alt Hacker NewsI may have genuinely new data for you.
Qwen3.5-35B-A3B is reported to perform slightly better than the model you mentioned.
It runs fine but non-optimal on a single 3090 with even 131072 tokens of context , and due to the hybrid attention architecture, the memory usage and compute scale rather less drastically than ctx^2. I've had friends with smaller cards still getting work out of it. Generation is at around 20 tokens/sec on that 3090 (without doing anything special yet) . You'll need enough DRAM to hold the bits of the model that don't fit. Nothing to write home about, but genuinely usable in a pinch or for tasks that don't need immediate interactivity.
It's the first local model that passes my personal kimbench usability benchmark at least. Just be aware that it is extremely verbose in thinking mode. Seems to be a qwen thing.
(edit: On rechecking my numbers; I now realize I can possibly optimize this a lot better)
With respect, this isn't "new data" it is an anecdote. And it kind of represents exactly the problem I was talking about above:
- Qwen is near Sonnet 4.5!
- How do I run that?
- [Starts talking about something inferior that isn't near Sonnet 4.5].
It is this strange bait/switch discussion that happens over and over. Least of all because Sonnet has a 200K context window, and most of these ancdotes aren't for anywhere near that context size.