2026-09-15 14:49 UTC
I have a 7900 XTX with 24GB of VRAM where I am running Qwen 3.8 27B. I traded in my RTX 3070 and got it for around $700 recently. That model performs pretty similarly to Claude Sonnet 5 in performance for coding and certain other tasks. I was running Qwen 3.6 35B-A3B on the 3070 before and I still run it on my server with a 4060 and 32GB of RAM, and that model is more like Claude Haiku.
I expect 3.8 35B-A3B should be released pretty soon and provide a nice bump in performance.
I regularly follow this guy’s YouTube channel, and his latest video is about running a 177B model on his RTX 3060 via SSD offloading and getting Opus-like performance for certain tasks: m.youtube.com/watch?v=IH8XmxiwliQ.
Supposedly, open weight models that run in a data center are like 4 months behind the frontier at this point, and what can run on a gaming PC is progressing rapidly as well while the exponential gains at the frontier have largely turned into incremental gains at this point.
Replies (2)
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@naught@sh.itjust.works 2026-09-15 16:05
This is great info! I’ve been using OpenCode Go because I only have 16GB to work with and their limits are pretty generous. Looking forward to tiny, competent local models. Thanks o7
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@undefinedTruth@lemmy.zip 2026-09-15 19:23
Maybe this is good enough for small projects but if you deal with a large codebase the small context starts be becoming a problem. In my day job I frequently keep maxing out the 1M context of Opus and Fable when I am dealing with any mildly complex task. I can’t imagine how a fully local setup could even start being viable on my 16 GB GPU. And yes I know about RAM offloading and it is really damn slow, at least from my own tests.