Models › Qwen2.5-Coder-7B-Instruct-abliterated
Qwen2.5-Coder-7B-Instruct-abliterated: VRAM needs and speed by GPU
At Q4_K_M, Qwen2.5-Coder-7B-Instruct-abliterated needs about 5.7 GB of VRAM. No measured runs yet. Speeds below are estimates. Submit a run.
7.62B parameters · license: apache-2.0 · 32,768-token context · GGUF published Nov 13, 2024 · GGUF files on Hugging Face
Memory needed per quantization
| Quant | File size | Needs (estimate) | Smallest card it fits |
|---|---|---|---|
| IQ2_M | 2.8 GB | 3.8 GB | 8 GB cards |
| Q2_K | 3.0 GB | 4.0 GB | 8 GB cards |
| IQ3_XS | 3.3 GB | 4.3 GB | 8 GB cards |
| Q3_K_S | 3.5 GB | 4.5 GB | 8 GB cards |
| Q2_K_L | 3.5 GB | 4.5 GB | 8 GB cards |
| IQ3_M | 3.6 GB | 4.6 GB | 8 GB cards |
| Q3_K_M | 3.8 GB | 4.8 GB | 8 GB cards |
| Q3_K_L | 4.1 GB | 5.1 GB | 8 GB cards |
| IQ4_XS | 4.2 GB | 5.2 GB | 8 GB cards |
| Q4_0 | 4.4 GB | 5.4 GB | 8 GB cards |
| Q4_K_S | 4.5 GB | 5.4 GB | 8 GB cards |
| Q3_K_XL | 4.6 GB | 5.6 GB | 8 GB cards |
| Q4_K_M | 4.7 GB | 5.7 GB | 8 GB cards |
| Q4_K_L | 5.1 GB | 6.1 GB | 8 GB cards |
| Q5_K_S | 5.3 GB | 6.3 GB | 8 GB cards |
| Q5_K_M | 5.4 GB | 6.4 GB | 8 GB cards |
| Q5_K_L | 5.8 GB | 6.8 GB | 8 GB cards |
| Q6_K | 6.3 GB | 7.2 GB | 8 GB cards |
| Q6_K_L | 6.5 GB | 7.5 GB | 12 GB cards |
| Q8_0 | 8.1 GB | 9.1 GB | 12 GB cards |
| F16 | 15.2 GB | 16.2 GB | 24 GB cards |
Expected speed on popular hardware
| Hardware | Best quant that fits | Expected tok/s |
|---|---|---|
| NVIDIA RTX 3060 | Q8_0 | 38.0 estimate |
| NVIDIA RTX 4060 Ti | Q6_K | 39.1 estimate |
| NVIDIA RTX 3090 | Q8_0 | 81.0 estimate |
| NVIDIA RTX 4090 | Q8_0 | 89.7 estimate |
| NVIDIA RTX 5090 | Q8_0 | 142 estimate |
| AMD Radeon RX 7900 XTX | Q8_0 | 90.1 estimate |
| Apple M4 Pro (20-core GPU) (64 GB) | Q8_0 | 28.6 estimate |
| Apple M3 Max (40-core GPU) (64 GB) | Q8_0 | 41.7 estimate |
| AMD Ryzen AI Max+ 395 (Radeon 8060S) | Q8_0 | 25.7 estimate |
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