Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs Gemini 2.5 Flash
Gemini 2.5 Flash has enough public results to be ranked (#162); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
DeepSeek
GoogleSummary
- They share 1 benchmark with published results for both. DeepSeek-V2 (MoE-236B, May 2024) scores higher in 1 category and Gemini 2.5 Flash in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V2 (MoE-236B, May 2024) leads 39.8 to 35.5.
- DeepSeek-V2 (MoE-236B, May 2024) has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 39.7 | 39.0 |
| Released | 2024-05-07 | 2025-04-17 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.30 |
| Output $ / M tokens | — | $2.50 |
| Results tracked | 10 | 54 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek-V2 (MoE-236B, May 2024) leads
DeepSeek-V2 (MoE-236B, May 2024): 39.8 (#141), Gemini 2.5 Flash: 35.5 (#210)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| SWE-bench Verified (bash only) | — | 28.7% |
| Aider Polyglot | — | 55.1% |
| WeirdML | — | 41.9% |
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | — | 1424 |
| BigCodeBench Complete | 59.4% | — |
| ALE-Bench | — | 661.88 |
Agentic & Tool Use Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 30.6 (#67)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| Terminal-Bench | — | 17.1% |
| Berkeley Function Calling Leaderboard | — | 56.2% |
| TheAgentCompany | — | 41.1% |
| BALROG | — | 33.5% |
| Vending-Bench 2 | — | 548.84 |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 18.2 (#271)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| Epoch Capabilities Index | 124.78 | 143.04 |
| ARC-AGI-2 | — | 2.5% |
| SimpleBench | — | 41.2% |
| Kagi LLM Benchmark | — | 56.8% |
| ARC-AGI-1 | — | 33.3% |
| CritPt | — | 1.1% |
| EnigmaEval | — | 2.7% |
| LMArena Hard Prompts | — | 1422 |
| DTBench | — | 76.5% |
| LMCA | — | 27.5% |
| BIG-Bench Hard | 78.8% | — |
| ForecastBench | — | 60.6 |
| HellaSwag | 87.1% | — |
| PIQA | 83.9% | — |
| WinoGrande | 86.3% | — |
Math Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 38.1 (#87)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 73.1% |
| Omni-MATH | — | 38.5% |
| LMArena Math | — | 1415 |
| FrontierMath (Feb 2025 set) | — | 4.8% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 36.1 (#162)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| Humanity's Last Exam | — | 12.1% |
| MMLU-Pro | — | 63.9% |
| Confabulations | — | 16.8% |
| Vectara Hallucination Rate | — | 7.8% |
| GPQA (HELM) | — | 39% |
| LMArena Expert | — | 1426 |
| ARC (AI2) Challenge | 92.2% | — |
| MMLU | 78.4% | — |
| TriviaQA | 80% | — |
Multimodal Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 41.2 (#31)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| LMArena Vision | — | 1254 |
| GeoBench | — | 76% |
| VPCT | — | 46.2% |
| SpatialViz-Bench | — | 36.9% |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 52.5 (#83)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| LMArena Non-English | — | 1410 |
| LMArena Chinese | — | 1450 |
| LMArena French | — | 1433 |
| LMArena German | — | 1419 |
| LMArena Japanese | — | 1403 |
| LMArena Korean | — | 1385 |
| LMArena Russian | — | 1415 |
| LMArena Spanish | — | 1421 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 75.9 (#50)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| IFEval | — | 89.8% |
| LMArena Instruction Following | — | 1405 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 47.5 (#16)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| Fiction.LiveBench | — | 77.8% |
| LMArena Longer Query | — | 1419 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemini 2.5 Flash: 54.0 (#153)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemini 2.5 Flash |
|---|---|---|
| LMArena Text | — | 1417 |
| LMArena Creative Writing | — | 1400 |
| Short-Story Creative Writing | — | 76.5% |
| EQ-Bench Creative Writing | — | 1137 |
| WildBench | — | 81.7% |
| LMArena Multi-Turn | — | 1408 |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than Gemini 2.5 Flash?
Gemini 2.5 Flash has enough public results to be ranked (#162); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or Gemini 2.5 Flash better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 39.8 versus 35.5 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Gemini 2.5 Flash share?
1 benchmark has published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Gemini 2.5 Flash has 54.