Model comparison
DeepSeek-R1-Distill-Qwen-1.5B vs Qwen3 235B-A22B
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 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 1 category and Qwen3 235B-A22B in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 235B-A22B leads 49.6 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 235B-A22B.
Side by side
| DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 26.1 | 43.5 |
| Released | 2025-01-20 | 2025-04 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 16K |
| Input $ / M tokens | — | $0.70 |
| Output $ / M tokens | — | $2.80 |
| Results tracked | 5 | 49 |
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Category by category
Coding Qwen3 235B-A22B leads
DeepSeek-R1-Distill-Qwen-1.5B: 21.8 (#336), Qwen3 235B-A22B: 44.3 (#75)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| Aider Polyglot | — | 59.6% |
| SciCode | — | 42.4% |
| WeirdML | — | 41% |
| BigCodeBench Instruct | 7% | — |
| LMArena Coding | — | 1445 |
| BigCodeBench Complete | 7.9% | — |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Qwen3 235B-A22B: 33.9 (#51)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 52.1% |
| Vending-Bench 2 | — | -11.34 |
Reasoning DeepSeek-R1-Distill-Qwen-1.5B leads
DeepSeek-R1-Distill-Qwen-1.5B: 19.2 (#262), Qwen3 235B-A22B: 15.7 (#311)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| Chess Puzzles | 0% | 12% |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31% |
| Kagi LLM Benchmark | — | 69.4% |
| ARC-AGI-1 | — | 11% |
| CritPt | — | 0% |
| LMArena Hard Prompts | — | 1433 |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 80.3% |
| LMCA | — | 29.3% |
| Epoch Capabilities Index | — | 143.85 |
| ForecastBench | — | 59.7 |
Math Qwen3 235B-A22B leads
DeepSeek-R1-Distill-Qwen-1.5B: 23.0 (#274), Qwen3 235B-A22B: 50.4 (#57)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 21.4% | 86.7% |
| Omni-MATH | — | 71.8% |
| LMArena Math | — | 1432 |
| MATH Level 5 | — | 68.9% |
| FrontierMath (Feb 2025 set) | — | 8.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3 235B-A22B leads
DeepSeek-R1-Distill-Qwen-1.5B: 16.0 (#290), Qwen3 235B-A22B: 49.6 (#73)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| GPQA Diamond | 33.6% | 80.1% |
| SimpleQA Verified | — | 40.4% |
| MMLU-Pro | — | 84.4% |
| Confabulations | — | 15.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 72.7% |
| LMArena Expert | — | 1463 |
Multilingual Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Qwen3 235B-A22B: 52.3 (#89)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | — | 1409 |
| LMArena Chinese | — | 1481 |
| LMArena French | — | 1445 |
| LMArena German | — | 1433 |
| LMArena Japanese | — | 1399 |
| LMArena Korean | — | 1391 |
| LMArena Russian | — | 1411 |
| LMArena Spanish | — | 1430 |
Instruction Following Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Qwen3 235B-A22B: 72.6 (#136)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| IFEval | — | 83.5% |
| LMArena Instruction Following | — | 1408 |
Long Context Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Qwen3 235B-A22B: 46.1 (#26)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| Fiction.LiveBench | — | 75% |
| LMArena Longer Query | — | 1426 |
Writing & Preference Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Qwen3 235B-A22B: 59.6 (#108)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | — | 1419 |
| LMArena Creative Writing | — | 1384 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1366 |
| WildBench | — | 86.6% |
| LMArena Multi-Turn | — | 1432 |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-1.5B better than Qwen3 235B-A22B?
Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 26.1 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-1.5B or Qwen3 235B-A22B better for coding?
Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 21.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Qwen-1.5B and Qwen3 235B-A22B share?
3 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-1.5B has 5 scored results on Noometry and Qwen3 235B-A22B has 49.