Model comparison
DeepSeek-V2.5 (Sep 2024) vs Gemini 2.0 Flash-Lite
DeepSeek-V2.5 (Sep 2024) and Gemini 2.0 Flash-Lite score almost the same on the Noometry Index (37.6 vs 37.8), so choose on price, context window or the category you care about most.
Last verified . 17 shared benchmarks.
DeepSeek
GoogleSummary
- They share 17 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 2 categories and Gemini 2.0 Flash-Lite in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where Gemini 2.0 Flash-Lite leads 37.9 to 31.7.
- DeepSeek-V2.5 (Sep 2024) has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 37.6 | 37.8 |
| Released | 2024-09-06 | 2025-02-05 |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 22 | 32 |
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Category by category
Coding Gemini 2.0 Flash-Lite leads
DeepSeek-V2.5 (Sep 2024): 31.7 (#281), Gemini 2.0 Flash-Lite: 37.9 (#185)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Coding | 1309 | 1322 |
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Reasoning DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 25.6 (#145), Gemini 2.0 Flash-Lite: 22.0 (#210)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1324 |
| LiveBench Reasoning | — | 50.1% |
| DTBench | — | 52.5% |
| LiveBench Data Analysis | — | 65.5% |
| ForecastBench | — | 57.1 |
| LiveBench | — | 54.3% |
Math DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 35.9 (#177), Gemini 2.0 Flash-Lite: 34.1 (#196)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Math | 1288 | 1309 |
| Omni-MATH | — | 37.4% |
| LiveBench Math | — | 58.1% |
Knowledge Too close to call
DeepSeek-V2.5 (Sep 2024): 34.8 (#193), Gemini 2.0 Flash-Lite: 35.0 (#189)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Expert | 1266 | 1305 |
| MMLU-Pro | — | 72% |
| GPQA (HELM) | — | 50% |
Multimodal Not comparable
DeepSeek-V2.5 (Sep 2024): —, Gemini 2.0 Flash-Lite: 31.2 (#109)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Vision | — | 1100 |
Multilingual Gemini 2.0 Flash-Lite leads
DeepSeek-V2.5 (Sep 2024): 42.5 (#193), Gemini 2.0 Flash-Lite: 46.0 (#161)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Non-English | 1273 | 1323 |
| LMArena Chinese | 1318 | 1339 |
| LMArena French | 1289 | 1347 |
| LMArena German | 1258 | 1306 |
| LMArena Japanese | 1228 | 1301 |
| LMArena Korean | 1209 | 1325 |
| LMArena Russian | 1289 | 1328 |
| LMArena Spanish | 1248 | 1313 |
Instruction Following Gemini 2.0 Flash-Lite leads
DeepSeek-V2.5 (Sep 2024): 67.5 (#194), Gemini 2.0 Flash-Lite: 70.4 (#163)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Instruction Following | 1280 | 1305 |
| LiveBench Instruction Following | — | 78.3% |
| IFEval | — | 82.4% |
Long Context Too close to call
DeepSeek-V2.5 (Sep 2024): 39.5 (#174), Gemini 2.0 Flash-Lite: 40.1 (#160)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Longer Query | 1301 | 1320 |
Writing & Preference Gemini 2.0 Flash-Lite leads
DeepSeek-V2.5 (Sep 2024): 49.8 (#187), Gemini 2.0 Flash-Lite: 51.7 (#177)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash-Lite |
|---|---|---|
| LMArena Text | 1294 | 1330 |
| LMArena Creative Writing | 1285 | 1319 |
| LMArena Multi-Turn | 1297 | 1307 |
| WildBench | — | 79% |
| LiveBench Language | — | 34.3% |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Gemini 2.0 Flash-Lite?
DeepSeek-V2.5 (Sep 2024) and Gemini 2.0 Flash-Lite score almost the same on the Noometry Index (37.6 vs 37.8), so choose on price, context window or the category you care about most.
Is DeepSeek-V2.5 (Sep 2024) or Gemini 2.0 Flash-Lite better for coding?
Gemini 2.0 Flash-Lite scores higher on coding benchmarks: 37.9 versus 31.7 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Gemini 2.0 Flash-Lite share?
17 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Gemini 2.0 Flash-Lite has 32.