MetaCode Llama 34B Instruct on NVIDIA GeForce RTX 4060 8GB
RTX 4060 8GB cannot run Code Llama 34B Instruct. 8 GB VRAM is insufficient at any quantization level.
Model Size
33.7B
Device VRAM
8 GB
Bandwidth
272 GB/s
Quantization
Q2_K
Performance by Quantization
OwnRig currently has one published compatibility entry for Code Llama 34B Instruct on NVIDIA GeForce RTX 4060 8GB 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
33.7B params. Minimum quantizations still exceed 8GB.
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 4060 8GB
NVIDIA GeForce RTX 4060 8GB has 8 GB at 272 GB/s. Street price: $289.
See all models NVIDIA GeForce RTX 4060 8GB can run →Estimate method: 34B model exceeds 8GB even at Q2_K. 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.