@github.awesome: Running a 400-billion parameter model locally usually means a server rack. Someone just did it on a MacBook Pro with 48GB of RAM. The engine is called flash-moe. Instead of loading a 209GB model into memory, it streams weights from SSD to GPU on demand, pulling around five tokens per second on consumer hardware. the whole engine was built in 24 hours, with Claude Code autonomously running experiments based on an Apple research paper. #github #opensource

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Sunday 22 March 2026 03:42:03 GMT
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nforestglade
NForestGlade :
5 tokens per second - you can guess the next letter yourself
2026-03-22 13:26:30
83
smithing_gold
Krispy 💡 :
5 tokens per second is crawling.😂
2026-03-22 10:55:06
69
helpgood.tech
Cody :
for anyone watching at home this isn't new technology, this is standard practice since about '95-'98 and the introduction of memory swapping, page file in Windows land. you have your hardware RAM and a service that watches it for memory that is not being accessed, if there's been any pressure for RAM then the low accessed areas are moved to the swap space on your disk, in this case modern hardware uses SSD. relatively fast in human time. if you craft a AI to use both the idea would be that you use roughly 40 gigs of that hardware RAM actively while swapping the rest of the 200 gig model from your disc just as it's needed, is it slower than having 200 gigs of RAM, yes. is it relatively performative considering what you're doing, also yes, I'd say not too bad. probably wouldn't be too snappy, but it would be very intelligent considering speed you're seeing in the hardware it's running on. thanks for coming to my Ted talk
2026-03-22 05:00:49
24
justnico16
Nico :
Does it use TurboQuant? There’s been some amazing optimizations coming out lately
2026-04-09 02:59:20
0
anythingunused
Florin Moldoveanu :
4 tokens per second, 4 bit quantized, 209 GB... yeah that's not running the model, that is slowly killing the SSD.
2026-03-22 19:04:27
15
carlos.ponto
Carlos. :
sloooowwww
2026-03-22 04:21:00
19
wesbosley
Wes Bosley :
llama.cpp already does this with unified mem
2026-03-22 09:25:52
0
kokrramolles
An avocado :
5 tokens për second.
2026-03-22 10:56:29
0
sycicnok
sycicnok :
claude is the developer. that's the important part.
2026-03-22 07:16:22
2
ziobudda
Michel M. | AI CODER :
+3.6K $ machine for 5 tokens/second ??? Really ???
2026-03-24 09:21:50
0
hojit84726
hojit84726 :
I'm guessing having multiple fast SSDs in raid 0 would provide better tokens ?
2026-03-22 08:45:24
0
sveinbjornp
Sveinbjörn :
5 tokens a second? Is that useable?
2026-03-22 07:28:14
0
adambellstedt370
Adam :
https://github.com/danveloper/flash-moe
2026-03-22 09:34:52
0
getklarted
getklarted :
That is so sick
2026-03-24 10:43:36
0
mr_s1n1ster4
Mr_S1n1ster :
Not even worth it for five tokens it’s a joke
2026-03-23 18:09:27
1
hetox5026
Ad :
Excellent for sharing 👍🙏
2026-03-22 11:40:58
0
gohome.gi
Liu :
crazy, just by claude code...
2026-03-22 06:23:00
0
lucaslaram
Lucas Marotta :
Maybe use something like direct storage
2026-03-22 06:38:59
1
drunkondata
DROP TABLE user_names; :
how is this different from AirLLM?
2026-04-22 10:34:47
0
checkmatethesystem
WhatIsDeadMayNeverDIE. :
copying thing's i see 😂
2026-03-25 23:33:06
0
matetod0
matetod :
Another thing to say is that SSD has that Mac, a 17GB/s beast, I'm not saying it doesn't exist in the commercial sector though, it's not exactly an easy thing and it's supported by all PCs.
2026-03-22 08:21:12
0
israeldavid3171
ectron :
thats my question why store weights in memory as a storage point .. the layers aint even taking the whole memory ... we need a better way to store weights .. thr computing layers should inly be in memory
2026-03-22 07:49:16
0
user242273687114
user242273687114 :
😁😁😁
2026-03-28 01:22:01
0
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