--- title: "SenseNova-6.8-Code2Video GSQ-RCO GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/78f43f93-2a33-400e-a778-71e873414af0" updated: "2026-11-13" --- # SenseNova-6.8-Code2Video GSQ-RCO GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs a 26.9B parameter SenseNova-6.8-Code2Video model as a mixed precision GGUF file, in a terminal chat or a local server. For people who want that model on their own hardware. SenseNova-6.8-Code2Video GSQ-RCO 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 OliviaRossi ## About ### What it is This is a GGUF quantization of sensenova's SenseNova-6.8-Code2Video, made by OliviaRossi. Rather than storing every weight at one precision, it gives each tensor its own type, using the GSQ and RCO method from ISTA-DASLab, in a profile called GSQ-RCO-IQ3\_S. The model has 26.9B parameters. The card does not describe what the base model does, but its name and sample prompt point to video script work. ### Who it suits It suits people who run models locally from GGUF files and want a 26.9B model in a smaller form. Developers and video writers are the likeliest users. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Run a local model server with an OpenAI compatible interface | llama-server listening on port 8080 | | Media | Video creators and script writers | Draft video scripts on their own machine | The sample prompt Generate a video script: | | Research | Quantization researchers | Study a per tensor mixed precision recipe | Attention layers kept at higher precision than feed forward layers | You can skip it if you want the original unquantized model, since this file trades precision for size. ### Where to use it - A terminal, through the llama-cli program - A local server, through llama-server, which offers an OpenAI compatible interface - Windows, macOS or Linux with Python, to download the file | Use case | Who | What they get back | | --- | --- | --- | | Chat in a terminal | Anyone with a GGUF runtime | Replies to a typed prompt | | Serve a local API | Developers | An endpoint other tools can call on port 8080 | | Draft a video script | Video writers | Script text written by the model | ### How to set it up - Python and pip, to download the file - The llama-cli and llama-server programs, run from the folder that holds them - Memory: Hugging Face estimates the size of a 4-bit copy of this model at 13.4 GB 1. Install the Hugging Face hub package. 2. Download the model files to your computer. 3. Point llama-cli or llama-server at the GGUF file with the commands below. ```sh pip install -U huggingface_hub hf download OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF ``` ### How to use it Start a terminal chat or a local server with the file. The card shows both commands. ```bash # Terminal Chat ./llama-cli -m SenseNova-6.8-Code2Video-GSQ-RCO-IQ3_S.gguf -p "Generate a video script:" -ngl 99 # OpenAI-Compatible Server ./llama-server -m SenseNova-6.8-Code2Video-GSQ-RCO-IQ3_S.gguf --port 8080 -ngl 99 -c 32768 ``` | Tool | What it does | | --- | --- | | ./llama-cli | Chats with the model in a terminal | | ./llama-server | Starts a server with an OpenAI compatible interface | | -m | Points to the GGUF file | | -ngl 99 | Offloads up to 99 layers to the GPU | | -c 32768 | Sets the context window to 32768 tokens | | --port 8080 | Sets the port the server uses | ### Example Run the llama-cli command with the prompt Generate a video script: and the file name as shown. The model continues from that prompt and writes script text in the terminal. ### For newcomers and experts Quantization stores a model's numbers with fewer bits, which makes the file smaller and easier to run at home. For a first try, download the file and run the llama-cli command, then change the prompt to your own topic. A recipe called RCO picks a type for each tensor. Attention projections attn\_qkv and attn\_gate get IQ4\_XS, Q5\_K and Q6\_K. Feed forward layers ffn\_down and ffn\_up get IQ2\_S and IQ2\_XXS. SSM and normalization layers stay at BF16 and F32. The tensor map and the importance matrix come from a Qwen3.8 27B setup. The original SenseNova weights → RCO picks a type for each tensor → A mixed precision GGUF file is written → llama-cli or llama-server loads the file → You chat or call the local API ### Good to know The card gives no quality scores or comparison with the original model, so test it on your own tasks. - License: Apache 2.0 - Cost to run: none named, you use your own hardware - Data it reaches: files on your computer, and a server on port 8080 if you start llama-server - Not for: judging quality from the card, which lists no benchmark results ## README ````markdown # SenseNova-6.8-Code2Video GSQ-RCO GGUF Runs a 26.9B parameter SenseNova-6.8-Code2Video model as a mixed precision GGUF file, in a terminal chat or a local server. For people who want that model on their own hardware. Made by OliviaRossi 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 quantization of sensenova's SenseNova-6.8-Code2Video, made by OliviaRossi. Rather than storing every weight at one precision, it gives each tensor its own type, using the GSQ and RCO method from ISTA-DASLab, in a profile called GSQ-RCO-IQ3_S. The model has 26.9B parameters. The card does not describe what the base model does, but its name and sample prompt point to video script work. Who it suits: It suits people who run models locally from GGUF files and want a 26.9B model in a smaller