Model comparison
Grok 4.20 Multi-Agent vs Qwen3-1.7B
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 26.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 42.4 to 18.5.
- Qwen3-1.7B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 Multi-Agent | Qwen3-1.7B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 45.5 | 26.2 |
| Released | 2026-03-09 | 2025-04-29 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 30K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $2.50 | — |
| Results tracked | 20 | 4 |
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Category by category
Coding Not comparable
Grok 4.20 Multi-Agent: 42.4 (#91), Qwen3-1.7B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| LMArena Coding | 1458 | — |
Agentic & Tool Use Not comparable
Grok 4.20 Multi-Agent: —, Qwen3-1.7B: 24.5 (#108)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.4% |
| LMArena Search | 1204 | — |
Reasoning Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 42.4 (#44), Qwen3-1.7B: 18.5 (#263)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| NYT Connections (extended) | 89.6% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | 1448 | — |
Math Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 36.6 (#106), Qwen3-1.7B: 15.4 (#288)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 8.1% |
| LMArena Math | 1441 | — |
Knowledge Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 39.7 (#116), Qwen3-1.7B: 19.6 (#273)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| GPQA Diamond | — | 38% |
| LMArena Expert | 1445 | — |
Multimodal Not comparable
Grok 4.20 Multi-Agent: 39.8 (#44), Qwen3-1.7B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| LMArena Vision | 1259 | — |
Multilingual Not comparable
Grok 4.20 Multi-Agent: 54.6 (#40), Qwen3-1.7B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| LMArena Non-English | 1440 | — |
| LMArena Chinese | 1475 | — |
| LMArena French | 1467 | — |
| LMArena German | 1456 | — |
| LMArena Japanese | 1405 | — |
| LMArena Korean | 1416 | — |
| LMArena Russian | 1457 | — |
| LMArena Spanish | 1447 | — |
Instruction Following Not comparable
Grok 4.20 Multi-Agent: 75.0 (#80), Qwen3-1.7B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| LMArena Instruction Following | 1420 | — |
Long Context Not comparable
Grok 4.20 Multi-Agent: 43.7 (#84), Qwen3-1.7B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| LMArena Longer Query | 1430 | — |
Writing & Preference Not comparable
Grok 4.20 Multi-Agent: 64.1 (#57), Qwen3-1.7B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-1.7B |
|---|---|---|
| LMArena Text | 1450 | — |
| LMArena Creative Writing | 1435 | — |
| LMArena Multi-Turn | 1451 | — |
Frequently asked questions
Is Grok 4.20 Multi-Agent better than Qwen3-1.7B?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 26.2 on the Noometry Index.
How many benchmarks do Grok 4.20 Multi-Agent and Qwen3-1.7B share?
0 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen3-1.7B has 4.