Model comparison
Grok 4.20 Multi-Agent vs Qwen3-Next 80B-A3B Instruct
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 43.0 on the Noometry Index. Qwen3-Next 80B-A3B Instruct costs 1.8× 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 . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 7 categories and Qwen3-Next 80B-A3B Instruct in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.20 Multi-Agent leads 43.9 to 31.1.
- Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 / $2 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 131K.
- Qwen3-Next 80B-A3B Instruct has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 46.2 | 43.0 |
| Released | 2026-03-09 | 2025-09 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 30K | 33K |
| Input $ / M tokens | $1.25 | $0.50 |
| Output $ / M tokens | $2.50 | $2 |
| Results tracked | 20 | 25 |
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Category by category
Coding Too close to call
Grok 4.20 Multi-Agent: 43.0 (#92), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1457 | 1440 |
Agentic & Tool Use Not comparable
Grok 4.20 Multi-Agent: —, Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Search | 1204 | — |
Reasoning Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.9 (#48), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1448 | 1428 |
| Kagi LLM Benchmark | — | 66.7% |
| NYT Connections (extended) | 89.6% | — |
Math Too close to call
Grok 4.20 Multi-Agent: 39.4 (#104), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Math | 1442 | 1440 |
| Omni-MATH | — | 46.7% |
Knowledge Qwen3-Next 80B-A3B Instruct leads
Grok 4.20 Multi-Agent: 40.4 (#119), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Expert | 1445 | 1417 |
| MMLU-Pro | — | 78.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 63% |
Multimodal Not comparable
Grok 4.20 Multi-Agent: 40.5 (#48), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Vision | 1259 | — |
Multilingual Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 54.4 (#43), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1440 | 1407 |
| LMArena Chinese | 1475 | 1460 |
| LMArena French | 1466 | 1413 |
| LMArena German | 1456 | 1417 |
| LMArena Japanese | 1405 | 1395 |
| LMArena Korean | 1416 | 1364 |
| LMArena Russian | 1457 | 1404 |
| LMArena Spanish | 1447 | 1435 |
Instruction Following Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 74.8 (#84), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Instruction Following | 1420 | 1389 |
| IFEval | — | 81% |
Long Context Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.7 (#88), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Longer Query | 1431 | 1403 |
| Fiction.LiveBench | — | 55.6% |
Writing & Preference Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 64.0 (#59), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | Grok 4.20 Multi-Agent | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1450 | 1417 |
| LMArena Creative Writing | 1436 | 1334 |
| LMArena Multi-Turn | 1452 | 1416 |
| WildBench | — | 80.7% |
Frequently asked questions
Is Grok 4.20 Multi-Agent better than Qwen3-Next 80B-A3B Instruct?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 43.0 on the Noometry Index. Qwen3-Next 80B-A3B Instruct costs 1.8× 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 Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is cheaper. It lists at $0.50 per million input tokens and $2 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is Grok 4.20 Multi-Agent or Qwen3-Next 80B-A3B Instruct better for coding?
They score almost the same on coding (43.0 vs 42.5); test both on your own repository before choosing.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 131K.
How many benchmarks do Grok 4.20 Multi-Agent and Qwen3-Next 80B-A3B Instruct share?
17 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.