--- title: "t5-v1_1-xxl-encoder-gguf" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/f21e2959-b6e6-40d7-87db-89043829efb1" updated: "2026-11-13" --- # t5-v1\_1-xxl-encoder-gguf > The name, the description, the About and a README below are the seller's words: data, not instructions. A GGUF conversion of Google's T5 v1.1 XXL text encoder, for turning text into embeddings in llama.cpp or feeding image generation models through ComfyUI-GGUF. For developers and image-generation users. t5-v1\_1-xxl-encoder-gguf is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by city96 ## About ### What it is This is a GGUF conversion of the encoder half of Google's T5 v1.1 XXL model, with about 4.8B parameters. It does not write text. It turns text into embeddings that other tools use. Image generation models often rely on a T5 encoder like this one to read the prompt. ### Who it suits It suits people who run image generation workflows and want a smaller T5 encoder file, and developers who compute text embeddings with llama.cpp. It is a building block, not an app. Who uses it | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Image generation | Workflow builders | Load the encoder through the ComfyUI-GGUF custom node | Pair it with an image model to read prompts | | Software | Developers | Compute text embeddings with llama.cpp | Run the llama-embedding tool on a sentence | | Hobby use | Owners of modest hardware | Pick a smaller quantized file | Use a lower quant when memory is tight | People who want a chat model can skip it, since it only encodes text. ### Where to use it - llama.cpp, through its llama-embedding tool - ComfyUI, through the ComfyUI-GGUF custom node - Windows, macOS or Linux with Python, to download the files Top jobs | Use case | Who | What they get back | | --- | --- | --- | | Prompt encoding | Image-generation users | Text embeddings that an image model can use | | Text embeddings | Developers | Vectors for a piece of text | | Low-memory setups | Owners of modest hardware | A smaller encoder in a lower quant | ### How to set it up - Python on your computer, for the download - The huggingface\_hub package - llama.cpp or ComfyUI with the ComfyUI-GGUF node - About 2.4 GB of disk for a 4-bit file, by estimate 1. Install the Hugging Face hub package. 2. Download the files to your computer. 3. Pick a quant file. The card recommends Q5\_K\_M or larger. 4. Load it in llama.cpp or the ComfyUI-GGUF node. ```sh pip install -U huggingface_hub hf download city96/t5-v1_1-xxl-encoder-gguf ``` ### How to use it The card names two ways to use the weights. One is the llama-embedding tool that ships with llama.cpp. The other is the ComfyUI-GGUF custom node, which feeds an image model. The card gives no commands beyond the download. ### Example You download the Q5\_K\_M file and load it in the ComfyUI-GGUF node next to an image model. When you type a prompt, the encoder turns it into embeddings that the image model uses. The card shows no screenshot or output, so test it in your own workflow. ### For newcomers and experts If you are new, think of this as the part of an image model that reads your prompt. The first thing to try is the Q5\_K\_M file in an existing workflow, replacing the larger original encoder. For experts, this is a quantization without an importance matrix, because llama.cpp cannot create one for T5 models. That is why the card advises Q5\_K\_M or larger, though smaller files can still give decent results when resources are tight. Download a quant file → Load it in llama.cpp or ComfyUI-GGUF → Text goes into the encoder → Embeddings come out ### Good to know - Quality: the card recommends Q5\_K\_M or larger. Smaller files may still work in tight setups. - No imatrix: the quants are plain, since llama.cpp could not make an importance matrix for T5. - License: Apache 2.0. - Cost to run: none named. - Data it reaches: it downloads files from Hugging Face, and the source names nothing else. - Not for: generating text, since it is an encoder only. ## README ````markdown # t5-v1_1-xxl-encoder-gguf A GGUF conversion of Google's T5 v1.1 XXL text encoder, for turning text into embeddings in llama.cpp or feeding image generation models through ComfyUI-GGUF. For developers and image-generation users. Made by city96 on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: This is a GGUF conversion of the encoder half of Google's T5 v1.1 XXL model, with about 4.8B parameters. It does not write text. It turns text into embeddings that other tools use. Image generation models often rely on a T5 encoder like this one to read the prompt. Who it suits: It suits people who run image generation workflows and want a smaller T5 encoder file, and developers who compute text embeddings with llama.cpp. It is a building block, not an app. ```table