MetaCode Llama 34B Instruct on NVIDIA GeForce RTX 3080 10GB
RTX 3080 10GB cannot run Code Llama 34B Instruct. 10 GB VRAM is insufficient at any quantization level.
Model Size
33.7B
Device VRAM
10 GB
Bandwidth
760 GB/s
Quantization
Q2_K
Performance by Quantization
OwnRig currently has one published compatibility entry for Code Llama 34B Instruct on NVIDIA GeForce RTX 3080 10GB at Q2_K. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q2_K | – | – | ✗ Offload | Not viable | estimated |
Notes
Q2_K
34B doesn't fit in 10GB.
About Code Llama 34B Instruct
Code Llama 34B Instruct (33.7B) is a coding, ai coding model. Meta's dedicated 34B coding model. Still competitive for code generation but being surpassed by newer models like Qwen 2.5 Coder 32B. Shorter context window (16K) is a limitation for large codebases.
View all Code Llama 34B Instruct hardware options →About NVIDIA GeForce RTX 3080 10GB
NVIDIA GeForce RTX 3080 10GB has 10 GB at 760 GB/s. Street price: $399.
See all models NVIDIA GeForce RTX 3080 10GB can run →Estimate method: Performance estimates based on model size and device bandwidth. Reference hardware source: github.com (2026-03-15)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.