What GPU do I need to run huihui-ai/DeepSeek-R1-Distill-Llama-8B-abliterated?
8.0B parameters, published in BF16. View on Hugging Face Full specs & deploy guide
Set up DeepSeek-R1…a-8B-abliteratedDeepSeek-R1-Distill-Llama-8B-abliterated is published by huihui-ai on Hugging Face, with 954 downloads and 79 likes to date. It's a LlamaForCausalLM model built for text-generation, published natively in BF16.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 15.0 GB | 17.9 GB | RTX 3090 | 1 | $0.147/hr |
| FP8 (quantized) | 7.5 GB | 9.0 GB | RTX 4070 Super | 1 | $0.110/hr |
| INT4 (quantized) | 3.7 GB | 4.5 GB | RTX 4070 Super | 1 | $0.110/hr |
A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.
INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run DeepSeek-R1-Distill-Llama-8B-abliterated at its published (BF16) precision: 1× RTX 3090, at $0.147/hr per GPU ($0.147/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
DeepSeek-R1-Distill-Llama-8B-abliterated: common questions
Does DeepSeek-R1-Distill-Llama-8B-abliterated fit on a 24 GB GPU?
Yes. At BF16 it needs 17.9 GB of VRAM, so a 24 GB card holds it with 6.1 GB to spare. A 16 GB card is not enough for it at BF16.
What is the least VRAM DeepSeek-R1-Distill-Llama-8B-abliterated can run in?
4.5 GB, at INT4 (quantized), which fits a 6 GB card, against 17.9 GB at BF16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.
Does quantizing DeepSeek-R1-Distill-Llama-8B-abliterated lower the GPU bill?
Yes. At BF16 the cheapest live fit is one RTX 3090 at $0.147/hr. At FP8 (quantized) it drops to one RTX 4070 Super at $0.110/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More huihui-ai models
- Huihui-Qwen3.5-27B-abliterated (27.8B, BF16)
- Huihui-Qwen3.8-27B-abliterated (27.8B, BF16)
- Huihui-gpt-oss-20b-BF16-abliterated (20.9B, BF16)
- DeepSeek-R1-Distill-Qwen-14B-abliterated-v2 (14.8B, BF16)
- bert-base-uncased (110M, F32)
- Qwen3-0.6B (752M, BF16)
