | DeepSeek-R1-Distill-Qwen-14B | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | 44.7% | 84.8% |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-14B better than Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is the stronger model overall, scoring 37.6 to 32.7 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-14B or Qwen3.6 35B-A3B better for coding?
They score almost the same on coding (36.9 vs 37.2); test both on your own repository before choosing.
How many benchmarks do DeepSeek-R1-Distill-Qwen-14B and Qwen3.6 35B-A3B share?
4 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-14B has 7 scored results on Noometry and Qwen3.6 35B-A3B has 14.