CodeLlama 34B vs DeepSeek-Coder V2 (class)
Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.
| CodeLlama 34B | DeepSeek-Coder V2 (class) | |
|---|---|---|
| Parameters | 34B | 16B |
| Context window | 16K tokens | 128K tokens |
| License | Llama Community License | DeepSeek License |
| ~VRAM @ 4-bit (Q4_K_M) | ~21 GB | ~11 GB |
| ~VRAM @ 8-bit (Q8_0) | ~37 GB | ~18 GB |
| Minimum device | NVIDIA GeForce RTX 3090 | Intel Arc A770 16GB |
| Recommended device | Supermicro 8x H100 SuperServer | Supermicro 8x H100 SuperServer |
| Deployment | Hybrid | Local / on-prem |
| Capabilities | Code | Code, Long context |
Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.
Bottom line
DeepSeek-Coder V2 (class) (~16B) is lighter than CodeLlama 34B (~34B), so it runs on more modest hardware, while CodeLlama 34B trades a larger footprint for more capacity. At 4-bit, DeepSeek-Coder V2 (class) needs about 11GB versus ~21GB, a meaningful gap when choosing a GPU. DeepSeek-Coder V2 (class) advertises the longer context window (128K vs 16K), which helps with long documents. Minimum viable hardware differs: CodeLlama 34B starts on a NVIDIA GeForce RTX 3090, DeepSeek-Coder V2 (class) on a Intel Arc A770 16GB. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.
Pick CodeLlama 34B if you have the memory to spare and want the larger model, or your focus is coding.
Pick DeepSeek-Coder V2 (class) if you want the lighter footprint and cheaper hardware, or you need the longer 128K context window, or your focus is coding.
A 24GB+ card (RTX 3090/4090) or 32GB+ Mac at 4-bit. The largest CodeLlama for a single box.
The compact coder variants fit 16GB+ at 4-bit; larger MoE variants need 48GB+ or cloud.
Run the winner on hardware you control
Pick the model that fits your footprint, then turn the right machine into a private AI Business OS — no per-seat data leaving your premises.