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Model reference · open weights

t5gemma-ul2

LLMs google Text gen 1 build Open, with conditions 50k dl/mo

t5gemma-ul2 is an open-weight language model from Google. t5gemma-2b-2b-ul2-it (BF16) weighs 11.2 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.

  • T5Gemma is a family of lightweight encoder-decoder research models from Google, designed for text-to-text generation tasks such as question answering, summarization, and reasoning.
  • The specific t5gemma-ul2 variant features a 2B encoder and 2B decoder adapted using UL2, with a total of 5.6B parameters.
  • It is available in English under the gemma license and is suitable for deployment in resource-limited environments.

Summary of the google/t5gemma-2b-2b-ul2-it model card, 2026-10-01

Hugging Face ↗GitHub ↗Paper ↗

What it is

Released byGoogle
Released2025-06-19
Parameters5.6B
VRAM11.2 GB for the weights

What it runs on

Memory and cards for t5gemma-2b-2b-ul2-it (BF16)

11.2 GBweights, file size
762 MBruntime overhead, at least

How much memory each request adds isn't estimated yet for this architecture. The weights need at least the cards below, plus room for the context.

CardWeights alone
RTX 3060 12 GBdoes not fit
RTX 4060 Ti 16 GBfits
RTX 3090 24 GBfits
RTX 4090 24 GBfits
RTX 5090 32 GBfits
L40S 48 GBfits
A100 80 GBfits
H100 80 GBfits
RTX PRO 6000 Blackwell 96 GBfits
DGX Spark (GB10) 128 GB unifiedfits
H200 141 GBfits
B200 180 GBfits

How it works

How language models work

Your prompttext / messagesTransformerattention over tokensNext-token loopgenerate + streamResponsetext · tool callsA language model reads your tokens and predicts the next one, again and again, streaming the reply back.
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