What GPU do I need to run deep-principle/Hydrogen-1.0?
753.3B parameters, published in BF16. View on Hugging FaceGated
Set up Hydrogen-1.0Hydrogen-1.0 is published by deep-principle on Hugging Face, with 26,024 downloads and 279 likes to date. It's a GlmMoeDsaForCausalLM model built for text-generation, published natively in BF16, and gated: you'll need to accept the model's terms on Hugging Face before downloading weights.
VRAM required & cheapest live GPU fit
Required VRAM = weight size at each precision times a flat 1.2 overhead for activations and fragmentation. The KV-cache grows with context and is not in that factor; it is listed per model below where the architecture is published. Full formula and assumptions: methodology.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 1403.2 GB | 1683.8 GB | No capable live offer found | – | – |
| FP8 (quantized) | 701.6 GB | 841.9 GB | No capable live offer found | – | – |
| INT4 (quantized) | 350.8 GB | 421.0 GB | RTX PRO 6000 | 5 | $6.88/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.
Hydrogen-1.0: KV cache by context length
The KV cache is the memory the attention layers hold for every token of context, on top of the weights. It is not part of the flat 1.2x overhead in the table above, grows with context length and with every concurrent request, and is why a long-context deployment needs more VRAM than the table shows.
KV-cache size for Hydrogen-1.0 is not published for this architecture, so no figure is shown.
Hydrogen-1.0: common questions
Can Hydrogen-1.0 run on a single GPU?
Not on a desktop card. At BF16 it needs 1683.8 GB of VRAM, more than a single 32 GB desktop card holds. No card currently listed on the marketplace both supports BF16 and has enough VRAM for it, so how many it would take is not something this page can answer today.
Do I need approval to download Hydrogen-1.0?
Yes. deep-principle gates this repository on Hugging Face, so you have to accept its terms with a signed-in account before the weights will download. It does not change the 1683.8 GB the model needs once you have them.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More GLM-5 models
- GLM-5.2-FP8 (753.3B, F8_E4M3)
- GLM-5.2 (753.3B, BF16)
- GLM-5.3 (753.3B, F8_E4M3)
- GLM-5.3-BF16 (753.3B, BF16)
- penclaw-GLM-5.3-abliterated (753.3B, BF16)
Lineage
Based on GLM-5.3.
Alternatives at this size
Other models for text-generation within about a third of Hydrogen-1.0's 753.3B parameters, from other model lines.
- DeepSeek-R1 (684.5B, F8_E4M3)
- NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 (560.5B, BF16)
- Kimi-K2-Instruct (1026.4B, F8_E4M3)
- A.X-K2 (691.7B, F8_E4M3)
- MiMo-V2.5-Pro (1023.2B, F8_E4M3)
More on Hydrogen-1.0
Related reading: H100 pricing and specs, How much VRAM you need for LLMs, Serving LLMs with vLLM, vLLM vs TensorRT-LLM vs SGLang, Best GPU for LLM inference, and What AI model fine-tuning is.
