Llama 3.1 70B vs Llama 3.3 70B
Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.
| Llama 3.1 70B | Llama 3.3 70B | |
|---|---|---|
| Parameters | 70B | 70B |
| Context window | 128K tokens | 128K tokens |
| License | Llama Community License | Llama Community License |
| ~VRAM @ 4-bit (Q4_K_M) | ~42 GB | ~42 GB |
| ~VRAM @ 8-bit (Q8_0) | ~75 GB | ~75 GB |
| Minimum device | NVIDIA RTX A6000 | NVIDIA RTX A6000 |
| Recommended device | Supermicro 8x H100 SuperServer | Supermicro 8x H100 SuperServer |
| Deployment | Hybrid | Hybrid |
| Capabilities | Tools, Reasoning, Multilingual, Long context | Tools, Reasoning, Multilingual, Long context |
Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.
Bottom line
Llama 3.1 70B and Llama 3.3 70B are the same size (~70B parameters), so their memory footprints are comparable. Both target a 128K context window. Both can start on a NVIDIA RTX A6000-class machine. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.
Pick Llama 3.1 70B if document rag at quality.
Pick Llama 3.3 70B if high-quality rag.
Flagship tier — ~42GB at 4-bit needs a 48GB card, a 64GB+ unified-memory Mac, or multi-GPU.
Flagship tier — ~42GB at 4-bit means a 48GB card, a 64GB+ unified-memory Mac, or multi-GPU.
Run the winner on hardware you control
Pick the model that fits your footprint, then turn the right machine into a private AI Business OS — no per-seat data leaving your premises.