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Show HN: One-click AI employee with its own cloud desktop

https://cloudbot-ai.com
1•fainir•1m ago•0 comments

Show HN: Poddley – Search podcasts by who's speaking

https://poddley.com
1•onesandofgrain•2m ago•0 comments

Same Surface, Different Weight

https://www.robpanico.com/articles/display/?entry_short=same-surface-different-weight
1•retrocog•4m ago•0 comments

The Rise of Spec Driven Development

https://www.dbreunig.com/2026/02/06/the-rise-of-spec-driven-development.html
2•Brajeshwar•8m ago•0 comments

The first good Raspberry Pi Laptop

https://www.jeffgeerling.com/blog/2026/the-first-good-raspberry-pi-laptop/
2•Brajeshwar•8m ago•0 comments

Seas to Rise Around the World – But Not in Greenland

https://e360.yale.edu/digest/greenland-sea-levels-fall
1•Brajeshwar•8m ago•0 comments

Will Future Generations Think We're Gross?

https://chillphysicsenjoyer.substack.com/p/will-future-generations-think-were
1•crescit_eundo•12m ago•0 comments

State Department will delete Xitter posts from before Trump returned to office

https://www.npr.org/2026/02/07/nx-s1-5704785/state-department-trump-posts-x
2•righthand•15m ago•0 comments

Show HN: Verifiable server roundtrip demo for a decision interruption system

https://github.com/veeduzyl-hue/decision-assistant-roundtrip-demo
1•veeduzyl•16m ago•0 comments

Impl Rust – Avro IDL Tool in Rust via Antlr

https://www.youtube.com/watch?v=vmKvw73V394
1•todsacerdoti•16m ago•0 comments

Stories from 25 Years of Software Development

https://susam.net/twenty-five-years-of-computing.html
2•vinhnx•17m ago•0 comments

minikeyvalue

https://github.com/commaai/minikeyvalue/tree/prod
3•tosh•21m ago•0 comments

Neomacs: GPU-accelerated Emacs with inline video, WebKit, and terminal via wgpu

https://github.com/eval-exec/neomacs
1•evalexec•26m ago•0 comments

Show HN: Moli P2P – An ephemeral, serverless image gallery (Rust and WebRTC)

https://moli-green.is/
2•ShinyaKoyano•30m ago•1 comments

How I grow my X presence?

https://www.reddit.com/r/GrowthHacking/s/UEc8pAl61b
2•m00dy•32m ago•0 comments

What's the cost of the most expensive Super Bowl ad slot?

https://ballparkguess.com/?id=5b98b1d3-5887-47b9-8a92-43be2ced674b
1•bkls•33m ago•0 comments

What if you just did a startup instead?

https://alexaraki.substack.com/p/what-if-you-just-did-a-startup
5•okaywriting•39m ago•0 comments

Hacking up your own shell completion (2020)

https://www.feltrac.co/environment/2020/01/18/build-your-own-shell-completion.html
2•todsacerdoti•42m ago•0 comments

Show HN: Gorse 0.5 – Open-source recommender system with visual workflow editor

https://github.com/gorse-io/gorse
1•zhenghaoz•42m ago•0 comments

GLM-OCR: Accurate × Fast × Comprehensive

https://github.com/zai-org/GLM-OCR
1•ms7892•43m ago•0 comments

Local Agent Bench: Test 11 small LLMs on tool-calling judgment, on CPU, no GPU

https://github.com/MikeVeerman/tool-calling-benchmark
1•MikeVeerman•44m ago•0 comments

Show HN: AboutMyProject – A public log for developer proof-of-work

https://aboutmyproject.com/
1•Raiplus•45m ago•0 comments

Expertise, AI and Work of Future [video]

https://www.youtube.com/watch?v=wsxWl9iT1XU
1•indiantinker•45m ago•0 comments

So Long to Cheap Books You Could Fit in Your Pocket

https://www.nytimes.com/2026/02/06/books/mass-market-paperback-books.html
4•pseudolus•45m ago•2 comments

PID Controller

https://en.wikipedia.org/wiki/Proportional%E2%80%93integral%E2%80%93derivative_controller
1•tosh•50m ago•0 comments

SpaceX Rocket Generates 100GW of Power, or 20% of US Electricity

https://twitter.com/AlecStapp/status/2019932764515234159
2•bkls•50m ago•0 comments

Kubernetes MCP Server

https://github.com/yindia/rootcause
1•yindia•51m ago•0 comments

I Built a Movie Recommendation Agent to Solve Movie Nights with My Wife

https://rokn.io/posts/building-movie-recommendation-agent
4•roknovosel•51m ago•0 comments

