Here goes nothing:
I’m not really sure if I’d end up with the 9700 in my main desktop alongside my 3090 (CUDA + ROCm sounds a bit messy), or if I’d end up moving it into my 2nd desktop solely for inference, but I guess I’d need to try it out in order to find out.
One thing that I’m certain is that the extra VRAM would be really welcome.
As a long time forum member I decided to take part into this contest and with that I have published my idea what I would do with the R9700 in the following blog post …
Here’s my entry. Thank you for this awesome giveaway!
Here is my entry
My entry because I’m doing this for fun 
I started building my homelab this year with truenas and openwrt flint 2.
Asrock x570 pro4 with Pro 4650G 16 gb ecc memory. I would use the GPU for some local LLM and when I saved up for another machine it would like to learn proxmox and have the local AI run there instead.
Here is my entry!
Thanks Wendell and all involved. Really hoping AMD gets more support in the ML space, we need something to keep NVIDIA honest.
I’d be incredibly grateful for this opportunity. I’m currently running a local AI stack with Ollama (gpt-oss:20b, qwen3:8b) and ComfyUI on a single RTX 5060 Ti 16GB, which has become severely limiting for my recent projects.
Current step is “How can I combine using n8n and ollama and the other services”.
But Final gole was can be call using Bot and Designing FAN and simulate, for my family business factory.
The memory constraint forces constant model swapping—I can barely run inference on a 20B parameter model while keeping ComfyUI loaded, and running larger models is essentially impossible. I’ve been researching the R9700 extensively for the past few weeks, specifically drawn to its 128GB VRAM, which would enable me to:
With 4 of these cards, I could build a truly powerful local AI cluster for research and development—something that would have been financially out of reach otherwise. This isn’t just an upgrade; it’s the difference between “what’s theoretically possible” and “what I can actually build.”
I posted about my mountain bike suspension analysis project here - Mountain Bike Dynamics measurement and analysis
Always fun to see so many projects, I think my own project is fun too. Interaction-less Access Control and automation
[A tale of two 2080 supers.] (A tale of two 2080 SUPERs - my plead for the R9700 GPU)
I would love to run LLMs locally as nobody else needs to know that I asked AI how to do something that 99% of the population would never even consider doing in a homelab. Also I’d link my post but it appears new users cannot add links to comments so you get the below:
/t/offline-ai-homelab-hellhole-r9700-giveaway/243835?u=joshdude
https://forum.level1techs.com/t/forwardslashbuilds-building-a-verified-powershell-llm-for-it-engineers-r9700-giveaway-entry/243853
Here to try my luck at the beginning of my adventures.
i would use a r9700 as a basis for my AI-medical diagnosis tool.
I won’t tag (which could be interpreted as asking for a favorite back), but I would be happy if any of ProjectPhysX, Maurice12, or oldgreg got a GPU.
Any scientists/neuro-enthusiasts? Check out my submission for the R9700 giveaway, using machine learning to segment whole-brain imaging datasets:
I would use the rig for my daily AI hobbyist hustle. I have been trying to integrate LLMs into my daily Dermatology workflow (In an ethical manner of course). Interestingly my personal observations have been that the LLMs that perform well on established med-related benchmarks do not really provide better differentials for a case scenario than the ones that ‘apparently’ perform worse.
Secondly I will train a very niche AI image recognition algorithm for what we call ‘Nail Fold Capillaroscopy’. It will aid in early detection and prognostication of suspect connective tissue disorder patients (say Systemic lupus erythematosus, systemic sclerosis, dermatomyositis).
Hey wendell, long time viewer first time poster. Thank you for setting this up!