Model comparison
DeepSeek V4 Pro vs Qwen2-72B
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 30.0 on the Noometry Index.
Last verified . 20 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- They share 20 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 9 categories and Qwen2-72B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek V4 Pro leads 59.5 to 21.2.
- The biggest single-benchmark swing is WeirdML: 66.2% for DeepSeek V4 Pro and 11.3% for Qwen2-72B.
Side by side
| DeepSeek V4 Pro | Qwen2-72B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 54.3 | 30.0 |
| Released | 2026-04-24 | 2024-06-07 |
| Weights | Open | Open |
| Context window | 1M | — |
| Max output | 393K | — |
| Input $ / M tokens | $0.66 | — |
| Output $ / M tokens | $1.98 | — |
| Results tracked | 48 | 26 |
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Category by category
Coding DeepSeek V4 Pro leads
DeepSeek V4 Pro: 52.4 (#34), Qwen2-72B: 29.1 (#310)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| WeirdML | 66.2% | 11.3% |
| LMArena Coding | 1470 | 1196 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| BigCodeBench Instruct | — | 38.5% |
| BigCodeBench Complete | — | 54% |
| ALE-Bench | 1,403 | — |
Agentic & Tool Use DeepSeek V4 Pro leads
DeepSeek V4 Pro: 32.8 (#58), Qwen2-72B: 17.0 (#146)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| APEX-Agents | 47.3% | — |
| TheAgentCompany | — | 1.1% |
| METR Time Horizons | — | 29.9% |
| Vending-Bench 2 | 3,285 | — |
Reasoning DeepSeek V4 Pro leads
DeepSeek V4 Pro: 56.5 (#24), Qwen2-72B: 23.2 (#181)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| LMArena Hard Prompts | 1461 | 1191 |
| Epoch Capabilities Index | 155.31 | 125.28 |
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| ForecastBench | 56.1 | — |
Math DeepSeek V4 Pro leads
DeepSeek V4 Pro: 64.8 (#30), Qwen2-72B: 30.2 (#236)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| LMArena Math | 1455 | 1235 |
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
| MATH Level 5 | — | 39.1% |
Knowledge DeepSeek V4 Pro leads
DeepSeek V4 Pro: 59.5 (#31), Qwen2-72B: 21.2 (#275)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| GPQA Diamond | 91.7% | 40.8% |
| LMArena Expert | 1464 | 1171 |
| SimpleQA Verified | 52.9% | — |
| Vectara Hallucination Rate | 8.6% | — |
| MMLU | — | 82.4% |
Multilingual DeepSeek V4 Pro leads
DeepSeek V4 Pro: 54.4 (#45), Qwen2-72B: 35.9 (#244)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| LMArena Non-English | 1439 | 1176 |
| LMArena Chinese | 1486 | 1240 |
| LMArena French | 1472 | 1170 |
| LMArena German | 1458 | 1151 |
| LMArena Japanese | 1445 | 1111 |
| LMArena Korean | 1447 | 1083 |
| LMArena Russian | 1453 | 1169 |
| LMArena Spanish | 1458 | 1169 |
Instruction Following DeepSeek V4 Pro leads
DeepSeek V4 Pro: 76.1 (#47), Qwen2-72B: 61.7 (#241)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| LMArena Instruction Following | 1448 | 1181 |
Long Context DeepSeek V4 Pro leads
DeepSeek V4 Pro: 45.0 (#51), Qwen2-72B: 36.1 (#235)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| LMArena Longer Query | 1458 | 1192 |
| CL-bench Life | 13.5% | — |
Writing & Preference DeepSeek V4 Pro leads
DeepSeek V4 Pro: 65.5 (#46), Qwen2-72B: 40.8 (#241)
| Benchmark | DeepSeek V4 Pro | Qwen2-72B |
|---|---|---|
| LMArena Text | 1451 | 1203 |
| LMArena Creative Writing | 1446 | 1181 |
| LMArena Multi-Turn | 1467 | 1196 |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |
Frequently asked questions
Is DeepSeek V4 Pro better than Qwen2-72B?
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 30.0 on the Noometry Index.
Is DeepSeek V4 Pro or Qwen2-72B better for coding?
DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 29.1 in the Noometry coding category.
How many benchmarks do DeepSeek V4 Pro and Qwen2-72B share?
20 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Qwen2-72B has 26.