Model comparison
Grok 3 vs Qwen-14B
Grok 3 is the stronger model overall, scoring 39.9 to 31.4 on the Noometry Index.
Last verified . 11 shared benchmarks.
Alibaba (Qwen)Summary
- They share 11 benchmarks with published results for both. Grok 3 scores higher in 6 categories and Qwen-14B in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Grok 3 leads 55.8 to 27.6.
- Qwen-14B has downloadable open weights; the other is API-only.
Side by side
| Grok 3 | Qwen-14B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 39.9 | 31.4 |
| Released | 2025-04-09 | 2023-09-24 |
| Weights | Proprietary | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 40 | 18 |
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Category by category
Coding Grok 3 leads
Grok 3: 41.9 (#115), Qwen-14B: 31.2 (#288)
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| LMArena Coding | 1432 | 1071 |
| Aider Polyglot | 53.3% | — |
| WeirdML | 37.2% | — |
Agentic & Tool Use Not comparable
Grok 3: 30.5 (#76), Qwen-14B: —
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| BALROG | 29.5% | — |
Reasoning Qwen-14B leads
Grok 3: 13.7 (#333), Qwen-14B: 19.6 (#257)
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| LMArena Hard Prompts | 1434 | 1027 |
| Epoch Capabilities Index | 138.33 | 113.03 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 36.1% | — |
| Kagi LLM Benchmark | 61.3% | — |
| ARC-AGI-1 | 5.5% | — |
| BIG-Bench Hard | — | 55% |
| LAMBADA | — | 71.1% |
| PIQA | — | 79.9% |
Math Grok 3 leads
Grok 3: 38.0 (#145), Qwen-14B: 31.2 (#227)
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| LMArena Math | 1391 | 1068 |
| OTIS Mock AIME 2024-2025 | 55.6% | — |
| Omni-MATH | 46.4% | — |
| MATH Level 5 | 88.7% | — |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
| GSM8K | — | 61.3% |
Knowledge Not comparable
Grok 3: 46.2 (#82), Qwen-14B: —
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 78.8% | — |
| Confabulations | 14.2% | — |
| Vectara Hallucination Rate | 5.8% | — |
| GPQA (HELM) | 65% | — |
| LMArena Expert | 1421 | — |
| ARC (AI2) Challenge | — | 84.4% |
| BoolQ | — | 86.2% |
| MMLU | — | 66.3% |
Multilingual Grok 3 leads
Grok 3: 52.3 (#87), Qwen-14B: 27.5 (#275)
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| LMArena Non-English | 1410 | 1041 |
| LMArena Chinese | 1448 | 1077 |
| LMArena French | 1460 | — |
| LMArena German | 1431 | — |
| LMArena Japanese | 1387 | — |
| LMArena Korean | 1373 | — |
| LMArena Russian | 1416 | — |
| LMArena Spanish | 1417 | — |
Instruction Following Grok 3 leads
Grok 3: 75.0 (#73), Qwen-14B: 52.4 (#289)
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| LMArena Instruction Following | 1409 | 1031 |
| IFEval | 88.4% | — |
Long Context Grok 3 leads
Grok 3: 38.7 (#192), Qwen-14B: 31.3 (#280)
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| LMArena Longer Query | 1439 | 1028 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference Grok 3 leads
Grok 3: 55.8 (#141), Qwen-14B: 27.6 (#299)
| Benchmark | Grok 3 | Qwen-14B |
|---|---|---|
| LMArena Text | 1426 | 1051 |
| LMArena Creative Writing | 1414 | 1028 |
| LMArena Multi-Turn | 1425 | 1022 |
| Short-Story Creative Writing | 76.4% | — |
| EQ-Bench Creative Writing | 1186 | — |
| WildBench | 84.9% | — |
Frequently asked questions
Is Grok 3 better than Qwen-14B?
Grok 3 is the stronger model overall, scoring 39.9 to 31.4 on the Noometry Index.
Is Grok 3 or Qwen-14B better for coding?
Grok 3 scores higher on coding benchmarks: 41.9 versus 31.2 in the Noometry coding category.
How many benchmarks do Grok 3 and Qwen-14B share?
11 benchmarks have published results for both models. Grok 3 has 40 scored results on Noometry and Qwen-14B has 18.