Model comparison
Grok 4.20 Multi-Agent vs Llama 3.2 1B
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 20.1 on the Noometry Index. Llama 3.2 1B costs 22× 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 . 13 shared benchmarks.
MetaSummary
- They share 13 benchmarks with published results for both. Grok 4.20 Multi-Agent scores higher in 8 categories and Llama 3.2 1B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Grok 4.20 Multi-Agent leads 64.0 to 21.3.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 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 60K.
- Llama 3.2 1B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 Multi-Agent | Llama 3.2 1B | |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 46.2 | 20.1 |
| Released | 2026-03-09 | 2024-09-24 |
| Weights | Proprietary | Open |
| Context window | 1M | 60K |
| Max output | 30K | 54K |
| Input $ / M tokens | $1.25 | $0.027 |
| Output $ / M tokens | $2.50 | $0.20 |
| Results tracked | 20 | 22 |
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Category by category
Coding Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.0 (#92), Llama 3.2 1B: 21.1 (#338)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Coding | 1457 | 1070 |
| BigCodeBench Instruct | — | 8.2% |
| BigCodeBench Complete | — | 11.3% |
Agentic & Tool Use Not comparable
Grok 4.20 Multi-Agent: —, Llama 3.2 1B: 14.6 (#150)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 10.8% |
| BALROG | — | 6.6% |
| LMArena Search | 1204 | — |
Reasoning Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.9 (#48), Llama 3.2 1B: 16.2 (#308)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Hard Prompts | 1448 | 1044 |
| NYT Connections (extended) | 89.6% | — |
| Chess Puzzles | — | 0% |
| Epoch Capabilities Index | — | 101.99 |
Math Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 39.4 (#104), Llama 3.2 1B: 10.4 (#313)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Math | 1442 | 1086 |
| OTIS Mock AIME 2024-2025 | — | 0.6% |
Knowledge Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 40.4 (#119), Llama 3.2 1B: 7.2 (#312)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Expert | 1445 | 1007 |
| GPQA Diamond | — | 23.9% |
Multimodal Not comparable
Grok 4.20 Multi-Agent: 40.5 (#48), Llama 3.2 1B: —
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Vision | 1259 | — |
Multilingual Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 54.4 (#43), Llama 3.2 1B: 23.8 (#292)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1440 | 973 |
| LMArena Chinese | 1475 | 959 |
| LMArena German | 1456 | 1014 |
| LMArena Russian | 1457 | 941 |
| LMArena French | 1466 | — |
| LMArena Japanese | 1405 | — |
| LMArena Korean | 1416 | — |
| LMArena Spanish | 1447 | — |
Instruction Following Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 74.8 (#84), Llama 3.2 1B: 52.4 (#290)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1420 | 1031 |
Long Context Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.7 (#88), Llama 3.2 1B: 31.9 (#274)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1431 | 1050 |
Writing & Preference Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 64.0 (#59), Llama 3.2 1B: 21.3 (#310)
| Benchmark | Grok 4.20 Multi-Agent | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1450 | 1055 |
| LMArena Creative Writing | 1436 | 1033 |
| LMArena Multi-Turn | 1452 | 1030 |
| EQ-Bench Creative Writing | — | 200 |
Frequently asked questions
Is Grok 4.20 Multi-Agent better than Llama 3.2 1B?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 20.1 on the Noometry Index. Llama 3.2 1B costs 22× 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 Llama 3.2 1B?
Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is Grok 4.20 Multi-Agent or Llama 3.2 1B better for coding?
Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 21.1 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 60K.
How many benchmarks do Grok 4.20 Multi-Agent and Llama 3.2 1B share?
13 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Llama 3.2 1B has 22.