Model comparison
Grok 4.20 (Non-Reasoning) vs QwQ-32B
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 39.8 on the Noometry Index.
Last verified . 23 shared benchmarks.
Alibaba (Qwen)Summary
- They share 23 benchmarks with published results for both. Grok 4.20 (Non-Reasoning) scores higher in 7 categories and QwQ-32B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 (Non-Reasoning) leads 52.3 to 23.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 92.2% for Grok 4.20 (Non-Reasoning) and 59.2% for QwQ-32B.
- QwQ-32B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 (Non-Reasoning) | QwQ-32B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 48.6 | 39.8 |
| Released | 2026-02-17 | 2024-11-28 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 30K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $2.50 | — |
| Results tracked | 46 | 36 |
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Category by category
Coding Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 42.1 (#112), QwQ-32B: 35.4 (#226)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| LMArena Coding | 1459 | 1333 |
| Aider Polyglot | — | 20.9% |
| LMArena WebDev | 1375 | — |
| WeirdML | 52.3% | — |
| BigCodeBench Instruct | — | 44.6% |
| LiveBench Coding | — | 72.2% |
| BigCodeBench Complete | — | 54.4% |
| ALE-Bench | 1,150 | — |
Agentic & Tool Use Not comparable
Grok 4.20 (Non-Reasoning): 34.4 (#46), QwQ-32B: —
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| Terminal-Bench | 57.3% | — |
| τ²-bench Banking | 18% | — |
| LMArena Search | 1189 | — |
| Vending-Bench 2 | 4,663 | — |
Reasoning Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.3 (#32), QwQ-32B: 23.7 (#174)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| Chess Puzzles | 24% | 5% |
| LMArena Hard Prompts | 1451 | 1325 |
| Epoch Capabilities Index | 151.98 | 137.6 |
| ForecastBench | 61.4 | 58.3 |
| ARC-AGI-2 | 65.1% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 85.4% | — |
| ARC-AGI-1 | 89.5% | — |
| Thematic Generalization | 63.8% | — |
| LiveBench Reasoning | — | 83.5% |
| DTBench | 90.1% | — |
| LiveBench Data Analysis | — | 65% |
| LMCA | 38.7% | — |
| LiveBench | — | 72% |
Math Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 48.2 (#65), QwQ-32B: 38.0 (#143)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 92.2% | 59.2% |
| LMArena Math | 1455 | 1359 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 14% | — |
| LiveBench Math | — | 77.8% |
Knowledge Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.8 (#60), QwQ-32B: 37.2 (#158)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| GPQA Diamond | 89.3% | 65.3% |
| LMArena Expert | 1439 | 1324 |
| SimpleQA Verified | 30.2% | — |
| Confabulations | — | 15.6% |
Multimodal Not comparable
Grok 4.20 (Non-Reasoning): 33.3 (#98), QwQ-32B: —
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| 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), QwQ-32B: 44.8 (#176)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| LMArena Non-English | 1441 | 1305 |
| LMArena Chinese | 1481 | 1378 |
| LMArena French | 1476 | 1336 |
| LMArena German | 1465 | 1313 |
| LMArena Japanese | 1449 | 1262 |
| LMArena Korean | 1417 | 1279 |
| LMArena Russian | 1458 | 1297 |
| LMArena Spanish | 1443 | 1354 |
Instruction Following Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 74.8 (#83), QwQ-32B: 72.6 (#137)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| LMArena Instruction Following | 1420 | 1297 |
| LiveBench Instruction Following | — | 81.8% |
Long Context QwQ-32B leads
Grok 4.20 (Non-Reasoning): 45.5 (#34), QwQ-32B: 49.0 (#11)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| LMArena Longer Query | 1437 | 1308 |
| Fiction.LiveBench | — | 83.3% |
| 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), QwQ-32B: 50.6 (#180)
| Benchmark | Grok 4.20 (Non-Reasoning) | QwQ-32B |
|---|---|---|
| LMArena Text | 1451 | 1329 |
| LMArena Creative Writing | 1438 | 1288 |
| EQ-Bench Creative Writing | 1574 | 1257 |
| LMArena Multi-Turn | 1456 | 1314 |
| Short-Story Creative Writing | — | 80.2% |
| LiveBench Language | — | 51.4% |
Frequently asked questions
Is Grok 4.20 (Non-Reasoning) better than QwQ-32B?
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 to 39.8 on the Noometry Index.
Is Grok 4.20 (Non-Reasoning) or QwQ-32B better for coding?
Grok 4.20 (Non-Reasoning) scores higher on coding benchmarks: 42.1 versus 35.4 in the Noometry coding category.
How many benchmarks do Grok 4.20 (Non-Reasoning) and QwQ-32B share?
23 benchmarks have published results for both models. Grok 4.20 (Non-Reasoning) has 46 scored results on Noometry and QwQ-32B has 36.