MetaCode Llama 34B Instruct on NVIDIA GeForce RTX 4090
Yes — RTX 4090 handles Code Llama 34B Instruct well at Q4_K_M — 22 tok/s. Solid daily-driver performance on 24 GB VRAM.
Model Size
33.7B
Device VRAM
24 GB
Bandwidth
1008 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Code Llama 34B Instruct on NVIDIA GeForce RTX 4090 at Q4_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q4_K_M | 22 tok/s | 400ms | ✓ Yes | Good | estimated |
Notes
Q4_K_M
Q4 at 19GB fits on 4090 with 5GB headroom. Surpassed by Qwen 2.5 Coder 32B but still capable.
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 4090
NVIDIA GeForce RTX 4090 has 24 GB at 1008 GB/s. Street price: $1,799.
See all models NVIDIA GeForce RTX 4090 can run →Builds with NVIDIA GeForce RTX 4090
Estimate method: Community benchmarks. Reference hardware source: github.com (2026-01-15)
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.