Model reference · open weights

gemma

LLMs google Text gen 2 builds Open, with conditions 134k dl/mo

gemma is an open-weight language model from Google. gemma-2b (BF16) weighs 10.0 GB; the smallest configuration that runs it is RTX 3060 12 GB.

  • Gemma is a lightweight, open-weight text generation model developed by Google, designed for tasks such as question answering, summarization, and reasoning.
  • This 2.5B parameter version is a decoder-only large language model trained on 6 trillion tokens with an 8192 token context length.
  • It is available under the Gemma license and supports deployment on limited resources like laptops or desktops.

Summary of the google/gemma-2b model card, 2026-10-01

What it is

Released byGoogle
Released2024-02-08
Parameters2.5B
VRAM10.0 GB for the weights

What it runs on

Memory and cards for gemma-2b (BF16)

10.0 GBweights, file size
651 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 GBtight
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
2× RTX 3060 12 GB
split by layers (llama.cpp)
fits

Builds

Sizes, precisions & builds

BuildParamsPrecisionWeightsSmallest setup
gemma-2b (above) ↗ 2.5BBF16 10.0 GBRTX 3060 12 GB
gemma-7b ↗ 8.5BBF16 34.2 GBL40S 48 GB

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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