Model comparison
Grok 4.20 (Non-Reasoning) vs Qwen2-72B
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 30.0 on the Noometry Index.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. Grok 4.20 (Non-Reasoning) 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 Grok 4.20 (Non-Reasoning) leads 52.8 to 21.2.
- The biggest single-benchmark swing is GPQA Diamond: 89.3% for Grok 4.20 (Non-Reasoning) and 40.8% for Qwen2-72B.
- Qwen2-72B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 (Non-Reasoning) | Qwen2-72B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 48.6 | 30.0 |
| Released | 2026-02-17 | 2024-06-07 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 30K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $2.50 | — |
| Results tracked | 46 | 26 |
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Category by category
Coding Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 42.1 (#112), Qwen2-72B: 29.1 (#310)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| WeirdML | 52.3% | 11.3% |
| LMArena Coding | 1459 | 1196 |
| LMArena WebDev | 1375 | — |
| BigCodeBench Instruct | — | 38.5% |
| BigCodeBench Complete | — | 54% |
| ALE-Bench | 1,150 | — |
Agentic & Tool Use Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 34.4 (#46), Qwen2-72B: 17.0 (#146)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| Terminal-Bench | 57.3% | — |
| TheAgentCompany | — | 1.1% |
| τ²-bench Banking | 18% | — |
| LMArena Search | 1189 | — |
| METR Time Horizons | — | 29.9% |
| Vending-Bench 2 | 4,663 | — |
Reasoning Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.3 (#32), Qwen2-72B: 23.2 (#181)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| LMArena Hard Prompts | 1451 | 1191 |
| Epoch Capabilities Index | 151.98 | 125.28 |
| ARC-AGI-2 | 65.1% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 85.4% | — |
| ARC-AGI-1 | 89.5% | — |
| Chess Puzzles | 24% | — |
| Thematic Generalization | 63.8% | — |
| DTBench | 90.1% | — |
| LMCA | 38.7% | — |
| ForecastBench | 61.4 | — |
Math Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 48.2 (#65), Qwen2-72B: 30.2 (#236)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| LMArena Math | 1455 | 1235 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 17.1% | — |
| OTIS Mock AIME 2024-2025 | 92.2% | — |
| ProofBench | 14% | — |
| MATH Level 5 | — | 39.1% |
Knowledge Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.8 (#60), Qwen2-72B: 21.2 (#275)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| GPQA Diamond | 89.3% | 40.8% |
| LMArena Expert | 1439 | 1171 |
| SimpleQA Verified | 30.2% | — |
| MMLU | — | 82.4% |
Multimodal Not comparable
Grok 4.20 (Non-Reasoning): 33.3 (#98), Qwen2-72B: —
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1416 | — |
Multilingual Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 54.5 (#40), Qwen2-72B: 35.9 (#244)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| LMArena Non-English | 1441 | 1176 |
| LMArena Chinese | 1481 | 1240 |
| LMArena French | 1476 | 1170 |
| LMArena German | 1465 | 1151 |
| LMArena Japanese | 1449 | 1111 |
| LMArena Korean | 1417 | 1083 |
| LMArena Russian | 1458 | 1169 |
| LMArena Spanish | 1443 | 1169 |
Instruction Following Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 74.8 (#83), Qwen2-72B: 61.7 (#241)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| LMArena Instruction Following | 1420 | 1181 |
Long Context Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 45.5 (#34), Qwen2-72B: 36.1 (#235)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| LMArena Longer Query | 1437 | 1192 |
| CL-bench | 22.2% | — |
| CL-bench Life | 11.9% | — |
Writing & Preference Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 65.7 (#44), Qwen2-72B: 40.8 (#241)
| Benchmark | Grok 4.20 (Non-Reasoning) | Qwen2-72B |
|---|---|---|
| LMArena Text | 1451 | 1203 |
| LMArena Creative Writing | 1438 | 1181 |
| LMArena Multi-Turn | 1456 | 1196 |
| EQ-Bench Creative Writing | 1574 | — |
Frequently asked questions
Is Grok 4.20 (Non-Reasoning) better than Qwen2-72B?
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 30.0 on the Noometry Index.
Is Grok 4.20 (Non-Reasoning) or Qwen2-72B better for coding?
Grok 4.20 (Non-Reasoning) scores higher on coding benchmarks: 42.1 versus 29.1 in the Noometry coding category.
How many benchmarks do Grok 4.20 (Non-Reasoning) and Qwen2-72B share?
20 benchmarks have published results for both models. Grok 4.20 (Non-Reasoning) has 46 scored results on Noometry and Qwen2-72B has 26.