Hugging Face
Search models, datasets, users...
Ctrl K
Models
Datasets
Spaces
Buckets
Docs
Enterprise
Pricing
Website
Tasks
HuggingChat
Collections
Languages
Organizations
Community
Blog
Posts
Daily Papers
Hardware
Learn
Discord
Forum
GitHub
Solutions
Team & Enterprise
Hugging Face PRO
Enterprise Support
Inference Providers
Inference Endpoints
Storage Buckets
Log In
Sign Up
151.6
TFLOPS
Daniel Lefevre
Oxidez
9
1
3
Follow
Quazim0t0's profile picture
ironbcc's profile picture
webbrain-one-809856's profile picture
3 followers
¡
8 following
http://localhost
Oxidez
AI & ML interests
None yet
Recent Activity
new
activity
about 3 hours ago
unsloth/Qwen3.8-27B-GGUF:
Extendable to 1000000, it says on the card.
replied
to
savoji
's
post
about 3 hours ago
A 284B-parameter DeepSeek-V4-Flash now runs on a 64 GB desktop with 0 GPUs: llama-modchip shrinks the checkpoint to 56.56 GiB (1.71 bpw) and decodes at 9.1 to 14.7 tok/s. The standard UD-IQ1_S build is 76.87 GiB, above the ~62.5 GiB usable on a 64 GB Linux box. The repo mixes precisions (routed experts mostly IQ1_S, MLA projections in a custom Fractal-64 type) and patches the CPU kernels. The model plus a 256K KV cache then sits at 57.61 to 58.9 GiB RSS with zero swap. The repo was created on 2026-10-29 and already has 744 stars and 470 points on Hacker News. đ The numbers ⢠Size: 56.56 GiB, 20.31 GiB smaller than UD-IQ1_S ⢠Prefill: 25.0 to 44.36 tok/s (+77%) on a 16-core Ryzen 9 9955HX ⢠Decode: 5.91 tok/s unpatched, 9.06 to 9.95 tok/s at Top-6, 11.5 to 14.7 tok/s with the n-gram drafter â ď¸ Caveats ⢠"Lossless" means bit-exact against the same re-quantized checkpoint. Versus UD-IQ1_S the author reports 0.9964 top-logit cosine similarity ⢠The 98.5/100 quality score comes from the author's own gate, and the headline speeds come from one machine ⢠The custom tensor type 40 is rejected by stock llama.cpp, Ollama and LM Studio đ ď¸ Try it ⢠Run scripts/check_cpu_readiness.py from the repo: it needs no model download ⢠Run ./modchip bench for speed, then ./modchip eval to check the quality claims yourself Repo: https://github.com/synchopate/llama-modchip HN thread: https://news.ycombinator.com/item?id=50411961 Would you accept a custom runtime for 9 to 15 tok/s from a 284B model on a 64 GB box? đ Read it elsewhere ⢠The deep dive on Medium: https://medium.com/p/e47ab3581f58 ⢠The long read on Substack: https://sajjadpakdamansavoji.substack.com/p/llama-modchip-runs-a-284b-deepseek ⢠The thread on X: https://x.com/saavoji/status/2119858773280141526 ⢠Every version on sajjadpsavoji.github.io: https://sajjadpsavoji.github.io/blog#llama-modchip
new
activity
9 days ago
XHToken/Spark-X2.6-4B-GGUF:
A lot better for Hermes than Qwen 3.5 9B
View all activity
Organizations
None yet
Oxidez
's activity
All
Models
Datasets
Spaces
Buckets
Papers
Collections
Community
Posts
Upvotes
Likes
Articles
upvoted
an
article
3 months ago
view article
Article
How Much Memory Does Your Agent Actually Need?
ibm-research
â˘
Aug 18
â˘
83