Models › Mellum2.1-12B-A2.5B-Thinking
Mellum2.1-12B-A2.5B-Thinking: VRAM needs and speed by GPU
At Q4_K_M, Mellum2.1-12B-A2.5B-Thinking needs about 9.9 GB of VRAM. No measured runs yet. Speeds below are estimates. Submit a run.
12.15B parameters (mixture-of-experts, ~2.5B active) · license: apache-2.0 · 131,072-token context · GGUF published Oct 8, 2026 · GGUF files on Hugging Face
Memory needed per quantization
| Quant | File size | Needs (estimate) | Smallest card it fits |
|---|---|---|---|
| IQ2_M | 5.4 GB | 6.5 GB | 8 GB cards |
| Q2_K | 5.5 GB | 6.6 GB | 8 GB cards |
| Q3_K_S | 6.1 GB | 7.2 GB | 8 GB cards |
| IQ3_XXS | 6.3 GB | 7.4 GB | 8 GB cards |
| IQ3_XS | 6.3 GB | 7.4 GB | 8 GB cards |
| Q3_K_M | 6.7 GB | 7.8 GB | 12 GB cards |
| IQ4_XS | 7.0 GB | 8.1 GB | 12 GB cards |
| Q4_0 | 7.0 GB | 8.1 GB | 12 GB cards |
| Q3_K_L | 7.1 GB | 8.2 GB | 12 GB cards |
| IQ3_M | 7.2 GB | 8.3 GB | 12 GB cards |
| IQ4_NL | 7.7 GB | 8.8 GB | 12 GB cards |
| Q4_1 | 7.7 GB | 8.8 GB | 12 GB cards |
| Q4_K_S | 7.9 GB | 9.0 GB | 12 GB cards |
| Q4_K_M | 8.8 GB | 9.9 GB | 12 GB cards |
| Q5_K_S | 9.0 GB | 10.1 GB | 12 GB cards |
| Q4_K_L | 9.2 GB | 10.3 GB | 12 GB cards |
| Q5_K_M | 10.0 GB | 11.1 GB | 12 GB cards |
| Q6_K_S | 11.1 GB | 12.2 GB | 16 GB cards |
| Q6_K | 11.5 GB | 12.6 GB | 16 GB cards |
| Q6_K_L | 11.8 GB | 12.9 GB | 16 GB cards |
| Q8_0 | 12.9 GB | 14.0 GB | 16 GB cards |
| BF16 | 24.3 GB | 25.4 GB | 32 GB cards |
Expected speed on popular hardware
| Hardware | Best quant that fits | Expected tok/s |
|---|---|---|
| NVIDIA RTX 3060 | Q5_K_M | 74.2 estimate |
| NVIDIA RTX 4060 Ti | IQ3_XXS | 93.5 estimate |
| NVIDIA RTX 3090 | Q8_0 | 122 estimate |
| NVIDIA RTX 4090 | Q8_0 | 135 estimate |
| NVIDIA RTX 5090 | Q8_0 | 213 estimate |
| AMD Radeon RX 7900 XTX | Q8_0 | 136 estimate |
| Apple M4 Pro (20-core GPU) (64 GB) | Q8_0 | 43.0 estimate |
| Apple M3 Max (40-core GPU) (64 GB) | Q8_0 | 62.8 estimate |
| AMD Ryzen AI Max+ 395 (Radeon 8060S) | Q8_0 | 38.6 estimate |
Too big for your card?
Run Mellum2.1-12B-A2.5B-Thinking on a rented 24-80 GB GPU by the hour.
Rent a bigger GPU on RunPodAffiliate link: if you sign up, RigBench may earn a referral credit. It never affects rankings or numbers.