Model comparison
DeepSeek-V2.5 (Sep 2024) vs Gemini 2.0 Flash (Feb 2025)
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 35.1 on the Noometry Index.
Last verified . 20 shared benchmarks.
DeepSeek
GoogleSummary
- They share 20 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 5 categories and Gemini 2.0 Flash (Feb 2025) in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V2.5 (Sep 2024) leads 25.6 to 15.2.
- The biggest single-benchmark swing is Aider Polyglot: 17.8% for DeepSeek-V2.5 (Sep 2024) and 38.2% for Gemini 2.0 Flash (Feb 2025).
- 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 (Feb 2025) | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 37.6 | 35.1 |
| Released | 2024-09-06 | 2024-12-06 |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 22 | 54 |
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Category by category
Coding DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 31.7 (#281), Gemini 2.0 Flash (Feb 2025): 28.4 (#315)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| Aider Polyglot | 17.8% | 38.2% |
| BigCodeBench Instruct | 48.6% | 45.9% |
| LMArena Coding | 1309 | 1350 |
| BigCodeBench Complete | 53.2% | 59.9% |
| SWE-bench Verified (bash only) | — | 13.5% |
| WeirdML | — | 25.8% |
| LiveBench Coding | — | 63.4% |
| CadEval | — | 30% |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Agentic & Tool Use Not comparable
DeepSeek-V2.5 (Sep 2024): —, Gemini 2.0 Flash (Feb 2025): 28.1 (#92)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| TheAgentCompany | — | 11.4% |
Reasoning DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 25.6 (#145), Gemini 2.0 Flash (Feb 2025): 15.2 (#318)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1346 |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31.1% |
| Kagi LLM Benchmark | — | 37.8% |
| EnigmaEval | — | 1.1% |
| LiveBench Reasoning | — | 78.2% |
| DTBench | — | 63.2% |
| LiveBench Data Analysis | — | 69.4% |
| Epoch Capabilities Index | — | 135.36 |
| LiveBench | — | 66.9% |
Math Gemini 2.0 Flash (Feb 2025) leads
DeepSeek-V2.5 (Sep 2024): 35.9 (#177), Gemini 2.0 Flash (Feb 2025): 37.9 (#146)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Math | 1288 | 1352 |
| OTIS Mock AIME 2024-2025 | — | 57.8% |
| Omni-MATH | — | 45.9% |
| LiveBench Math | — | 75.8% |
| MATH Level 5 | — | 82.2% |
| FrontierMath (Feb 2025 set) | — | 1.7% |
Knowledge DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 34.8 (#193), Gemini 2.0 Flash (Feb 2025): 32.0 (#213)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Expert | 1266 | 1339 |
| GPQA Diamond | — | 64.1% |
| Humanity's Last Exam | — | 6.6% |
| MMLU-Pro | — | 73.7% |
| Confabulations | — | 12.4% |
| GPQA (HELM) | — | 55.6% |
| MMLU | — | 79.7% |
Multimodal Not comparable
DeepSeek-V2.5 (Sep 2024): —, Gemini 2.0 Flash (Feb 2025): 36.5 (#79)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Vision | — | 1158 |
| GeoBench | — | 77% |
Multilingual Gemini 2.0 Flash (Feb 2025) leads
DeepSeek-V2.5 (Sep 2024): 42.5 (#193), Gemini 2.0 Flash (Feb 2025): 47.4 (#149)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Non-English | 1273 | 1342 |
| LMArena Chinese | 1318 | 1373 |
| LMArena French | 1289 | 1391 |
| LMArena German | 1258 | 1353 |
| LMArena Japanese | 1228 | 1294 |
| LMArena Korean | 1209 | 1313 |
| LMArena Russian | 1289 | 1351 |
| LMArena Spanish | 1248 | 1363 |
Instruction Following Gemini 2.0 Flash (Feb 2025) leads
DeepSeek-V2.5 (Sep 2024): 67.5 (#194), Gemini 2.0 Flash (Feb 2025): 74.4 (#97)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Instruction Following | 1280 | 1336 |
| LiveBench Instruction Following | — | 85.8% |
| IFEval | — | 84.1% |
Long Context DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 39.5 (#174), Gemini 2.0 Flash (Feb 2025): 38.1 (#203)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Longer Query | 1301 | 1344 |
| Fiction.LiveBench | — | 61.1% |
Writing & Preference Too close to call
DeepSeek-V2.5 (Sep 2024): 49.8 (#187), Gemini 2.0 Flash (Feb 2025): 49.5 (#190)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | Gemini 2.0 Flash (Feb 2025) |
|---|---|---|
| LMArena Text | 1294 | 1354 |
| LMArena Creative Writing | 1285 | 1340 |
| LMArena Multi-Turn | 1297 | 1350 |
| Short-Story Creative Writing | — | 73.8% |
| EQ-Bench Creative Writing | — | 1128 |
| WildBench | — | 80% |
| LiveBench Language | — | 51.3% |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than Gemini 2.0 Flash (Feb 2025)?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 35.1 on the Noometry Index.
Is DeepSeek-V2.5 (Sep 2024) or Gemini 2.0 Flash (Feb 2025) better for coding?
DeepSeek-V2.5 (Sep 2024) scores higher on coding benchmarks: 31.7 versus 28.4 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Gemini 2.0 Flash (Feb 2025) share?
20 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Gemini 2.0 Flash (Feb 2025) has 54.