Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs Gemma 3 27B
Gemma 3 27B has enough public results to be ranked (#284); 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 Gemma 3 27B in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in coding, where DeepSeek-V2 (MoE-236B, May 2024) leads 40.4 to 22.5.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 40.3 | 30.8 |
| Released | 2024-05-07 | 2025-03-11 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $0.08 |
| Output $ / M tokens | — | $0.16 |
| Results tracked | 10 | 43 |
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Category by category
Coding DeepSeek-V2 (MoE-236B, May 2024) leads
DeepSeek-V2 (MoE-236B, May 2024): 40.4 (#139), Gemma 3 27B: 22.5 (#334)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| Aider Polyglot | — | 4.9% |
| SciCode | — | 21.2% |
| BigCodeBench Instruct | 48.9% | — |
| LiveBench Coding | — | 39.9% |
| LMArena Coding | — | 1322 |
| BigCodeBench Complete | 59.4% | — |
Agentic & Tool Use Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 25.1 (#110)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 29.5% |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 16.7 (#301)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| Epoch Capabilities Index | 124.77 | 130.04 |
| Kagi LLM Benchmark | — | 40.4% |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | — | 43.8% |
| LMArena Hard Prompts | — | 1340 |
| DTBench | — | 52.5% |
| LiveBench Data Analysis | — | 51.5% |
| LMCA | — | 12.3% |
| BIG-Bench Hard | 78.8% | — |
| HellaSwag | 87.1% | — |
| LiveBench | — | 50% |
| PIQA | 83.9% | — |
| WinoGrande | 86.3% | — |
Math Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 25.9 (#265)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 22.5% |
| LiveBench Math | — | 55.4% |
| LMArena Math | — | 1312 |
| MATH Level 5 | — | 74% |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 25.5 (#261)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| GPQA Diamond | — | 47.7% |
| Confabulations | — | 40.3% |
| Vectara Hallucination Rate | — | 7.4% |
| LMArena Expert | — | 1304 |
| ARC (AI2) Challenge | 92.2% | — |
| MMLU | 78.4% | — |
| TriviaQA | 80% | — |
Multimodal Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 32.6 (#100)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| LMArena Vision | — | 1164 |
| GeoBench | — | 52% |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 46.9 (#155)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| LMArena Non-English | — | 1334 |
| LMArena Chinese | — | 1346 |
| LMArena French | — | 1368 |
| LMArena German | — | 1362 |
| LMArena Japanese | — | 1287 |
| LMArena Korean | — | 1308 |
| LMArena Russian | — | 1349 |
| LMArena Spanish | — | 1349 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 70.6 (#160)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| LiveBench Instruction Following | — | 74.9% |
| LMArena Instruction Following | — | 1321 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 27.6 (#293)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| Fiction.LiveBench | — | 33.3% |
| LMArena Longer Query | — | 1333 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, Gemma 3 27B: 52.5 (#168)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | Gemma 3 27B |
|---|---|---|
| LMArena Text | — | 1358 |
| LMArena Creative Writing | — | 1346 |
| Short-Story Creative Writing | — | 79.9% |
| EQ-Bench Creative Writing | — | 1266 |
| LMArena Multi-Turn | — | 1345 |
| LiveBench Language | — | 34.6% |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than Gemma 3 27B?
Gemma 3 27B has enough public results to be ranked (#284); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or Gemma 3 27B better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 40.4 versus 22.5 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and Gemma 3 27B share?
1 benchmark has published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and Gemma 3 27B has 43.