form. Developers and video writers are the likeliest users. ```table Industry | Who uses it | How they use it | Example Software | Developers | Run a local model server with an OpenAI compatible interface | llama-server listening on port 8080 Media | Video creators and script writers | Draft video scripts on their own machine | The sample prompt Generate a video script: Research | Quantization researchers | Study a per tensor mixed precision recipe | Attention layers kept at higher precision than feed forward layers ``` You can skip it if you want the original unquantized model, since this file trades precision for size. Where to use it: - A terminal, through the llama-cli program - A local server, through llama-server, which offers an OpenAI compatible interface - Windows, macOS or Linux with Python, to download the file ```table Use case | Who | What they get back Chat in a terminal | Anyone with a GGUF runtime | Replies to a typed prompt Serve a local API | Developers | An endpoint other tools can call on port 8080 Draft a video script | Video writers | Script text written by the model ``` How to set it up: - Python and pip, to download the file - The llama-cli and llama-server programs, run from the folder that holds them - Memory: Hugging Face estimates the size of a 4-bit copy of this model at 13.4 GB 1. Install the Hugging Face hub package. 2. Download the model files to your computer. 3. Point llama-cli or llama-server at the GGUF file with the commands below. ```sh pip install -U huggingface_hub hf download OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF ``` How to use it: Start a terminal chat or a local server with the file. The card shows both commands. ```bash # Terminal Chat ./llama-cli -m SenseNova-6.8-Code2Video-GSQ-RCO-IQ3_S.gguf -p "Generate a video script:" -ngl 99 # OpenAI-Compatible Server ./llama-server -m SenseNova-6.8-Code2Video-GSQ-RCO-IQ3_S.gguf --port 8080 -ngl 99 -c 32768 ``` ```table Tool | What it does ./llama-cli | Chats with the model in a terminal ./llama-server | Starts a server with an OpenAI compatible interface -m | Points to the GGUF file -ngl 99 | Offloads up to 99 layers to the GPU -c 32768 | Sets the context window to 32768 tokens --port 8080 | Sets the port the server uses ``` Example: Run the llama-cli command with the prompt Generate a video script: and the file name as shown. The model continues from that prompt and writes script text in the terminal. For newcomers and experts: Quantization stores a model's numbers with fewer bits, which makes the file smaller and easier to run at home. For a first try, download the file and run the llama-cli command, then change the prompt to your own topic. A recipe called RCO picks a type for each tensor. Attention projections attn_qkv and attn_gate get IQ4_XS, Q5_K and Q6_K. Feed forward layers ffn_down and ffn_up get IQ2_S and IQ2_XXS. SSM and normalization layers stay at BF16 and F32. The tensor map and the importance matrix come from a Qwen3.8 27B setup. ```flow The original SenseNova weights RCO picks a type for each tensor A mixed precision GGUF file is written llama-cli or llama-server loads the file You chat or call the local API ``` Good to know: The card gives no quality scores or comparison with the original model, so test it on your own tasks. - License: Apache 2.0 - Cost to run: none named, you use your own hardware - Data it reaches: files on your computer, and a server on port 8080 if you start llama-server - Not for: judging quality from the card, which lists no benchmark results ## On Hugging Face, 13 November 2026 - Library: transformers - Parameters: 26.9B - Weights: about 13.4 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 13,778 - Likes: 9 - License: apache-2.0 - Based on: sensenova/SenseNova-6.8-Code2Video - Tags: transformers, gguf, llama.cpp, quantized, gsq-rco, iq3_s, non-uniform-quantization, code2video, imatrix ## Links - Model: https://huggingface.co/OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF - Files: https://huggingface.co/OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF on Hugging Face](https://huggingface.co/OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-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 | | --- | --- | --- | --- | --- | --- | | SenseNova-6.8-Code2Video GSQ-RCO GGUF (this page) | 13,778 | 9 | 26.9B | apache-2.0 | 2026-10-29 | | [Qwen3.8-27B-QSA-GSQ-RCO-GGUF](https://mindket.com/p/ce87f21f-5958-44f5-a952-a31b4dc6e24e) | 2,784 | 6 | 1.9B | apache-2.0 | 2026-11-08 | | [Qwen3.8-27B-Ridge-GGUF](https://mindket.com/p/f254bd76-fee2-4e04-80ac-a73f9621c088) | 292,932 | 369 | 27.3B | apache-2.0 | 2026-08-15 | | [MiniCPM-V-4.7-1B-gguf](https://mindket.com/p/f793ef5c-72e1-400b-91fa-5b2c31b01f3f) | 168,636 | 114 | 1B | apache-2.0 | 2026-11-11 | | [Ripple-65B-Preview-GGUF](https://mindket.com/p/00143f02-5553-4372-8620-836dbb7dfec1) | 100,818 | 53 | 64.8B | apache-2.0 | 2026-11-06 | | [Unlimited-OCR-2-GGUF](https://mindket.com/p/0d8a371b-6f90-4b59-8dd6-b520e35b577b) | 8,452 | 8 | 2.9B | mit | 2026-11-01 | 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: 2026-10-29 - First published: 2026-10-28 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF on Hugging Face](https://huggingface.co/OliviaRossi/SenseNova-6.8-Code2Video-GSQ-RCO-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/78f43f93-2a33-400e-a778-71e873414af0) - [Its page on Mindket](https://mindket.com/p/78f43f93-2a33-400e-a778-71e873414af0)