Model comparison
DeepSeek-R1-Distill-Qwen-1.5B vs Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 26.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
GoogleSummary
- The widest gap is in coding, where Gemini 2.5 Flash-Lite leads 38.5 to 21.8.
- DeepSeek-R1-Distill-Qwen-1.5B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 26.1 | 37.0 |
| Released | 2025-01-20 | 2025-06-17 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 5 | 33 |
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Category by category
Coding Gemini 2.5 Flash-Lite leads
DeepSeek-R1-Distill-Qwen-1.5B: 21.8 (#336), Gemini 2.5 Flash-Lite: 38.5 (#173)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| WeirdML | — | 35.2% |
| BigCodeBench Instruct | 7% | — |
| LMArena Coding | — | 1373 |
| BigCodeBench Complete | 7.9% | — |
| ALE-Bench | — | 325.9 |
Agentic & Tool Use Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Gemini 2.5 Flash-Lite: 28.0 (#96)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 36.9% |
Reasoning Gemini 2.5 Flash-Lite leads
DeepSeek-R1-Distill-Qwen-1.5B: 19.2 (#262), Gemini 2.5 Flash-Lite: 22.2 (#205)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| Kagi LLM Benchmark | — | 40.5% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | — | 1377 |
| DTBench | — | 62.8% |
| LMCA | — | 18.1% |
| Epoch Capabilities Index | — | 133.94 |
Math Gemini 2.5 Flash-Lite leads
DeepSeek-R1-Distill-Qwen-1.5B: 23.0 (#274), Gemini 2.5 Flash-Lite: 38.0 (#144)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 21.4% | — |
| Omni-MATH | — | 48% |
| LMArena Math | — | 1373 |
Knowledge Gemini 2.5 Flash-Lite leads
DeepSeek-R1-Distill-Qwen-1.5B: 16.0 (#290), Gemini 2.5 Flash-Lite: 32.5 (#210)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| GPQA Diamond | 33.6% | — |
| MMLU-Pro | — | 53.7% |
| Vectara Hallucination Rate | — | 3.3% |
| GPQA (HELM) | — | 30.9% |
| LMArena Expert | — | 1373 |
Multimodal Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Gemini 2.5 Flash-Lite: 29.1 (#114)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| LMArena Vision | — | 1198 |
| VPCT | — | 30% |
Multilingual Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Gemini 2.5 Flash-Lite: 49.3 (#134)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| LMArena Non-English | — | 1369 |
| LMArena Chinese | — | 1404 |
| LMArena French | — | 1388 |
| LMArena German | — | 1389 |
| LMArena Japanese | — | 1359 |
| LMArena Korean | — | 1360 |
| LMArena Russian | — | 1373 |
| LMArena Spanish | — | 1396 |
Instruction Following Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Gemini 2.5 Flash-Lite: 70.0 (#168)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| IFEval | — | 81% |
| LMArena Instruction Following | — | 1367 |
Long Context Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Gemini 2.5 Flash-Lite: 33.3 (#262)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| Fiction.LiveBench | — | 47.2% |
| LMArena Longer Query | — | 1373 |
Writing & Preference Not comparable
DeepSeek-R1-Distill-Qwen-1.5B: —, Gemini 2.5 Flash-Lite: 56.8 (#135)
| Benchmark | DeepSeek-R1-Distill-Qwen-1.5B | Gemini 2.5 Flash-Lite |
|---|---|---|
| LMArena Text | — | 1379 |
| LMArena Creative Writing | — | 1367 |
| WildBench | — | 81.8% |
| LMArena Multi-Turn | — | 1366 |
Frequently asked questions
Is DeepSeek-R1-Distill-Qwen-1.5B better than Gemini 2.5 Flash-Lite?
Gemini 2.5 Flash-Lite is the stronger model overall, scoring 37.0 to 26.1 on the Noometry Index.
Is DeepSeek-R1-Distill-Qwen-1.5B or Gemini 2.5 Flash-Lite better for coding?
Gemini 2.5 Flash-Lite scores higher on coding benchmarks: 38.5 versus 21.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Qwen-1.5B and Gemini 2.5 Flash-Lite share?
0 benchmarks have published results for both models. DeepSeek-R1-Distill-Qwen-1.5B has 5 scored results on Noometry and Gemini 2.5 Flash-Lite has 33.