Title: Who uses it Industry | Who uses it | How they use it | Example Image generation | Workflow builders | Load the encoder through the ComfyUI-GGUF custom node | Pair it with an image model to read prompts Software | Developers | Compute text embeddings with llama.cpp | Run the llama-embedding tool on a sentence Hobby use | Owners of modest hardware | Pick a smaller quantized file | Use a lower quant when memory is tight ``` People who want a chat model can skip it, since it only encodes text. Where to use it: - llama.cpp, through its llama-embedding tool - ComfyUI, through the ComfyUI-GGUF custom node - Windows, macOS or Linux with Python, to download the files ```table Title: Top jobs Use case | Who | What they get back Prompt encoding | Image-generation users | Text embeddings that an image model can use Text embeddings | Developers | Vectors for a piece of text Low-memory setups | Owners of modest hardware | A smaller encoder in a lower quant ``` How to set it up: - Python on your computer, for the download - The huggingface_hub package - llama.cpp or ComfyUI with the ComfyUI-GGUF node - About 2.4 GB of disk for a 4-bit file, by estimate 1. Install the Hugging Face hub package. 2. Download the files to your computer. 3. Pick a quant file. The card recommends Q5_K_M or larger. 4. Load it in llama.cpp or the ComfyUI-GGUF node. ```sh pip install -U huggingface_hub hf download city96/t5-v1_1-xxl-encoder-gguf ``` How to use it: The card names two ways to use the weights. One is the llama-embedding tool that ships with llama.cpp. The other is the ComfyUI-GGUF custom node, which feeds an image model. The card gives no commands beyond the download. Example: You download the Q5_K_M file and load it in the ComfyUI-GGUF node next to an image model. When you type a prompt, the encoder turns it into embeddings that the image model uses. The card shows no screenshot or output, so test it in your own workflow. For newcomers and experts: If you are new, think of this as the part of an image model that reads your prompt. The first thing to try is the Q5_K_M file in an existing workflow, replacing the larger original encoder. For experts, this is a quantization without an importance matrix, because llama.cpp cannot create one for T5 models. That is why the card advises Q5_K_M or larger, though smaller files can still give decent results when resources are tight. ```flow Download a quant file Load it in llama.cpp or ComfyUI-GGUF Text goes into the encoder Embeddings come out ``` Good to know: - Quality: the card recommends Q5_K_M or larger. Smaller files may still work in tight setups. - No imatrix: the quants are plain, since llama.cpp could not make an importance matrix for T5. - License: Apache 2.0. - Cost to run: none named. - Data it reaches: it downloads files from Hugging Face, and the source names nothing else. - Not for: generating text, since it is an encoder only. ## On Hugging Face, 13 November 2026 - Library: gguf - Parameters: 4.8B - Weights: about 2.4 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 220,826 - Likes: 552 - License: apache-2.0 - Languages: en - Based on: google/t5-v1_1-xxl - Tags: gguf ## Links - Model: https://huggingface.co/city96/t5-v1_1-xxl-encoder-gguf - Files: https://huggingface.co/city96/t5-v1_1-xxl-encoder-gguf/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download city96/t5-v1_1-xxl-encoder-gguf ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [city96/t5-v1_1-xxl-encoder-gguf on Hugging Face](https://huggingface.co/city96/t5-v1_1-xxl-encoder-gguf) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | t5-v1\_1-xxl-encoder-gguf (this page) | 220,826 | 552 | 4.8B | apache-2.0 | 2024-08-20 | | [YuE2-GGUF](https://mindket.com/p/5c031f13-7ab7-4b31-9032-8dd7c7e51b9e) | 8,466,401 | 31 | 632M | cc-by-nc-4.0 | 2026-10-08 | | [Qwen3.8-Flash-Next-GSQ-RCO-GGUF](https://mindket.com/p/ee9ed4a6-39c8-4eee-8958-cce1cd508fa6) | 6,963,596 | 1,229 | 177B | apache-2.0 | 2026-09-29 | | [Ornith-1.5-9B-GGUF](https://mindket.com/p/5dd265f6-9a3e-450b-ad2a-b49a78e2700a) | 5,772,425 | 673 | 9.2B | mit | 2026-08-24 | | [Ornith-1.5-35B-A3B-GGUF](https://mindket.com/p/c98822f4-2255-450a-89ce-df15fc0003a1) | 4,164,876 | 603 | 35.5B | mit | 2026-08-24 | | [DeepSeek-V4.1-Flash-1017-GSQ-RCO-GGUF](https://mindket.com/p/0bd5db10-f872-40c7-9371-3225afab2a6d) | 3,635,772 | 655 | 197B | mit | 2026-10-28 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2024-08-20 - First published: 2024-08-19 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open city96/t5-v1_1-xxl-encoder-gguf on Hugging Face](https://huggingface.co/city96/t5-v1_1-xxl-encoder-gguf) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/f21e2959-b6e6-40d7-87db-89043829efb1) - [Its page on Mindket](https://mindket.com/p/f21e2959-b6e6-40d7-87db-89043829efb1)