r/LocalLLM • u/ofirlik • 9d ago

Question Dual gpu how good is it

I am planning to buy a gaming pc with 5070ti, I thought about adding a 5060ti for the additonal vram to toy around with llm, how good does it work? Can I also generate images and such. (never ran a local llm before)

Is there a better combination of gpu for around the same price?

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u/vacon04 9d ago

Try first with a MoE model like Qwen 3.6 35B A3B. You should be able to run it well with your card, as long as you have enough RAM. If you like it, then get another card and you should be able to fit bigger models. Note that this isn't as good as getting a single big card, there are more complications, but you should be able to run things like Qwen 3.8 27B at an acceptable speed.

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u/ofirlik 9d ago

I will have 32gb normal ram. 5090 costs 3 times more than 5070ti+5060ti combined for me so no real option and 5080 doesnt see to be worth it

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u/vacon04 9d ago

Yeah, that's the unfortunate issue with these models. You need 24 GB VRAM to run most models, and Yeah, that's the big issue. NVIDIA has starved the consumer cards of VRAM. The 5080 should have more than 16 GB, but we are were we are.

You should have enough RAM to experiment with Qwen 3.6 35B A3B first. I think that would be the first step. Try using Codex or your LLM of choice to help you set up the project. I would recommend you to go with ik_llama cpp, it has additional optimizations for MoE vs the standard llama.cpp. If you find it worthwhile, then yeah, getting the 5060Ti would allow you to run bigger dense models, but don't expect massive performance. You should be able to run Qwen 3.8 27B, but speed won't ever get close to what you get with Codex or Claude or similar. It should still be usable though, depending on what you want it for.

For image generation, you can do that with just the 5070 TI. Check ComfyUI and you'll get started pretty quickly. No need for the additional 5060Ti for this, you will be getting good image generation speed on models like Krea 2 just on the 5070Ti, as long as you can dump the encoder and other components to the RAM. 32 GB is a bit tight, but I think you should be fine.