Bartowski
starcoder2 15b instruct v0.1 (15B parameters) requires approximately 12.7 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 15 GB of VRAM.
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No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | — |
Q3_K_S | 3 | 7.4 GB | Low | — |
NVFP4 | 4 | 8.4 GB | Medium | — |
Q4_K_M | 4 | 9.2 GB | Medium | — |
Q5_K_M | 5 | 10.8 GB | High | — |
Q6_K | 6 | 12.3 GB | High | — |
Q8_0 | 8 | 16.1 GB | Very High | — |
F16 | 16 | 30.7 GB | Maximum | — |
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
starcoder2 15b instruct v0.1 (15B parameters) requires approximately 12.7 GB of VRAM with Q4_K_M quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
Yes, RX 7600 XT 16GB can run starcoder2 15b instruct v0.1 with a compatibility score of 48/100. It provides 16 GB of memory and achieves approximately 18.3 tokens per second.
The recommended quantization for starcoder2 15b instruct v0.1 is Q4_K_M, which offers the best balance between model quality and memory efficiency. Higher quantizations preserve more quality but require more VRAM.
The top recommended hardware for starcoder2 15b instruct v0.1: RTX A4500 20GB (score: 55/100), RX 7900 XT 20GB (score: 55/100), RTX 4090 24GB (score: 54/100). These provide the best combination of memory, bandwidth, and compute for running this model locally.
Yes, starcoder2 15b instruct v0.1 is well-suited for chat as well as coding. It was designed with these use cases in mind.
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