Llama 3.1 70B vs Mixtral 8x7B (MoE)
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 | Mixtral 8x7B (MoE) | |
|---|---|---|
| Parameters | 70B | 47B total / ~13B active (MoE) |
| Context window | 128K tokens | 32K tokens |
| License | Llama Community License | Apache-2.0 |
| ~VRAM @ 4-bit (Q4_K_M) | ~42 GB | ~28 GB |
| ~VRAM @ 8-bit (Q8_0) | ~75 GB | ~50 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, Multilingual |
Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.
Bottom line
Mixtral 8x7B (MoE) (~47B) is lighter than Llama 3.1 70B (~70B), so it runs on more modest hardware, while Llama 3.1 70B trades a larger footprint for more capacity. At 4-bit, Mixtral 8x7B (MoE) needs about 28GB versus ~42GB, a meaningful gap when choosing a GPU. Llama 3.1 70B advertises the longer context window (128K vs 32K), which helps with long documents. Mixtral 8x7B (MoE)'s Apache-2.0 license is the more permissive of the two for commercial use. 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 you have the memory to spare and want the larger model, or you need the longer 128K context window.
Pick Mixtral 8x7B (MoE) if you want the lighter footprint and cheaper hardware, or you want the more permissive Apache-2.0 license.
Flagship tier — ~42GB at 4-bit needs a 48GB card, a 64GB+ unified-memory Mac, or multi-GPU.
~28GB+ at 4-bit; suits 48GB pro cards or unified-memory machines. Sparse activation gives good speed for the quality.
Run the winner on hardware you control
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