Model reference · open weights

Dream

LLMs Dream-org Text gen 1 build Open weights 96k dl/mo

Dream is an open-weight language model from Dream-org. Dream-v0-Instruct-7B (BF16) weighs 15.2 GB; the smallest configuration that runs it is 2× RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

What it is

Released byDream-org
Released2025-04-03
Parameters7.6B
VRAM15.2 GB for the weights

What it runs on

Memory and cards for Dream-v0-Instruct-7B (BF16)

15.2 GBweights, file size
57 MBcache per 1K tokens
799 MBruntime overhead, at least
131,072 tokenscontext max
CardRequests at onceContext maxMemory
8K each32K each
RTX 3060 12 GB … RTX 4060 Ti 16 GB
2 smaller cards
RTX 3090 24 GB153125K23.4 GB
RTX 4090 24 GB153124K23.4 GB
RTX 5090 32 GB317all 128K31.0 GB
L40S 48 GB5914all 128K44.0 GB
A100 80 GB13233all 128K78.2 GB
H100 80 GB12230all 128K78.1 GB
RTX PRO 6000 Blackwell 96 GB15639all 128K93.8 GB
DGX Spark (GB10) 128 GB unified18446all 128K107 GB
H200 141 GB25062all 128K138 GB
B200 180 GB32982all 128K176 GB
2× RTX 3060 12 GB
tensor parallel
133109K11.6 GB a card
2× RTX 4060 Ti 16 GB
tensor parallel
297all 128K15.4 GB a card
Memory needed at each load
Requests at once8K tokens each32K tokens each
116.5 GB17.9 GB
518.4 GB25.4 GB
819.8 GB31.1 GB
1623.5 GB46.1 GB
3231.1 GB76.2 GB
6446.1 GB136 GB

One card, with vLLM's small-card settings.

From the model card

What Dream-org says about Dream

This is the instruct model of Dream 7B, which is an open diffusion large language model with top-tier performance. More details about the model and usage can be found in the blog and github bellow:

  • Blog: https://hkunlp.github.io/blog/2025/dream/
  • Github: https://github.com/HKUNLP/Dream

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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