Llama 3.1 8B vs Qwen3 8B
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 8B | Qwen3 8B | |
|---|---|---|
| Parameters | 8B | 8B |
| Context window | 128K tokens | 128K tokens |
| License | Llama Community License | Apache-2.0 |
| ~VRAM @ 4-bit (Q4_K_M) | ~6 GB | ~6 GB |
| ~VRAM @ 8-bit (Q8_0) | ~9 GB | ~9 GB |
| Minimum device | NVIDIA GeForce RTX 3060 12GB | NVIDIA GeForce RTX 3060 12GB |
| Recommended device | NVIDIA B200 (placeholder) | NVIDIA B200 (placeholder) |
| Deployment | Local / on-prem | Local / on-prem |
| Capabilities | Tools, Multilingual, Long context | Tools, Reasoning, Code, 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 8B and Qwen3 8B are the same size (~8B parameters), so their memory footprints are comparable. Both target a 128K context window. Qwen3 8B's Apache-2.0 license is the more permissive of the two for commercial use. Both can start on a NVIDIA GeForce RTX 3060 12GB-class machine. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.
Pick Llama 3.1 8B if first private assistant.
Pick Qwen3 8B if you want the more permissive Apache-2.0 license.
Runs comfortably at 4-bit on any 8GB+ GPU, a Mac mini, or a small mini PC. The classic entry point for local AI.
8GB+ GPUs at 4-bit. A strong, current small generalist with optional step-by-step reasoning.
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