{ "schema_version": 1, "generated": "2026-10-20", "id": "surya-koritala-glyd--run-qwen35-9b-on-24gb-gpu", "repo": "surya-koritala/Glyd", "repo_url": "https://github.com/surya-koritala/Glyd", "repo_slug": "surya-koritala-glyd", "title": "Run Qwen3.5-9B on a 24 GB GPU with long context", "page_title": "How to run Qwen3.5-9B on a 24 GB GPU with long context with Glyd", "summary": "Fit Qwen3.5-9B on an RTX 4090 and chat in the terminal with more KV cache room.", "who": "A developer with a single 24 GB NVIDIA GPU who cannot load bf16 Qwen3.5-9B or get long context from it.", "problem": "bf16 Qwen3.5-9B runs out of memory at start on a 24 GB RTX 4090, even at 4,096 tokens.", "outcome": "A working terminal chat with Qwen3.5-9B, using Glyd's GPU-specific settings and the freed memory for KV cache.", "steps": [ "Confirm the machine runs Linux with an NVIDIA GPU (Ampere, Ada, Hopper or Blackwell) and driver 580 or newer.", "Review the install script at https://getglyd.com/install.sh if you do not trust the host, then run `curl -LsSf https://getglyd.com/install.sh | sh`.", "Run `glyd run Qwen/Qwen3.5-9B` to apply settings for your GPU and open a chat in the terminal.", "Send a test question and confirm a reply comes back.", "Note the context length Glyd sets up and compare it with the README's RTX 4090 result of 189,440 tokens." ], "agent_prompt": "Using the repo surya-koritala/Glyd on a Linux machine with and driver , install Glyd with its install script from getglyd.com and run `glyd run Qwen/Qwen3.5-9B`. Report the context length Glyd sets up and the GPU settings it applies. Verify that the terminal chat opens and returns a reply to a test question.", "agents": [ "any" ], "difficulty": "Intermediate", "time": "30 minutes", "basis": "readme", "caveat": "The :swift suffix is not lossless, so keep the plain model name when you need bf16-exact weights.", "category": "Software and DevOps", "tags": [ "Software and DevOps" ], "lang": "rust", "requirements": [ "Linux (x86_64 or aarch64) with an NVIDIA GPU: Ampere, Ada, Hopper or Blackwell, driver 580 or newer", "For the Python and vLLM steps: Python with pip, and vLLM for serving", "For the codec: Homebrew or a release tarball from the Glyd releases", "A Glyd license from suryakoritala@getglyd.com if the work is commercial, since the README says commercial use needs one" ], "risk": "none", "seen_in_the_wild": false, "mentioned_publicly": false, "risks": [ { "tag": "remote-script", "notice": "The install step pipes a script from getglyd.com directly into sh, so read it first if the host is not one you trust." } ], "best": true, "score": 1.0, "evidence": [], "url": "https://dedupedai.com/use-cases/surya-koritala-glyd/run-qwen35-9b-on-24gb-gpu/", "md": "https://dedupedai.com/use-cases/surya-koritala-glyd/run-qwen35-9b-on-24gb-gpu/index.md", "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.", "api": "https://dedupedai.com/api/v1/usecases/surya-koritala-glyd--run-qwen35-9b-on-24gb-gpu.json", "api_version": "v1" }