Model comparison
Grok 4.20 (Non-Reasoning) vs Llama 3.2 1B
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 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 (Non-Reasoning)'s lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
MetaSummary
- They share 18 benchmarks with published results for both. Grok 4.20 (Non-Reasoning) scores higher in 9 categories and Llama 3.2 1B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Grok 4.20 (Non-Reasoning) leads 52.8 to 7.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 92.2% for Grok 4.20 (Non-Reasoning) and 0.6% for Llama 3.2 1B.
- 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 (Non-Reasoning).
- Grok 4.20 (Non-Reasoning) 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 (Non-Reasoning) | Llama 3.2 1B | |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 48.6 | 20.1 |
| Released | 2026-02-17 | 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 | 46 | 22 |
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Category by category
Coding Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 42.1 (#112), Llama 3.2 1B: 21.1 (#338)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| LMArena Coding | 1459 | 1070 |
| LMArena WebDev | 1375 | — |
| WeirdML | 52.3% | — |
| BigCodeBench Instruct | — | 8.2% |
| BigCodeBench Complete | — | 11.3% |
| ALE-Bench | 1,150 | — |
Agentic & Tool Use Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 34.4 (#46), Llama 3.2 1B: 14.6 (#150)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| Terminal-Bench | 57.3% | — |
| Berkeley Function Calling Leaderboard | — | 10.8% |
| τ²-bench Banking | 18% | — |
| BALROG | — | 6.6% |
| LMArena Search | 1189 | — |
| Vending-Bench 2 | 4,663 | — |
Reasoning Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.3 (#32), Llama 3.2 1B: 16.2 (#308)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| Chess Puzzles | 24% | 0% |
| LMArena Hard Prompts | 1451 | 1044 |
| Epoch Capabilities Index | 151.98 | 101.99 |
| ARC-AGI-2 | 65.1% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 85.4% | — |
| ARC-AGI-1 | 89.5% | — |
| Thematic Generalization | 63.8% | — |
| DTBench | 90.1% | — |
| LMCA | 38.7% | — |
| ForecastBench | 61.4 | — |
Math Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 48.2 (#65), Llama 3.2 1B: 10.4 (#313)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 92.2% | 0.6% |
| LMArena Math | 1455 | 1086 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 14% | — |
Knowledge Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.8 (#60), Llama 3.2 1B: 7.2 (#312)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| GPQA Diamond | 89.3% | 23.9% |
| LMArena Expert | 1439 | 1007 |
| SimpleQA Verified | 30.2% | — |
Multimodal Not comparable
Grok 4.20 (Non-Reasoning): 33.3 (#98), Llama 3.2 1B: —
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1416 | — |
Multilingual Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 54.5 (#40), Llama 3.2 1B: 23.8 (#292)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1441 | 973 |
| LMArena Chinese | 1481 | 959 |
| LMArena German | 1465 | 1014 |
| LMArena Russian | 1458 | 941 |
| LMArena French | 1476 | — |
| LMArena Japanese | 1449 | — |
| LMArena Korean | 1417 | — |
| LMArena Spanish | 1443 | — |
Instruction Following Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 74.8 (#83), Llama 3.2 1B: 52.4 (#290)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1420 | 1031 |
Long Context Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 45.5 (#34), Llama 3.2 1B: 31.9 (#274)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1437 | 1050 |
| CL-bench | 22.2% | — |
| CL-bench Life | 11.9% | — |
Writing & Preference Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 65.7 (#44), Llama 3.2 1B: 21.3 (#310)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1451 | 1055 |
| LMArena Creative Writing | 1438 | 1033 |
| EQ-Bench Creative Writing | 1574 | 200 |
| LMArena Multi-Turn | 1456 | 1030 |
Frequently asked questions
Is Grok 4.20 (Non-Reasoning) better than Llama 3.2 1B?
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.6 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 (Non-Reasoning)'s lead doesn't matter for your workload.
Which is cheaper, Grok 4.20 (Non-Reasoning) 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 (Non-Reasoning) lists at $1.25 and $2.50.
Is Grok 4.20 (Non-Reasoning) or Llama 3.2 1B better for coding?
Grok 4.20 (Non-Reasoning) scores higher on coding benchmarks: 42.1 versus 21.1 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 (Non-Reasoning) does, with 1M tokens against 60K.
How many benchmarks do Grok 4.20 (Non-Reasoning) and Llama 3.2 1B share?
18 benchmarks have published results for both models. Grok 4.20 (Non-Reasoning) has 46 scored results on Noometry and Llama 3.2 1B has 22.