Model comparison
Grok-2 (Dec 2024) vs Llama-3.3-70B-Instruct
Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 30.6 on the Noometry Index.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. Grok-2 (Dec 2024) scores higher in 6 categories and Llama-3.3-70B-Instruct in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in long context, where Grok-2 (Dec 2024) leads 38.8 to 26.4.
- The biggest single-benchmark swing is MATH Level 5: 63.5% for Grok-2 (Dec 2024) and 41.6% for Llama-3.3-70B-Instruct.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.
Side by side
| Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 33.7 | 30.6 |
| Released | 2024-08-13 | 2024-12-06 |
| Weights | Proprietary | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.32 |
| Results tracked | 34 | 43 |
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Category by category
Coding Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 33.3 (#258), Llama-3.3-70B-Instruct: 31.0 (#290)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| WeirdML | 22.2% | 14.4% |
| LiveBench Coding | 46.4% | 36.6% |
| LMArena Coding | 1287 | 1268 |
| SciCode | — | 26% |
| BigCodeBench Instruct | — | 46.9% |
| BigCodeBench Complete | — | 57.5% |
Agentic & Tool Use Not comparable
Grok-2 (Dec 2024): —, Llama-3.3-70B-Instruct: 25.8 (#105)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |
Reasoning Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 16.9 (#299), Llama-3.3-70B-Instruct: 14.1 (#327)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| SimpleBench | 22.7% | 19.9% |
| LiveBench Reasoning | 54.8% | 50.8% |
| LMArena Hard Prompts | 1272 | 1257 |
| DTBench | 65.2% | 59.5% |
| LiveBench Data Analysis | 54.5% | 49.5% |
| Epoch Capabilities Index | 130.48 | 127.33 |
| LiveBench | 54.3% | 50.2% |
| CritPt | — | 0% |
| LMCA | — | 17.5% |
| ForecastBench | — | 58.6 |
Math Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 20.8 (#284), Llama-3.3-70B-Instruct: 15.3 (#298)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 11.5% | 5.1% |
| LiveBench Math | 54.9% | 42.2% |
| LMArena Math | 1283 | 1267 |
| MATH Level 5 | 63.5% | 41.6% |
| FrontierMath (Feb 2025 set) | 0.7% | — |
Knowledge Too close to call
Grok-2 (Dec 2024): 29.8 (#233), Llama-3.3-70B-Instruct: 30.6 (#226)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| GPQA Diamond | 53.8% | 47.4% |
| Confabulations | 20.1% | 22.8% |
| LMArena Expert | 1254 | 1225 |
| Vectara Hallucination Rate | — | 4.1% |
| MMLU | — | 86.3% |
Multilingual Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 43.1 (#188), Llama-3.3-70B-Instruct: 39.9 (#220)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 1282 | 1236 |
| LMArena Chinese | 1289 | 1217 |
| LMArena French | 1318 | 1281 |
| LMArena German | 1287 | 1251 |
| LMArena Japanese | 1244 | 1150 |
| LMArena Korean | 1237 | 1143 |
| LMArena Russian | 1286 | 1252 |
| LMArena Spanish | 1281 | 1270 |
Instruction Following Llama-3.3-70B-Instruct leads
Grok-2 (Dec 2024): 66.9 (#202), Llama-3.3-70B-Instruct: 71.1 (#157)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LiveBench Instruction Following | 69.6% | 82.7% |
| LMArena Instruction Following | 1270 | 1242 |
Long Context Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 38.8 (#190), Llama-3.3-70B-Instruct: 26.4 (#295)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 1276 | 1256 |
| Fiction.LiveBench | — | 33.3% |
Writing & Preference Grok-2 (Dec 2024) leads
Grok-2 (Dec 2024): 48.6 (#198), Llama-3.3-70B-Instruct: 47.6 (#207)
| Benchmark | Grok-2 (Dec 2024) | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1305 | 1274 |
| LMArena Creative Writing | 1284 | 1250 |
| LMArena Multi-Turn | 1290 | 1280 |
| LiveBench Language | 45.6% | 39.2% |
| Short-Story Creative Writing | 63.6% | — |
Frequently asked questions
Is Grok-2 (Dec 2024) better than Llama-3.3-70B-Instruct?
Grok-2 (Dec 2024) is the stronger model overall, scoring 33.7 to 30.6 on the Noometry Index.
Is Grok-2 (Dec 2024) or Llama-3.3-70B-Instruct better for coding?
Grok-2 (Dec 2024) scores higher on coding benchmarks: 33.3 versus 31.0 in the Noometry coding category.
How many benchmarks do Grok-2 (Dec 2024) and Llama-3.3-70B-Instruct share?
32 benchmarks have published results for both models. Grok-2 (Dec 2024) has 34 scored results on Noometry and Llama-3.3-70B-Instruct has 43.