Model comparison
DeepSeek-V3 vs Gemini 3 Pro
Gemini 3 Pro is the stronger model overall, scoring 54.8 to 39.5 on the Noometry Index.
Last verified . 34 shared benchmarks.
DeepSeek
GoogleSummary
- They share 34 benchmarks with published results for both. DeepSeek-V3 scores higher in 0 categories and Gemini 3 Pro in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3 Pro leads 52.5 to 20.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 37.8% for DeepSeek-V3 and 91.4% for Gemini 3 Pro.
- DeepSeek-V3 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3 | Gemini 3 Pro | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 39.5 | 54.8 |
| Released | 2024-12-26 | 2025-11-18 |
| Weights | Open | Proprietary |
| Context window | 164K | — |
| Max output | 164K | — |
| Input $ / M tokens | $0.24 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 60 | 67 |
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Category by category
Coding Gemini 3 Pro leads
DeepSeek-V3: 42.3 (#106), Gemini 3 Pro: 51.6 (#39)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| WeirdML | 36.1% | 69.9% |
| LMArena Coding | 1368 | 1481 |
| SWE-bench Verified | — | 72.9% |
| SWE-bench Verified (bash only) | — | 74.2% |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1440 |
| SWE-bench Multilingual | — | 68.7% |
| SciCode | 35.8% | — |
| GSO | — | 18.6% |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| BigCodeBench Complete | 62.2% | — |
| ALE-Bench | — | 1,177 |
| AlgoTune | — | 1.83 |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |
Agentic & Tool Use Not comparable
DeepSeek-V3: —, Gemini 3 Pro: 40.6 (#23)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| METR Time Horizons | 49.6% | 71% |
| Terminal-Bench | — | 69.4% |
| Berkeley Function Calling Leaderboard | — | 72.5% |
| GDPval | — | 40.3% |
| Remote Labor Index | — | 1.3% |
| τ²-bench Airline | — | 80.5% |
| τ²-bench Banking | — | 18% |
| τ²-bench Retail | — | 75.9% |
| τ²-bench Telecom | — | 91% |
| DeepResearch Bench | — | 46.3% |
| BALROG | — | 58.1% |
| LMArena Search | — | 1207 |
| Vending-Bench 2 | — | 5,478 |
Reasoning Gemini 3 Pro leads
DeepSeek-V3: 20.5 (#236), Gemini 3 Pro: 52.5 (#31)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| SimpleBench | 27.2% | 76.4% |
| Kagi LLM Benchmark | 52.3% | 80.1% |
| CritPt | 0% | 6.9% |
| LMArena Hard Prompts | 1365 | 1480 |
| Epoch Capabilities Index | 135.94 | 152.92 |
| ForecastBench | 59.1 | 61.2 |
| ARC-AGI-2 | — | 31.1% |
| NYT Connections (extended) | — | 94.4% |
| ARC-AGI-1 | — | 75% |
| Chess Puzzles | — | 31% |
| EnigmaEval | — | 18.2% |
| LiveBench Reasoning | 65.8% | — |
| DTBench | 64.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 15.5% | — |
| BIG-Bench Hard | 87.5% | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |
Math Gemini 3 Pro leads
DeepSeek-V3: 32.1 (#219), Gemini 3 Pro: 49.9 (#59)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 91.4% |
| Omni-MATH | 40.3% | 55.5% |
| LMArena Math | 1373 | 1476 |
| FrontierMath (Feb 2025 set) | 1.7% | 37.6% |
| MathArena Final-Answer Competitions | — | 67% |
| ProofBench | — | 20% |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath Tier 4 (v1) | — | 18.8% |
Knowledge Gemini 3 Pro leads
DeepSeek-V3: 37.5 (#155), Gemini 3 Pro: 64.4 (#16)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| GPQA Diamond | 67.6% | 92.6% |
| MMLU-Pro | 72.3% | 90.3% |
| Vectara Hallucination Rate | 6.1% | 13.6% |
| GPQA (HELM) | 53.8% | 80.3% |
| LMArena Expert | 1351 | 1475 |
| Humanity's Last Exam | — | 37.5% |
| Confabulations | 26.1% | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |
Multimodal Not comparable
DeepSeek-V3: —, Gemini 3 Pro: 57.6 (#2)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| LMArena Vision | — | 1305 |
| GeoBench | — | 84% |
| VPCT | — | 91% |
| LMArena Document | — | 1434 |
Multilingual Gemini 3 Pro leads
DeepSeek-V3: 48.5 (#143), Gemini 3 Pro: 56.9 (#16)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| LMArena Non-English | 1358 | 1474 |
| LMArena Chinese | 1391 | 1523 |
| LMArena French | 1385 | 1492 |
| LMArena German | 1374 | 1515 |
| LMArena Japanese | 1333 | 1510 |
| LMArena Korean | 1319 | 1448 |
| LMArena Russian | 1373 | 1493 |
| LMArena Spanish | 1358 | 1470 |
Instruction Following Gemini 3 Pro leads
DeepSeek-V3: 72.8 (#130), Gemini 3 Pro: 76.3 (#45)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| IFEval | 83.2% | 87.7% |
| LMArena Instruction Following | 1345 | 1458 |
| LiveBench Instruction Following | 81.5% | — |
Long Context Gemini 3 Pro leads
DeepSeek-V3: 34.0 (#253), Gemini 3 Pro: 44.0 (#79)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| LMArena Longer Query | 1352 | 1471 |
| Fiction.LiveBench | 50% | — |
| CL-bench | — | 15.8% |
Writing & Preference Gemini 3 Pro leads
DeepSeek-V3: 57.4 (#130), Gemini 3 Pro: 66.4 (#35)
| Benchmark | DeepSeek-V3 | Gemini 3 Pro |
|---|---|---|
| LMArena Text | 1375 | 1479 |
| LMArena Creative Writing | 1364 | 1482 |
| EQ-Bench Creative Writing | 1472 | 1525 |
| WildBench | 83% | 85.9% |
| LMArena Multi-Turn | 1389 | 1484 |
| Short-Story Creative Writing | 77% | — |
| LiveBench Language | 49.1% | — |
Frequently asked questions
Is DeepSeek-V3 better than Gemini 3 Pro?
Gemini 3 Pro is the stronger model overall, scoring 54.8 to 39.5 on the Noometry Index.
Is DeepSeek-V3 or Gemini 3 Pro better for coding?
Gemini 3 Pro scores higher on coding benchmarks: 51.6 versus 42.3 in the Noometry coding category.
How many benchmarks do DeepSeek-V3 and Gemini 3 Pro share?
34 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and Gemini 3 Pro has 67.