What GPU do I need to run yandex/AliceAI-Foundation-80B-A3B-Base?
81.3B parameters, published in BF16. View on Hugging Face
AliceAI-Foundation-80B-A3B-Base is published by yandex on Hugging Face, with 4,786 downloads and 380 likes to date. It's a AliceAIForCausalLM 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 | 151.4 GB | 181.7 GB | RTX A5000 | 8 | $1.41/hr |
| FP8 (quantized) | 75.7 GB | 90.8 GB | RTX PRO 6000 | 1 | $1.53/hr |
| cheaper alt. | RTX 4090 | 2 | $0.962/hr | ||
| INT4 (quantized) | 37.9 GB | 45.4 GB | RTX A6000 | 1 | $0.363/hr |
| cheaper alt. | RTX A5000 | 2 | $0.352/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 AliceAI-Foundation-80B-A3B-Base at its published (BF16) precision: 8× RTX A5000, at $0.176/hr per GPU ($1.41/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
AliceAI-Foundation-80B-A3B-Base: common questions
Can AliceAI-Foundation-80B-A3B-Base run on a single GPU?
No. At BF16 it needs 181.7 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest capable card in the live feed is a 24.0 GB RTX A5000, and it takes 8 of them.
How many GPUs do I need to run AliceAI-Foundation-80B-A3B-Base?
8 at BF16. It needs 181.7 GB of VRAM and the cheapest capable live offer is a 24.0 GB RTX A5000, so 8 of them come to $1.41/hr in total.
Does quantizing AliceAI-Foundation-80B-A3B-Base lower the GPU bill?
Yes. At BF16 the cheapest live fit is 8 RTX A5000 cards at $1.41/hr. At INT4 (quantized) it drops to one RTX A6000 at $0.363/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More yandex models
- bert-base-uncased (110M, F32)
- Qwen3-0.6B (752M, BF16)
- gpt2 (137M, F32)
- Qwen3-8B (8.2B, BF16)
- Qwen3.6-35B-A3B-FP8 (36.0B, F8_E4M3)
- Qwen3.5-9B (9.7B, BF16)
Related reading: RTX A5000 pricing and specs, The NVIDIA Inception program, explained, Google Colab alternatives for dedicated GPU access, Free GPU credits for students and researchers, and RunPod volume disk vs. network volume, compared.