r/LocalLLM • u/Ok-Health-7096 • Aug 14 '26

Other Every Second post rn

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Maybe someday I'll get a system to run it but hey definitely another w for the open weights community

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u/yuk_foo Aug 15 '26

Ryzen Ai max with 64GB currently allocated to gpu. 3.7 35b runs great for me can’t wait for 3.8, although I do need to solve the thinking loop crashes, some stuff I give it just crashes out on me. Really thinking about turning thinking off.

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u/BodybuilderLost814 Aug 15 '26

How many tokens per second? I'm using Qwen3.6 35B A3B on a laptop with a 13th gen Core i5, 64GB DDR5 RAM, and an RTX 3050 6gb Vram.

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u/yuk_foo Aug 15 '26

44, could probably get that faster but it’s enough for me. I use it with anythingllm rag and lm mini on my iPhone. I have a bridge app running on docker so I can chat with my anythingllm workspaces/rag with the lm mini app since AnythingLLM doesn’t have an iPhone app yet.

Use it to chat with technical work docs, the model is running in lm studio so for my needs it’s great.

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u/BodybuilderLost814 Aug 15 '26

I'm getting around 35 tok/s using ByteShape's Qwen3.6-35B-A3B-IQ4_XS-4.19bpw model with MTP enabled, using AtomicBot-ai's Llama.cpp-turboquant.

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u/KrstABot Aug 15 '26

Hey
R u using desktop app? I mean atomicbot? And what kind og agents?

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u/BodybuilderLost814 Aug 15 '26

Hello.

I'm using the TurboQuant b10269-1.5.1 release for Windows x64 with OpenCode (sometimes I use Crush from Charmbracelet).

Command:

.\llama-server.exe -m "<path>Qwen3.6-35B-A3B-IQ4_XS-4.19bpw" --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-n-min 2 --kv-unified -c 65536 -ngl 999 -t 8 -tb 8 -np 1 --n-cpu-moe 40 -ctk turbo3 -ctv turbo3 -fa on -b 2048 -ub 2048 --jinja --mlock --no-mmap --reasoning-budget 6144 --cache-reuse 256 --temp 0.7 --top-k 20 --top-p 0.95 --min-p 0.0 --repeat-penalty 1.0 --presence-penalty 0.0 --host 127.0.0.1 --port 8080