RichardErkhov
stabilityai japanese stablelm base gamma 7b (7B parameters) requires approximately 6.6 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 8 GB of VRAM.
Quick specs
Related models
Quick picks
Best hardware
Run this model
Quantization options
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | — |
Q3_K_S | 3 | 3.4 GB | Low | — |
NVFP4 | 4 | 3.9 GB | Medium | — |
Q4_K_M | 4 | 4.3 GB | Medium | — |
Q5_K_M | 5 | 5.0 GB | High | — |
Q6_K | 6 | 5.7 GB | High | — |
Q8_0 | 8 | 7.5 GB | Very High | — |
F16 | 16 | 14.3 GB | Maximum | — |
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
stabilityai japanese stablelm base gamma 7b (7B parameters) requires approximately 6.6 GB of VRAM with Q4_K_M quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
Yes, Intel Arc A580 8GB can run stabilityai japanese stablelm base gamma 7b with a compatibility score of 52/100. It provides 8 GB of memory and achieves approximately 58.8 tokens per second.
The recommended quantization for stabilityai japanese stablelm base gamma 7b 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 stabilityai japanese stablelm base gamma 7b: RTX 3080 10GB (score: 56/100), RTX 2080 Ti 11GB (score: 56/100), GTX 1080 Ti 11GB (score: 55/100). These provide the best combination of memory, bandwidth, and compute for running this model locally.
Yes, stabilityai japanese stablelm base gamma 7b is well-suited for chat. It was designed with these use cases in mind.
See also
