BBrainOutput

DeepSeek-Coder V2 (class) vs StarCoder2 15B

Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.

DeepSeek-Coder V2 (class)StarCoder2 15B
Parameters16B15B
Context window128K tokens16K tokens
LicenseDeepSeek LicenseBigCode OpenRAIL-M
~VRAM @ 4-bit (Q4_K_M)~11 GB~10 GB
~VRAM @ 8-bit (Q8_0)~18 GB~17 GB
Minimum deviceIntel Arc A770 16GBNVIDIA GeForce RTX 3060 12GB
Recommended deviceSupermicro 8x H100 SuperServerSupermicro 8x H100 SuperServer
DeploymentLocal / on-premLocal / on-prem
CapabilitiesCode, Long contextCode

Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.

Bottom line

StarCoder2 15B (~15B) is lighter than DeepSeek-Coder V2 (class) (~16B), so it runs on more modest hardware, while DeepSeek-Coder V2 (class) trades a larger footprint for more capacity. At 4-bit, StarCoder2 15B needs about 10GB versus ~11GB, 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: DeepSeek-Coder V2 (class) starts on a Intel Arc A770 16GB, StarCoder2 15B on a NVIDIA GeForce RTX 3060 12GB. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.

Pick DeepSeek-Coder V2 (class) if…

Pick DeepSeek-Coder V2 (class) if you have the memory to spare and want the larger model, or you need the longer 128K context window, or your focus is coding.

Pick StarCoder2 15B if…

Pick StarCoder2 15B if you want the lighter footprint and cheaper hardware, or your focus is coding.

Full profile
DeepSeek-Coder V2 (class)

The compact coder variants fit 16GB+ at 4-bit; larger MoE variants need 48GB+ or cloud.

Full profile
StarCoder2 15B

16GB+ GPUs at 4-bit. The largest StarCoder2 for stronger completion on one card.

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.