Model comparison
Grok 4.20 (Non-Reasoning) vs Llama 3-70B
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.5 to 28.5 on the Noometry Index.
Last verified . 23 shared benchmarks.
MetaSummary
- They share 23 benchmarks with published results for both. Grok 4.20 (Non-Reasoning) scores higher in 9 categories and Llama 3-70B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Grok 4.20 (Non-Reasoning) leads 48.0 to 12.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 92.2% for Grok 4.20 (Non-Reasoning) and 4.3% for Llama 3-70B.
- Llama 3-70B has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 (Non-Reasoning) | Llama 3-70B | |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 48.5 | 28.5 |
| Released | 2026-02-17 | 2024-04-18 |
| Weights | Proprietary | Open |
| Context window | 1M | — |
| Max output | 30K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $2.50 | — |
| Results tracked | 46 | 31 |
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Category by category
Coding Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 41.8 (#104), Llama 3-70B: 35.3 (#215)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| LMArena Coding | 1458 | 1206 |
| LMArena WebDev | 1374 | — |
| WeirdML | 52.3% | — |
| BigCodeBench Instruct | — | 43.6% |
| BigCodeBench Complete | — | 54.5% |
| ALE-Bench | 1,150 | — |
| HumanEval+ | — | 72% |
| MBPP+ | — | 69% |
Agentic & Tool Use Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 34.3 (#43), Llama 3-70B: 20.9 (#132)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| Terminal-Bench | 57.3% | — |
| τ²-bench Banking | 18% | — |
| Cybench | — | 5% |
| LMArena Search | 1189 | — |
| Vending-Bench 2 | 4,663 | — |
Reasoning Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.2 (#30), Llama 3-70B: 17.4 (#284)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| Kagi LLM Benchmark | 75% | 35.1% |
| LMArena Hard Prompts | 1451 | 1195 |
| DTBench | 90.1% | 54.2% |
| Epoch Capabilities Index | 152.01 | 122.91 |
| ForecastBench | 61.4 | 57.1 |
| ARC-AGI-2 | 65.1% | — |
| NYT Connections (extended) | 85.4% | — |
| ARC-AGI-1 | 89.5% | — |
| Chess Puzzles | 24% | — |
| Thematic Generalization | 63.8% | — |
| LMCA | 38.7% | — |
| WinoGrande | — | 83.5% |
Math Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 48.0 (#54), Llama 3-70B: 12.0 (#299)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 92.2% | 4.3% |
| LMArena Math | 1455 | 1218 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 14% | — |
| MATH Level 5 | — | 22.6% |
Knowledge Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 52.8 (#54), Llama 3-70B: 20.8 (#272)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| GPQA Diamond | 89.3% | 40.6% |
| LMArena Expert | 1440 | 1149 |
| SimpleQA Verified | 30.2% | — |
| MMLU | — | 79.3% |
Multimodal Not comparable
Grok 4.20 (Non-Reasoning): 33.2 (#88), Llama 3-70B: —
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1416 | — |
Multilingual Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 54.7 (#38), Llama 3-70B: 33.8 (#246)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| LMArena Non-English | 1440 | 1142 |
| LMArena Chinese | 1481 | 1114 |
| LMArena French | 1477 | 1231 |
| LMArena German | 1463 | 1169 |
| LMArena Japanese | 1450 | 1017 |
| LMArena Korean | 1417 | 1017 |
| LMArena Russian | 1457 | 1159 |
| LMArena Spanish | 1442 | 1241 |
Instruction Following Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 75.0 (#79), Llama 3-70B: 62.8 (#233)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| LMArena Instruction Following | 1420 | 1194 |
Long Context Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 45.4 (#33), Llama 3-70B: 35.6 (#235)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| LMArena Longer Query | 1436 | 1174 |
| CL-bench | 22.2% | — |
| CL-bench Life | 11.9% | — |
Writing & Preference Grok 4.20 (Non-Reasoning) leads
Grok 4.20 (Non-Reasoning): 65.9 (#42), Llama 3-70B: 43.0 (#225)
| Benchmark | Grok 4.20 (Non-Reasoning) | Llama 3-70B |
|---|---|---|
| LMArena Text | 1451 | 1221 |
| LMArena Creative Writing | 1439 | 1210 |
| LMArena Multi-Turn | 1456 | 1223 |
| EQ-Bench Creative Writing | 1574 | — |
Frequently asked questions
Is Grok 4.20 (Non-Reasoning) better than Llama 3-70B?
Grok 4.20 (Non-Reasoning) is the stronger model overall, scoring 48.5 to 28.5 on the Noometry Index.
Is Grok 4.20 (Non-Reasoning) or Llama 3-70B better for coding?
Grok 4.20 (Non-Reasoning) scores higher on coding benchmarks: 41.8 versus 35.3 in the Noometry coding category.
How many benchmarks do Grok 4.20 (Non-Reasoning) and Llama 3-70B share?
23 benchmarks have published results for both models. Grok 4.20 (Non-Reasoning) has 46 scored results on Noometry and Llama 3-70B has 31.