Qwen2.5-Coder 1.5B vs StarCoder2 3B
Size, context window, license, approximate VRAM and the minimum local hardware each model needs — computed from our catalog and compatibility engine, not benchmarks.
| Qwen2.5-Coder 1.5B | StarCoder2 3B | |
|---|---|---|
| Parameters | 1.5B | 3B |
| Context window | 32K tokens | 16K tokens |
| License | Apache-2.0 | BigCode OpenRAIL-M |
| ~VRAM @ 4-bit (Q4_K_M) | ~1 GB | ~2.2 GB |
| ~VRAM @ 8-bit (Q8_0) | ~1.7 GB | ~3.4 GB |
| Minimum device | NVIDIA GeForce RTX 3060 12GB | NVIDIA GeForce RTX 3060 12GB |
| Recommended device | Supermicro 8x H100 SuperServer | Supermicro 8x H100 SuperServer |
| Deployment | Local / on-prem | Local / on-prem |
| Capabilities | Code | Code |
Highlighted cells mark the lighter / longer / more permissive side per row, for local deployment. Informational rows have no winner.
Bottom line
Qwen2.5-Coder 1.5B (~1.5B) is lighter than StarCoder2 3B (~3B), so it runs on more modest hardware, while StarCoder2 3B trades a larger footprint for more capacity. At 4-bit, Qwen2.5-Coder 1.5B needs about 1GB versus ~2.2GB, a meaningful gap when choosing a GPU. Qwen2.5-Coder 1.5B advertises the longer context window (32K vs 16K), which helps with long documents. Qwen2.5-Coder 1.5B's Apache-2.0 license is the more permissive of the two for commercial use. Both can start on a NVIDIA GeForce RTX 3060 12GB-class machine. Figures are approximate working-set estimates, not benchmarks — verify the exact release before committing hardware.
Pick Qwen2.5-Coder 1.5B if you want the lighter footprint and cheaper hardware, or you need the longer 32K context window, or you want the more permissive Apache-2.0 license.
Pick StarCoder2 3B if you have the memory to spare and want the larger model, or your focus is coding.
Runs on a CPU or any small GPU. The tiny coder for fast, private in-editor completion.
Runs on a CPU or any small GPU. A tiny code model for fast, private completion.
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.