LLMBOTTLENECK.COM
Hugging Face repository / answered by gemma-4-E2B-it

RinggAI/ringg-router-e2b: what it needs to run

RinggAI/ringg-router-e2b is a fine-tune of google/gemma-4-E2B-it. Its configuration matches gemma-4-E2B-it's on every field that decides memory, so gemma-4-E2B-it's requirements are this repository's.

Answered by

Geometrypublished data. Both configurations are published files, read at the revisions named below and compared field by field. Not a test that the model loads.

gemma-4-E2B-it (google/gemma-4-E2B-it) — every compared field is stated by both and equal.

gemma-4-E2B-it: weight-file size by format

FormatSizeRangeBasis
FP1610.3 GB7.17 GB – 10.4 GBsize range
Q8_05.45 GB3.81 GB – 6.26 GBsize range
Q6_K4.21 GB2.94 GB – 5.21 GBsize range
Q5_K_M3.66 GB2.47 GB – 5.21 GBsize range
Q5_03.58 GB2.47 GB – 5.21 GBsize range
Q4_K_M3.14 GB2.02 GB – 5.21 GBsize range
Q4_02.98 GB2.02 GB – 5.21 GBsize range
Q3_K_M2.56 GB1.54 GB – 5.21 GBsize range
Q2_K2.03 GB1.18 GB – 5.21 GBsize range

These are gemma-4-E2B-it’s sizes. A model with the same geometry quantizes to the same size, to within any difference in parameter count noted above. Which devices hold each, and how fast they run it, is on gemma-4-E2B-it’s page.

What was read, and where

  1. RinggAI/ringg-router-e2b at revision ec2f6487bb4e is tagged by its publisher as a fine-tune of google/gemma-4-E2B-it.
  2. RinggAI/ringg-router-e2b/config.json at ec2f6487bb4e was compared with google/gemma-4-E2B-it/config.json at 3e22461f65e8, the revision the catalogue pins: layers and their pattern, widths, head counts, experts, latent and recurrent dimensions, vocabulary, tied embeddings and any vision or audio tower.
Licence, as tagged
apache-2.0
Parameters in its safetensors index
5.1B
Task, as tagged
text-generation
Last changed on Hugging Face
2026-09-29

Publishing this model? A badge for its card

The memory badge for this repository

[![Memory to run this model, from llmbottleneck.com](https://llmbottleneck.com/badge/RinggAI/ringg-router-e2b)](https://llmbottleneck.com/hf/RinggAI/ringg-router-e2b)

It states the memory to run the model at Q4_K_M with 8,192 tokens of context — built on this repository’s own Q4_K_M file when it publishes one — and links back to this page, where the evidence is.

Resolve another repository

The same answer as JSON: GET /v1/resolve?repo=RinggAI/ringg-router-e2b, with a free key from /keys.

llmbottleneck
catalogue 2026-10-03models 327devices 135