Model comparison
Llama 13b vs Llama-3.3-70B-Instruct
Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 24.4 on the Noometry Index.
Last verified . 10 shared benchmarks.
MetaSummary
- They share 10 benchmarks with published results for both. Llama 13b scores higher in 1 category and Llama-3.3-70B-Instruct in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where Llama-3.3-70B-Instruct leads 71.1 to 36.7.
Side by side
| Llama 13b | Llama-3.3-70B-Instruct | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 24.4 | 30.6 |
| Released | 2023-02-24 | 2024-12-06 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.32 |
| Results tracked | 21 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Llama-3.3-70B-Instruct leads
Llama 13b: 21.4 (#337), Llama-3.3-70B-Instruct: 31.0 (#290)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Coding | 683 | 1268 |
| SciCode | — | 26% |
| WeirdML | — | 14.4% |
| BigCodeBench Instruct | — | 46.9% |
| LiveBench Coding | — | 36.6% |
| BigCodeBench Complete | — | 57.5% |
Agentic & Tool Use Not comparable
Llama 13b: —, Llama-3.3-70B-Instruct: 25.8 (#105)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 31.9% |
| BALROG | — | 23% |
Reasoning Too close to call
Llama 13b: 14.0 (#329), Llama-3.3-70B-Instruct: 14.1 (#327)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Hard Prompts | 728 | 1257 |
| Epoch Capabilities Index | 100.58 | 127.33 |
| SimpleBench | — | 19.9% |
| CritPt | — | 0% |
| LiveBench Reasoning | — | 50.8% |
| DTBench | — | 59.5% |
| LiveBench Data Analysis | — | 49.5% |
| LMCA | — | 17.5% |
| BIG-Bench Hard | 37.9% | — |
| ForecastBench | — | 58.6 |
| HellaSwag | 79.2% | — |
| LAMBADA | 75.2% | — |
| LiveBench | — | 50.2% |
| PIQA | 80.1% | — |
| WinoGrande | 73% | — |
Math Llama 13b leads
Llama 13b: 26.7 (#256), Llama-3.3-70B-Instruct: 15.3 (#298)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Math | 838 | 1267 |
| OTIS Mock AIME 2024-2025 | — | 5.1% |
| LiveBench Math | — | 42.2% |
| MATH Level 5 | — | 41.6% |
| GSM8K | 20.6% | — |
Knowledge Not comparable
Llama 13b: —, Llama-3.3-70B-Instruct: 30.6 (#226)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| MMLU | 47.7% | 86.3% |
| GPQA Diamond | — | 47.4% |
| Confabulations | — | 22.8% |
| Vectara Hallucination Rate | — | 4.1% |
| LMArena Expert | — | 1225 |
| ARC (AI2) Challenge | 52.7% | — |
| BoolQ | 78.7% | — |
| OpenBookQA | 56.4% | — |
| TriviaQA | 77.9% | — |
Multimodal Not comparable
Llama 13b: —, Llama-3.3-70B-Instruct: —
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| ScienceQA | 43.3% | — |
Multilingual Llama-3.3-70B-Instruct leads
Llama 13b: 16.6 (#297), Llama-3.3-70B-Instruct: 39.9 (#220)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Non-English | 819 | 1236 |
| LMArena Chinese | — | 1217 |
| LMArena French | — | 1281 |
| LMArena German | — | 1251 |
| LMArena Japanese | — | 1150 |
| LMArena Korean | — | 1143 |
| LMArena Russian | — | 1252 |
| LMArena Spanish | — | 1270 |
Instruction Following Llama-3.3-70B-Instruct leads
Llama 13b: 36.7 (#305), Llama-3.3-70B-Instruct: 71.1 (#157)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Instruction Following | 781 | 1242 |
| LiveBench Instruction Following | — | 82.7% |
Long Context Not comparable
Llama 13b: —, Llama-3.3-70B-Instruct: 26.4 (#295)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| Fiction.LiveBench | — | 33.3% |
| LMArena Longer Query | — | 1256 |
Writing & Preference Llama-3.3-70B-Instruct leads
Llama 13b: 13.8 (#312), Llama-3.3-70B-Instruct: 47.6 (#207)
| Benchmark | Llama 13b | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text | 834 | 1274 |
| LMArena Creative Writing | 794 | 1250 |
| LMArena Multi-Turn | 753 | 1280 |
| LiveBench Language | — | 39.2% |
Frequently asked questions
Is Llama 13b better than Llama-3.3-70B-Instruct?
Llama-3.3-70B-Instruct is the stronger model overall, scoring 30.6 to 24.4 on the Noometry Index.
Is Llama 13b or Llama-3.3-70B-Instruct better for coding?
Llama-3.3-70B-Instruct scores higher on coding benchmarks: 31.0 versus 21.4 in the Noometry coding category.
How many benchmarks do Llama 13b and Llama-3.3-70B-Instruct share?
10 benchmarks have published results for both models. Llama 13b has 21 scored results on Noometry and Llama-3.3-70B-Instruct has 43.