Model comparison
DeepSeek-R1-Distill-Qwen-1.5B vs DeepSeek-R1-Distill-Qwen-32B
DeepSeek-R1-Distill-Qwen-32B is the stronger model overall, scoring 35.5 to 26.1 on the Noometry Index.
Last verified . 5 shared benchmarks.
DeepSeekSummary
- They share 5 benchmarks with published results for both. DeepSeek-R1-Distill-Qwen-1.5B scores higher in 1 category and DeepSeek-R1-Distill-Qwen-32B in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-R1-Distill-Qwen-32B leads 35.7 to 16.0.
- The biggest single-benchmark swing is BigCodeBench Complete: 7.9% for DeepSeek-R1-Distill-Qwen-1.5B and 54.9% for DeepSeek-R1-Distill-Qwen-32B.
Side by side
| DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B | |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Noometry Index | 26.1 | 35.5 |
| Released | 2025-01-20 | 2025-01-20 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 5 | 14 |
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Category by category
Coding DeepSeek-R1-Distill-Qwen-32B leads
DeepSeek-R1-Distill-Qwen-1.5B: 21.8 (#336), DeepSeek-R1-Distill-Qwen-32B: 36.1 (#212)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B |
|---|---|---|
| BigCodeBench Instruct | 7% | 43.9% |
| BigCodeBench Complete | 7.9% | 54.9% |
| LiveBench Coding | — | 33.7% |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, DeepSeek-R1-Distill-Qwen-32B: 28.1 (#94)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B |
|---|---|---|
| BALROG | — | 19.5% |
Reasoning Too close to call
DeepSeek-R1-Distill-Qwen-1.5B: 19.2 (#262), DeepSeek-R1-Distill-Qwen-32B: 18.2 (#284)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B |
|---|---|---|
| Chess Puzzles | 0% | 1% |
| LiveBench Reasoning | — | 52.3% |
| LiveBench Data Analysis | — | 45.4% |
| Epoch Capabilities Index | — | 137.44 |
| LiveBench | — | 45.5% |
Math DeepSeek-R1-Distill-Qwen-32B leads
DeepSeek-R1-Distill-Qwen-1.5B: 23.0 (#274), DeepSeek-R1-Distill-Qwen-32B: 34.5 (#194)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 21.4% | 55.6% |
| LiveBench Math | — | 59.4% |
Knowledge DeepSeek-R1-Distill-Qwen-32B leads
DeepSeek-R1-Distill-Qwen-1.5B: 16.0 (#290), DeepSeek-R1-Distill-Qwen-32B: 35.7 (#182)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B |
|---|---|---|
| GPQA Diamond | 33.6% | 64.1% |
Instruction Following Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, DeepSeek-R1-Distill-Qwen-32B: 61.6 (#243)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B |
|---|---|---|
| LiveBench Instruction Following | — | 55.7% |
Writing & Preference Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, DeepSeek-R1-Distill-Qwen-32B: 49.6 (#188)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | DeepSeek-R1-Distill-Qwen-32B |
|---|---|---|
| LiveBench Language | — | 26.8% |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-1.5B better than DeepSeek-R1-Distill-Qwen-32B?
DeepSeek-R1-Distill-Qwen-32B is the stronger model overall, scoring 35.5 to 26.1 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-1.5B or DeepSeek-R1-Distill-Qwen-32B better for coding?
DeepSeek-R1-Distill-Qwen-32B scores higher on coding benchmarks: 36.1 versus 21.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Qwen-1.5B and DeepSeek-R1-Distill-Qwen-32B share?
5 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-1.5B has 5 scored results on Noometry and DeepSeek-R1-Distill-Qwen-32B has 14.