Model comparison
DeepSeek-V2 (MoE-236B, May 2024) vs GPT-4.1 nano
GPT-4.1 nano has enough public results to be ranked (#327); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek-V2 (MoE-236B, May 2024) scores higher in 1 category and GPT-4.1 nano 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 24.1.
- DeepSeek-V2 (MoE-236B, May 2024) has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 40.3 | 27.9 |
| Released | 2024-05-07 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 33K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 10 | 38 |
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): 40.4 (#139), GPT-4.1 nano: 24.1 (#330)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| Aider Polyglot | — | 8.9% |
| SciCode | — | 25.9% |
| WeirdML | — | 19% |
| BigCodeBench Instruct | 48.9% | — |
| LMArena Coding | — | 1306 |
| BigCodeBench Complete | 59.4% | — |
Agentic & Tool Use Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 26.5 (#104)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 33% |
Reasoning Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 8.5 (#349)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| Epoch Capabilities Index | 124.77 | 129.62 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 33.3% |
| ARC-AGI-1 | — | 0% |
| CritPt | — | 0% |
| LMArena Hard Prompts | — | 1286 |
| DTBench | — | 52.5% |
| LMCA | — | 5.5% |
| BIG-Bench Hard | 78.8% | — |
| HellaSwag | 87.1% | — |
| PIQA | 83.9% | — |
| WinoGrande | 86.3% | — |
Math Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 26.9 (#252)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 28.9% |
| Omni-MATH | — | 36.7% |
| LMArena Math | — | 1274 |
| MATH Level 5 | — | 70% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 21.8 (#273)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| GPQA Diamond | — | 48.9% |
| SimpleQA Verified | — | 6% |
| MMLU-Pro | — | 55% |
| GPQA (HELM) | — | 50.7% |
| LMArena Expert | — | 1272 |
| ARC (AI2) Challenge | 92.2% | — |
| MMLU | 78.4% | — |
| TriviaQA | 80% | — |
Multimodal Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 29.2 (#113)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| LMArena Vision | — | 1063 |
Multilingual Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 41.6 (#205)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | — | 1260 |
| LMArena Chinese | — | 1270 |
| LMArena German | — | 1288 |
| LMArena Japanese | — | 1198 |
| LMArena Russian | — | 1261 |
Instruction Following Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 67.8 (#193)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| IFEval | — | 84.3% |
| LMArena Instruction Following | — | 1267 |
Long Context Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 23.7 (#296)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| Fiction.LiveBench | — | 25% |
| LMArena Longer Query | — | 1283 |
Writing & Preference Not comparable
DeepSeek-V2 (MoE-236B, May 2024): —, GPT-4.1 nano: 40.5 (#243)
| Benchmark | DeepSeek-V2 (MoE-236B, May 2024) | GPT-4.1 nano |
|---|---|---|
| LMArena Text | — | 1285 |
| LMArena Creative Writing | — | 1260 |
| EQ-Bench Creative Writing | — | 946 |
| WildBench | — | 81.2% |
| LMArena Multi-Turn | — | 1277 |
Frequently asked questions
Is DeepSeek-V2 (MoE-236B, May 2024) better than GPT-4.1 nano?
GPT-4.1 nano has enough public results to be ranked (#327); DeepSeek-V2 (MoE-236B, May 2024) does not yet, so treat this comparison as directional.
Is DeepSeek-V2 (MoE-236B, May 2024) or GPT-4.1 nano better for coding?
DeepSeek-V2 (MoE-236B, May 2024) scores higher on coding benchmarks: 40.4 versus 24.1 in the Noometry coding category.
How many benchmarks do DeepSeek-V2 (MoE-236B, May 2024) and GPT-4.1 nano share?
1 benchmark has published results for both models. DeepSeek-V2 (MoE-236B, May 2024) has 10 scored results on Noometry and GPT-4.1 nano has 38.