MetaCode Llama 34B Instruct on NVIDIA RTX PRO 6000 Blackwell Max-Q
Yes — RTX PRO 6000 Blackwell Max-Q handles Code Llama 34B Instruct well at Q5_K_M — 44 tok/s. Solid daily-driver performance on 96 GB VRAM.
Model Size
33.7B
Device VRAM
96 GB
Bandwidth
1800 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Code Llama 34B Instruct on NVIDIA RTX PRO 6000 Blackwell Max-Q at Q5_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q5_K_M | 44 tok/s | 126ms | ✓ Yes | Good | estimated |
Notes
Q5_K_M
96 GB GDDR7 fits Q5_K_M (22.7 GB) with 73 GB headroom. 1.8 TB/s bandwidth. High quality quantization with good speed.
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 RTX PRO 6000 Blackwell Max-Q
NVIDIA RTX PRO 6000 Blackwell Max-Q has 96 GB at 1800 GB/s. Street price: $7,000.
See all models NVIDIA RTX PRO 6000 Blackwell Max-Q can run →Estimate method: Estimated from full RTX PRO 6000 with ~8% reduction for Max-Q 300W power envelope. Reference hardware source: nvidia.com (2026-03-29)
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.