Running 27B dense model on M5 128GB is ok, but one can do better.
On M5 128GB one can make use of the ram and use sparse MoE. For example, DeepSeek-V4-Flash will fit, served by DwarfStar (https://github.com/antirez/ds4). One will probably improve 2x the token/sec speed, given DS4F 13B activated params in the MoE are ~1/2 of the ~27B of the dense Qwen.
27B Of the Qwen fit even on a cheaper 24GB card, e.g. amd 7900xtx (<$1K?) or slightly dearer nvidia 3090 (with cuda). With ~900 GB/s bandwidth they will likely be ~50% faster than the M5 with 600 GB/s.
This is discussed in the article:
"My personal impression is that within these quantizations Qwen 3.6 27B is as good as (or maybe slightly better than) DwarfStar4. Though, I won’t be surprised if for longer context projects DS4 has an edge."
Used both. DeepSeek-4 Flash Q2 - last 6 layers Q4 quant with DwarfStar which just about fits in 128Gb is definitely superior IMO - my contexts tend to run typically 50-100k. Throughput tends to be about 12-13k tok/sec - just about acceptable.
Works beautifully on a 3090, very usable speed. Don't expect Opus 4.8-level performance, but there are some things you just need to keep local.
True - they are workhorses. Not super bright, but good enough for lots of everyday tasks. I've found sweet spot to be turning thinking off, as it adds small or no value, while increasing the token count and waiting time. Last 27B I used was https://huggingface.co/Jackrong/Qwopus3.6-27B-Coder-GGUF - specifically post-train adapted a bit to run with thinking off. I saw today the 35B-A3B MoE from the same HF acc is out, downloading that rn to try.
Please don't use that garbage. Just use the base Qwen models or Nex/Orinth, as those are the only properly post-trained finetunes. The Qwopus models are marketing.
Can you expand on why Qwopus is not recommended and what "Nex/Orinth" brings to the table?
"DeepSeek-V4-Flash will fit" At Q2, 2bit? Lobotomized to death.
Hobbled - but not to death, the few times I use it (usually on a plane). I tried 2bit of a 20% REAP reduced experts. :-O That's the biggest that fits on my own h/w (3yrs old M2 Max 96gb). It's coherent, it does work, doesn't fall apart on casual use. IDK if better than dense 27b. Think 27b was slower on the same h/w. DS4F has got 1M context window. Nowadays with weeks long run hermes sessions, I get to 300k-400k context depths easily. The speed decline profile of DS4F with context depth increase is superior to any other model I try. (I try them all - love this stuff) Only previous model coming close on that is nemotron-cascade-2 (only 30b-a3b) - that also has 1M context window.