Model comparison
Grok 4.20 Multi-Agent vs Qwen2.5-Coder-32B
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 32.9 on the Noometry Index. Qwen2.5-Coder-32B costs 2.1× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Qwen2.5-Coder-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Grok 4.20 Multi-Agent leads 64.1 to 41.8.
- Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 33K.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 45.5 | 32.9 |
| Released | 2026-03-09 | 2024-09-18 |
| Weights | Proprietary | Open |
| Context window | 1M | 33K |
| Max output | 30K | 29K |
| Input $ / M tokens | $1.25 | $0.66 |
| Output $ / M tokens | $2.50 | $1 |
| Results tracked | 20 | 31 |
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Category by category
Coding Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 42.4 (#91), Qwen2.5-Coder-32B: 22.4 (#328)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Coding | 1458 | 1276 |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| BigCodeBench Instruct | — | 49% |
| LiveBench Coding | — | 56.9% |
| BigCodeBench Complete | — | 58% |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |
Agentic & Tool Use Not comparable
Grok 4.20 Multi-Agent: —, Qwen2.5-Coder-32B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Search | 1204 | — |
Reasoning Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 42.4 (#44), Qwen2.5-Coder-32B: 20.4 (#220)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Hard Prompts | 1448 | 1251 |
| NYT Connections (extended) | 89.6% | — |
| LiveBench Reasoning | — | 42.1% |
| LiveBench Data Analysis | — | 49.9% |
| Epoch Capabilities Index | — | 119.41 |
| HellaSwag | — | 83% |
| LiveBench | — | 46.2% |
| WinoGrande | — | 80.8% |
Math Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 36.6 (#106), Qwen2.5-Coder-32B: 30.8 (#203)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Math | 1441 | 1251 |
| LiveBench Math | — | 46.6% |
| GSM8K | — | 93% |
Knowledge Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 39.7 (#116), Qwen2.5-Coder-32B: 32.9 (#200)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1445 | 1221 |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |
Multimodal Not comparable
Grok 4.20 Multi-Agent: 39.8 (#44), Qwen2.5-Coder-32B: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1259 | — |
Multilingual Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 54.6 (#40), Qwen2.5-Coder-32B: 38.0 (#230)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1440 | 1205 |
| LMArena Chinese | 1475 | 1222 |
| LMArena Russian | 1457 | 1228 |
| LMArena French | 1467 | — |
| LMArena German | 1456 | — |
| LMArena Japanese | 1405 | — |
| LMArena Korean | 1416 | — |
| LMArena Spanish | 1447 | — |
Instruction Following Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 75.0 (#80), Qwen2.5-Coder-32B: 61.6 (#240)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Instruction Following | 1420 | 1223 |
| LiveBench Instruction Following | — | 58.7% |
Long Context Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.7 (#84), Qwen2.5-Coder-32B: 37.9 (#204)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1430 | 1251 |
Writing & Preference Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 64.1 (#57), Qwen2.5-Coder-32B: 41.8 (#235)
| Benchmark | Grok 4.20 Multi-Agent | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1450 | 1230 |
| LMArena Creative Writing | 1435 | 1174 |
| LMArena Multi-Turn | 1451 | 1222 |
| LiveBench Language | — | 23.3% |
Frequently asked questions
Is Grok 4.20 Multi-Agent better than Qwen2.5-Coder-32B?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 45.5 to 32.9 on the Noometry Index. Qwen2.5-Coder-32B costs 2.1× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Which is cheaper, Grok 4.20 Multi-Agent or Qwen2.5-Coder-32B?
Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is Grok 4.20 Multi-Agent or Qwen2.5-Coder-32B better for coding?
Grok 4.20 Multi-Agent scores higher on coding benchmarks: 42.4 versus 22.4 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 33K.
How many benchmarks do Grok 4.20 Multi-Agent and Qwen2.5-Coder-32B share?
12 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen2.5-Coder-32B has 31.