Model comparison
Llama 2-7B vs Llama-3.3-70B-Instruct
Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 29.1 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. Llama 2-7B scores higher in 3 categories and Llama-3.3-70B-Instruct in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where Llama-3.3-70B-Instruct leads 71.1 to 50.8.
Side by side
| Llama 2-7B | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 29.1 | 30.6 |
| Released | 2023-07-18 | 2024-12-06 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.32 |
| Results tracked | 29 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Llama-3.3-70B-Instruct leads
Llama 2-7B: 29.2 (#307), Llama-3.3-70B-Instruct: 31.0 (#290)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Coding | 1002 | 1268 |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |
Agentic & Tool Use Not comparable
Llama 2-7B: —, Llama-3.3-70B-Instruct: 25.8 (#105)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |
Reasoning Llama 2-7B leads
Llama 2-7B: 15.7 (#312), Llama-3.3-70B-Instruct: 14.1 (#327)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Hard Prompts | 1009 | 1257 |
| Epoch Capabilities Index | 99.06 | 127.33 |
| SimpleBench | — | 19.9% |
| CritPt | — | 0% |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | — | 50.8% |
| DTBench | — | 59.5% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| BIG-Bench Hard | 39.2% | — |
| ForecastBench | — | 58.6 |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| LiveBench | — | 50.2% |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Llama 2-7B leads
Llama 2-7B: 30.7 (#233), Llama-3.3-70B-Instruct: 15.3 (#298)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Math | 1042 | 1267 |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |
| GSM8K | 16.7% | — |
Knowledge Llama-3.3-70B-Instruct leads
Llama 2-7B: 28.2 (#248), Llama-3.3-70B-Instruct: 30.6 (#226)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Expert | 1036 | 1225 |
| MMLU | 45.8% | 86.3% |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, Llama-3.3-70B-Instruct: —
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| ScienceQA | 43.1% | — |
Multilingual Llama-3.3-70B-Instruct leads
Llama 2-7B: 23.8 (#293), Llama-3.3-70B-Instruct: 39.9 (#220)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 973 | 1236 |
| LMArena Chinese | 973 | 1217 |
| LMArena French | 970 | 1281 |
| LMArena German | 978 | 1251 |
| LMArena Russian | 995 | 1252 |
| LMArena Spanish | 1007 | 1270 |
| LMArena Japanese | — | 1150 |
| LMArena Korean | — | 1143 |
Instruction Following Llama-3.3-70B-Instruct leads
Llama 2-7B: 50.8 (#298), Llama-3.3-70B-Instruct: 71.1 (#157)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 1006 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
Long Context Llama 2-7B leads
Llama 2-7B: 30.4 (#287), Llama-3.3-70B-Instruct: 26.4 (#295)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Longer Query | 999 | 1256 |
| Fiction.LiveBench | — | 33.3% |
Writing & Preference Llama-3.3-70B-Instruct leads
Llama 2-7B: 28.0 (#298), Llama-3.3-70B-Instruct: 47.6 (#207)
| Benchmark | Llama 2-7B | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 1053 | 1274 |
| LMArena Creative Writing | 1033 | 1250 |
| LMArena Multi-Turn | 1029 | 1280 |
| LiveBench Language | — | 39.2% |
Frequently asked questions
Is Llama 2-7B better than Llama-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 29.1 on the Noometry Index.
Is Llama 2-7B or Llama-3.3-70B-Instruct better for coding?
Llama-3.3-70B-Instruct scores higher on coding benchmarks: 31.0 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Llama-3.3-70B-Instruct share?
17 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Llama-3.3-70B-Instruct has 43.