Model comparison
DeepSeek-R1-Distill-Llama-70B vs Gemini 2.0 Flash-Lite
DeepSeek-R1-Distill-Llama-70B and Gemini 2.0 Flash-Lite score almost the same on the Noometry Index (37.8 vs 37.8), so choose on price, context window or the category you care about most.
Last verified . 7 shared benchmarks.
DeepSeek
GoogleSummary
- They share 7 benchmarks with published results for both. DeepSeek-R1-Distill-Llama-70B scores higher in 2 categories and Gemini 2.0 Flash-Lite in 4 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 2.0 Flash-Lite leads 35.0 to 30.7.
- The biggest single-benchmark swing is LiveBench Reasoning: 67.6% for DeepSeek-R1-Distill-Llama-70B and 50.1% for Gemini 2.0 Flash-Lite.
- DeepSeek-R1-Distill-Llama-70B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 37.8 | 37.8 |
| Released | 2025-01-20 | 2025-02-05 |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 13 | 32 |
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Category by category
Coding Gemini 2.0 Flash-Lite leads
DeepSeek-R1-Distill-Llama-70B: 36.8 (#202), Gemini 2.0 Flash-Lite: 37.9 (#185)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LiveBench Coding | 51.6% | 47.1% |
| BigCodeBench Instruct | 35.3% | — |
| LMArena Coding | — | 1322 |
| BigCodeBench Complete | 49.9% | — |
Reasoning DeepSeek-R1-Distill-Llama-70B leads
DeepSeek-R1-Distill-Llama-70B: 24.9 (#156), Gemini 2.0 Flash-Lite: 22.0 (#210)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LiveBench Reasoning | 67.6% | 50.1% |
| LiveBench Data Analysis | 55.9% | 65.5% |
| LiveBench | 54.5% | 54.3% |
| Kagi LLM Benchmark | 52.3% | — |
| LMArena Hard Prompts | — | 1324 |
| DTBench | — | 52.5% |
| ForecastBench | — | 57.1 |
Math DeepSeek-R1-Distill-Llama-70B leads
DeepSeek-R1-Distill-Llama-70B: 36.0 (#176), Gemini 2.0 Flash-Lite: 34.1 (#196)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LiveBench Math | 58.1% | 58.1% |
| OTIS Mock AIME 2024-2025 | 51.4% | — |
| Omni-MATH | — | 37.4% |
| LMArena Math | — | 1309 |
| MATH Level 5 | 89.9% | — |
Knowledge Gemini 2.0 Flash-Lite leads
DeepSeek-R1-Distill-Llama-70B: 30.7 (#225), Gemini 2.0 Flash-Lite: 35.0 (#189)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| GPQA Diamond | 55.7% | — |
| MMLU-Pro | — | 72% |
| GPQA (HELM) | — | 50% |
| LMArena Expert | — | 1305 |
Multimodal Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Gemini 2.0 Flash-Lite: 31.2 (#109)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Vision | — | 1100 |
Multilingual Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Gemini 2.0 Flash-Lite: 46.0 (#161)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Non-English | — | 1323 |
| LMArena Chinese | — | 1339 |
| LMArena French | — | 1347 |
| LMArena German | — | 1306 |
| LMArena Japanese | — | 1301 |
| LMArena Korean | — | 1325 |
| LMArena Russian | — | 1328 |
| LMArena Spanish | — | 1313 |
Instruction Following Gemini 2.0 Flash-Lite leads
DeepSeek-R1-Distill-Llama-70B: 68.2 (#190), Gemini 2.0 Flash-Lite: 70.4 (#163)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LiveBench Instruction Following | 69.9% | 78.3% |
| IFEval | — | 82.4% |
| LMArena Instruction Following | — | 1305 |
Long Context Not comparable
DeepSeek-R1-Distill-Llama-70B: —, Gemini 2.0 Flash-Lite: 40.1 (#160)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Longer Query | — | 1320 |
Writing & Preference Gemini 2.0 Flash-Lite leads
DeepSeek-R1-Distill-Llama-70B: 49.0 (#194), Gemini 2.0 Flash-Lite: 51.7 (#177)
| Benchmark | DeepSeek-R1-Distill-Llama-70B | Gemini 2.0 Flash-Lite |
|---|---|---|
| LiveBench Language | 23.8% | 34.3% |
| LMArena Text | — | 1330 |
| LMArena Creative Writing | — | 1319 |
| WildBench | — | 79% |
| LMArena Multi-Turn | — | 1307 |
Frequently asked questions
Is DeepSeek-R1-Distill-Llama-70B better than Gemini 2.0 Flash-Lite?
DeepSeek-R1-Distill-Llama-70B and Gemini 2.0 Flash-Lite score almost the same on the Noometry Index (37.8 vs 37.8), so choose on price, context window or the category you care about most.
Is DeepSeek-R1-Distill-Llama-70B or Gemini 2.0 Flash-Lite better for coding?
Gemini 2.0 Flash-Lite scores higher on coding benchmarks: 37.9 versus 36.8 in the Noometry coding category.
How many benchmarks do DeepSeek-R1-Distill-Llama-70B and Gemini 2.0 Flash-Lite share?
7 benchmarks have published results for both models. DeepSeek-R1-Distill-Llama-70B has 13 scored results on Noometry and Gemini 2.0 Flash-Lite has 32.