Model comparison
DeepSeek V4 Pro vs GPT-5 Nano
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 33.5 on the Noometry Index. GPT-5 Nano costs 7.2× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.
Last verified . 35 shared benchmarks.
DeepSeekSummary
- They share 35 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 9 categories and GPT-5 Nano in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.5 to 16.3.
- The biggest single-benchmark swing is ARC-AGI-1: 90.5% for DeepSeek V4 Pro and 20.7% for GPT-5 Nano.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.66 / $1.98 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 400K.
- DeepSeek V4 Pro has downloadable open weights; the other is API-only.
Side by side
| DeepSeek V4 Pro | GPT-5 Nano | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 54.3 | 33.5 |
| Released | 2026-04-24 | 2025-08-07 |
| Weights | Open | Proprietary |
| Context window | 1M | 400K |
| Max output | 393K | 128K |
| Input $ / M tokens | $0.66 | $0.05 |
| Output $ / M tokens | $1.98 | $0.40 |
| Results tracked | 48 | 49 |
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Category by category
Coding DeepSeek V4 Pro leads
DeepSeek V4 Pro: 52.4 (#34), GPT-5 Nano: 33.6 (#254)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| WeirdML | 66.2% | 38.1% |
| LMArena Coding | 1470 | 1351 |
| ALE-Bench | 1,403 | 718.67 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| SWE-bench Verified (bash only) | — | 34.8% |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
Agentic & Tool Use DeepSeek V4 Pro leads
DeepSeek V4 Pro: 32.8 (#58), GPT-5 Nano: 25.8 (#106)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| Terminal-Bench | — | 21.8% |
| APEX-Agents | 47.3% | — |
| Berkeley Function Calling Leaderboard | — | 51.5% |
| Vending-Bench 2 | 3,285 | — |
Reasoning DeepSeek V4 Pro leads
DeepSeek V4 Pro: 56.5 (#24), GPT-5 Nano: 16.3 (#306)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| ARC-AGI-2 | 61.3% | 2.6% |
| Kagi LLM Benchmark | 53.5% | 62.2% |
| ARC-AGI-1 | 90.5% | 20.7% |
| Chess Puzzles | 47% | 27% |
| LMArena Hard Prompts | 1461 | 1328 |
| Mystery Game Puzzles | 43% | 9% |
| DTBench | 93.9% | 62.7% |
| LMCA | 45.5% | 7.9% |
| Epoch Capabilities Index | 155.31 | 139.38 |
| ForecastBench | 56.1 | 59.1 |
| NYT Connections (extended) | 91.3% | — |
| CritPt | 18% | — |
| Surface Evolver Bench | 40% | — |
Math DeepSeek V4 Pro leads
DeepSeek V4 Pro: 64.8 (#30), GPT-5 Nano: 29.4 (#241)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | 20% |
| FrontierMath Tier 4 | 26.8% | 2.4% |
| OTIS Mock AIME 2024-2025 | 98.6% | 81.1% |
| ProofBench | 50% | 12% |
| LMArena Math | 1455 | 1317 |
| MathArena Final-Answer Competitions | 76.6% | — |
| Omni-MATH | — | 54.6% |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge DeepSeek V4 Pro leads
DeepSeek V4 Pro: 59.5 (#31), GPT-5 Nano: 35.9 (#178)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| GPQA Diamond | 91.7% | 69.4% |
| SimpleQA Verified | 52.9% | 11.7% |
| Vectara Hallucination Rate | 8.6% | 10.5% |
| LMArena Expert | 1464 | 1321 |
| MMLU-Pro | — | 77.8% |
| GPQA (HELM) | — | 67.9% |
Multimodal Not comparable
DeepSeek V4 Pro: —, GPT-5 Nano: 31.3 (#108)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |
Multilingual DeepSeek V4 Pro leads
DeepSeek V4 Pro: 54.4 (#45), GPT-5 Nano: 45.3 (#172)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | 1439 | 1313 |
| LMArena Chinese | 1486 | 1356 |
| LMArena German | 1458 | 1327 |
| LMArena Japanese | 1445 | 1226 |
| LMArena Korean | 1447 | 1269 |
| LMArena Russian | 1453 | 1296 |
| LMArena Spanish | 1458 | 1360 |
| LMArena French | 1472 | — |
Instruction Following DeepSeek V4 Pro leads
DeepSeek V4 Pro: 76.1 (#47), GPT-5 Nano: 75.0 (#79)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| LMArena Instruction Following | 1448 | 1306 |
| IFEval | — | 93.2% |
Long Context DeepSeek V4 Pro leads
DeepSeek V4 Pro: 45.0 (#51), GPT-5 Nano: 31.3 (#281)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| LMArena Longer Query | 1458 | 1312 |
| Fiction.LiveBench | — | 44.4% |
| CL-bench Life | 13.5% | — |
Writing & Preference DeepSeek V4 Pro leads
DeepSeek V4 Pro: 65.5 (#46), GPT-5 Nano: 39.1 (#249)
| Benchmark | DeepSeek V4 Pro | GPT-5 Nano |
|---|---|---|
| LMArena Text | 1451 | 1320 |
| LMArena Creative Writing | 1446 | 1249 |
| EQ-Bench Creative Writing | 1553 | 705 |
| LMArena Multi-Turn | 1467 | 1311 |
| WildBench | — | 80.6% |
| EQ-Bench 4 | 1166 | — |
Frequently asked questions
Is DeepSeek V4 Pro better than GPT-5 Nano?
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 33.5 on the Noometry Index. GPT-5 Nano costs 7.2× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.
Which is cheaper, DeepSeek V4 Pro or GPT-5 Nano?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; DeepSeek V4 Pro lists at $0.66 and $1.98.
Is DeepSeek V4 Pro or GPT-5 Nano better for coding?
DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 33.6 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Pro does, with 1M tokens against 400K.
How many benchmarks do DeepSeek V4 Pro and GPT-5 Nano share?
35 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and GPT-5 Nano has 49.