What were the first animals? The fierce sponge–jelly battle that just won't end

https://www.nature.com/articles/d41586-026-00238-z
2•beardyw•59m ago•0 comments

Sidestepping Evaluation Awareness and Anticipating Misalignment

https://alignment.openai.com/prod-evals/
1•taubek•1h ago•0 comments
Open in hackernews

Show HN: Run Qwen3-Next-80B on 8GB GPU at 1tok/2s throughput

https://github.com/Mega4alik/ollm
123•anuarsh•4mo ago

Comments

addandsubtract•4mo ago
Great work! Can this technique also be used to run image diffusion models on lower VRAM GPUs?
GTP•4mo ago
Not an expert in machine learning, but AFAIK diffusion models use a completely different architecture, therefore you can't use the same code to run optimized versions of both. But maybe the core ideas can be adapted to diffusion somehow.
anuarsh•4mo ago
Thanks! I don't have much experience with diffusion models, but technically any multi-layer model could benefit from loading weights one by one
cahaya•4mo ago
Nice. Seems like i cannot run this on my Apple silicon M chips right?
jasonjmcghee•4mo ago
Depends how much ram yours has. Get a 4bit quant and it'll fit in ~40-50GB depending on context window.

And it'll run at like 40t/s depending on which one you have

poorman•4mo ago
If you have 64 GB of RAM you should be able to run the 4-bit quantized mlx models, which are specifically for the Apple silicon M chips. https://huggingface.co/collections/mlx-community/qwen3-next-...
cahaya•4mo ago
Got 32GB so was hoping I could use ollm to offload it to my SSD. Slower but making it possible to run bigger models (in emergencies)
tripplyons•4mo ago
I have can host it on my M3 laptop somewhere around 30-40 tokens per second using mlx_lm's server command:

mlx_lm.server --model mlx-community/Qwen3-Next-80B-A3B-Instruct-4bit --trust-remote-code --port 4444

I'm not sure if there is support for Qwen3-Next in any releases yet, but when I set up the python environment I had to install mlx_lm from source.

mhuffman•4mo ago
This particular one may not work on M chips, but the model itself does. I just tested a different sized version of the same model in LM Studio on a Macbook Pro, 64GB M2 Max with 12 cores, just to see.

Prompt: Create a solar system simulation in a single self-contained HTML file.

qwen3-next-80b (MLX format, 44.86 GB), 4bit 42.56 tok/sec , 2523 tokens, 12.79s to first token

- note: looked like ass, simulation broken, didn't work at all.

Then as a comparison for a model with a similar size, I tried GLM.

GLM-4-32B-0414-8bit (MLX format, 36.66 GB), 9.31 tok/sec, 2936 tokens, 4.77s to first token

- note: looked fantastic for a first try, everything worked as expected.

Not a fair comparison 4bit vs 8bit but some data. The tok/sec on Mac is pretty good depending on the models you use.

anuarsh•4mo ago
I haven't tested on Apple machines yet, but gpt-oss and qwen3-next should work I assume. Llama3 versions use cuda specific loading logic for speed boost, so it won't work for sure
mendeza•4mo ago
what is the throughput for gpt-oss, 1 token every 2 seconds is really slow, but understandable because you are moving cache to disk
anuarsh•4mo ago
1tok/2s is the best I got on my PC, thanks to MoE architecture of qwen3-next-80B. gpt-oss-20B is slower because I load all single layer experts to GPU and unpack weights (4bit -> bf16) each time. While with qwen3-next I load only active experts (normally 150 out of 512). Probably I could do the same with gpt-oss.
aappleby•4mo ago
Why even bother with the GPU at that point? CPU would be just as fast if you're bottlenecked on SSD bandwidth.
anuarsh•4mo ago
CPU is much slower than GPU. You can actually use both by offloading some layers to CPU as o.offload_layers_to_cpu(layers_num=12). It is faster to load from RAM than from SSD.
anuarsh•4mo ago
There's one more exciting thing about Qwen3-next (except, efficient MoE architecture and fast linear attention) - MTP (Multi token prediction). It is the additional layer that allows generating more tokens without the need to go through the model again. I'm trying to make it work, but unsuccesfully yet. Maybe someone could help me with it - https://github.com/Mega4alik/ollm/blob/dev/src/ollm/qwen3_ne... (dev brunch). Take a look
ydlr•4mo ago
How dramatically does this shorten lifespan of SSDs?
anuarsh•4mo ago
Good question, need to research this one