Model comparison
DeepSeek-V2.5 (Sep 2024) vs GPT-4.1
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 35.9 on the Noometry Index.
Last verified . 18 shared benchmarks.
DeepSeekSummary
- They share 18 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 2 categories and GPT-4.1 in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V2.5 (Sep 2024) leads 25.6 to 11.7.
- The biggest single-benchmark swing is Aider Polyglot: 17.8% for DeepSeek-V2.5 (Sep 2024) and 52.4% for GPT-4.1.
- DeepSeek-V2.5 (Sep 2024) has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V2.5 (Sep 2024) | GPT-4.1 | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 37.6 | 35.9 |
| Released | 2024-09-06 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 33K |
| Input $ / M tokens | — | $2 |
| Output $ / M tokens | — | $8 |
| Results tracked | 22 | 52 |
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Category by category
Coding GPT-4.1 leads
DeepSeek-V2.5 (Sep 2024): 31.7 (#281), GPT-4.1: 34.4 (#238)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| Aider Polyglot | 17.8% | 52.4% |
| LMArena Coding | 1309 | 1391 |
| SWE-bench Verified | — | 48.5% |
| SWE-bench Verified (bash only) | — | 39.6% |
| WeirdML | — | 39% |
| BigCodeBench Instruct | 48.6% | — |
| BigCodeBench Complete | 53.2% | — |
| CadEval | — | 42% |
| ALE-Bench | — | 558.1 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |
Agentic & Tool Use Not comparable
DeepSeek-V2.5 (Sep 2024): —, GPT-4.1: 34.7 (#43)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 54% |
Reasoning DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 25.6 (#145), GPT-4.1: 11.7 (#339)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1384 |
| ARC-AGI-2 | — | 0.4% |
| SimpleBench | — | 27% |
| Kagi LLM Benchmark | — | 52.3% |
| ARC-AGI-1 | — | 5.5% |
| Chess Puzzles | — | 6% |
| EnigmaEval | — | 2.2% |
| DTBench | — | 68.3% |
| LMCA | — | 25.6% |
| Epoch Capabilities Index | — | 136.78 |
| ForecastBench | — | 61.5 |
Math DeepSeek-V2.5 (Sep 2024) leads
DeepSeek-V2.5 (Sep 2024): 35.9 (#177), GPT-4.1: 22.3 (#280)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Math | 1288 | 1370 |
| FrontierMath (Tiers 1-3) | — | 6% |
| OTIS Mock AIME 2024-2025 | — | 38.3% |
| Omni-MATH | — | 47.1% |
| MATH Level 5 | — | 83% |
| FrontierMath (Feb 2025 set) | — | 5.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GPT-4.1 leads
DeepSeek-V2.5 (Sep 2024): 34.8 (#193), GPT-4.1: 37.1 (#160)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Expert | 1266 | 1364 |
| GPQA Diamond | — | 66.9% |
| Humanity's Last Exam | — | 5.4% |
| SimpleQA Verified | — | 31.1% |
| MMLU-Pro | — | 81.1% |
| Vectara Hallucination Rate | — | 5.6% |
| GPQA (HELM) | — | 65.9% |
Multimodal Not comparable
DeepSeek-V2.5 (Sep 2024): —, GPT-4.1: 38.2 (#67)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Vision | — | 1211 |
| GeoBench | — | 72% |
Multilingual GPT-4.1 leads
DeepSeek-V2.5 (Sep 2024): 42.5 (#193), GPT-4.1: 49.4 (#133)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Non-English | 1273 | 1370 |
| LMArena Chinese | 1318 | 1382 |
| LMArena French | 1289 | 1382 |
| LMArena German | 1258 | 1381 |
| LMArena Japanese | 1228 | 1319 |
| LMArena Korean | 1209 | 1339 |
| LMArena Russian | 1289 | 1377 |
| LMArena Spanish | 1248 | 1376 |
Instruction Following GPT-4.1 leads
DeepSeek-V2.5 (Sep 2024): 67.5 (#194), GPT-4.1: 71.3 (#153)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Instruction Following | 1280 | 1367 |
| IFEval | — | 83.8% |
Long Context Too close to call
DeepSeek-V2.5 (Sep 2024): 39.5 (#174), GPT-4.1: 40.0 (#163)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Longer Query | 1301 | 1385 |
| Fiction.LiveBench | — | 63.9% |
Writing & Preference GPT-4.1 leads
DeepSeek-V2.5 (Sep 2024): 49.8 (#187), GPT-4.1: 57.6 (#125)
| Benchmark | DeepSeek-V2.5 (Sep 2024) | GPT-4.1 |
|---|---|---|
| LMArena Text | 1294 | 1383 |
| LMArena Creative Writing | 1285 | 1363 |
| LMArena Multi-Turn | 1297 | 1398 |
| EQ-Bench Creative Writing | — | 1420 |
| WildBench | — | 85.4% |
Frequently asked questions
Is DeepSeek-V2.5 (Sep 2024) better than GPT-4.1?
DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.6 to 35.9 on the Noometry Index.
Is DeepSeek-V2.5 (Sep 2024) or GPT-4.1 better for coding?
GPT-4.1 scores higher on coding benchmarks: 34.4 versus 31.7 in the Noometry coding category.
How many benchmarks do DeepSeek-V2.5 (Sep 2024) and GPT-4.1 share?
18 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and GPT-4.1 has 52.