Model comparison
Grok 4.20 Multi-Agent vs Qwen-14B
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 30.8 on the Noometry Index.
Last verified . 10 shared benchmarks.
Alibaba (Qwen)Summary
- They share 10 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 7 categories and Qwen-14B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Grok 4.20 Multi-Agent leads 64.1 to 27.8.
- Qwen-14B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 Multi-Agent | Qwen-14B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 45.5 | 30.8 |
| Released | 2026-03-09 | 2023-09-24 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 30K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $2.50 | — |
| Results tracked | 20 | 18 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 42.4 (#91), Qwen-14B: 30.6 (#283)
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Coding | 1458 | 1072 |
Agentic & Tool Use Not comparable
Grok 4.20 Multi-Agent: —, Qwen-14B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Search | 1204 | — |
Reasoning Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 42.4 (#44), Qwen-14B: 18.7 (#255)
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Hard Prompts | 1448 | 1027 |
| NYT Connections (extended) | 89.6% | — |
| BIG-Bench Hard | — | 55% |
| Epoch Capabilities Index | — | 112.8 |
| LAMBADA | — | 71.1% |
| PIQA | — | 79.9% |
Math Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 36.6 (#106), Qwen-14B: 28.7 (#224)
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Math | 1441 | 1068 |
| GSM8K | — | 61.3% |
Knowledge Not comparable
Grok 4.20 Multi-Agent: 39.7 (#116), Qwen-14B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Expert | 1445 | — |
| ARC (AI2) Challenge | — | 84.4% |
| BoolQ | — | 86.2% |
| MMLU | — | 66.3% |
Multimodal Not comparable
Grok 4.20 Multi-Agent: 39.8 (#44), Qwen-14B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Vision | 1259 | — |
Multilingual Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 54.6 (#40), Qwen-14B: 27.7 (#270)
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Non-English | 1440 | 1042 |
| LMArena Chinese | 1475 | 1077 |
| LMArena French | 1467 | — |
| LMArena German | 1456 | — |
| LMArena Japanese | 1405 | — |
| LMArena Korean | 1416 | — |
| LMArena Russian | 1457 | — |
| LMArena Spanish | 1447 | — |
Instruction Following Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 75.0 (#80), Qwen-14B: 52.6 (#284)
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Instruction Following | 1420 | 1031 |
Long Context Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.7 (#84), Qwen-14B: 31.3 (#276)
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Longer Query | 1430 | 1029 |
Writing & Preference Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 64.1 (#57), Qwen-14B: 27.8 (#294)
| Benchmark | Grok 4.20 Multi-Agent | Qwen-14B |
|---|---|---|
| LMArena Text | 1450 | 1051 |
| LMArena Creative Writing | 1435 | 1028 |
| LMArena Multi-Turn | 1451 | 1022 |
Frequently asked questions
Is Grok 4.20 Multi-Agent better than Qwen-14B?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 30.8 on the Noometry Index.
Is Grok 4.20 Multi-Agent or Qwen-14B better for coding?
Grok 4.20 Multi-Agent scores higher on coding benchmarks: 42.4 versus 30.6 in the Noometry coding category.
How many benchmarks do Grok 4.20 Multi-Agent and Qwen-14B share?
10 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen-14B has 18.