ByteShape

Run your own local AI coding agent We just published a beginner guide for using @opencode with local models (@lmstudio, llama.cpp, @ollama). Mac, Linux, WSL2, full setup + API + config. byteshape.com/blogs/tutorial… From “I have a model” → “I have a working coding agent”

GPUs are consistent. CPUs are not. With our ByteShape Qwen 3.5 9B quants, the same models perform well across GPUs, but CPUs each have their own “favorites”. No one-size-fits-all. Optimize for your hardware. byteshape.com/blogs/Qwen3.5-…

ByteShape was quietly launched just before the year end. Two weeks ago, we announced our investment in the company. Since its launch, and with minimal fanfare on purpose, @ByteShape cumulative downloads have easily blown past 100,000. No small feat for a new startup!

Announcing @twosmallfishvc's investment in @ByteShape. In short, ByteShape is delivering step-function gains in AI efficiency, including up to 7x faster training, up to 10x faster inference, plus up to 40% compression to reduce model size.

@atarl666028 @Alibaba_Qwen 👀

@Alibaba_Qwen @ByteShape When will Shape Learn Quantized be released?

🚀 Introducing the Qwen 3.5 Medium Model Series Qwen3.5-Flash · Qwen3.5-35B-A3B · Qwen3.5-122B-A10B · Qwen3.5-27B ✨ More intelligence, less compute. • Qwen3.5-35B-A3B now surpasses Qwen3-235B-A22B-2507 and Qwen3-VL-235B-A22B — a reminder that better architecture, data quality, and RL can move intelligence forward, not just bigger parameter counts. • Qwen3.5-122B-A10B and 27B continue narrowing the gap between medium-sized and frontier models — especially in more complex agent scenarios. • Qwen3.5-Flash is the hosted production version aligned with 35B-A3B, featuring: – 1M context length by default – Official built-in tools 🔗 Hugging Face: huggingface.co/collections/Qw… 🔗 ModelScope: modelscope.cn/collections/Qw… 🔗 Qwen3.5-Flash API: modelstudio.console.alibabacloud.com/ap-southeast-1… Try in Qwen Chat 👇 Flash: chat.qwen.ai/?models=qwen3.… 27B: chat.qwen.ai/?models=qwen3.… 35B-A3B: chat.qwen.ai/?models=qwen3.… 122B-A10B: chat.qwen.ai/?models=qwen3.… Would love to hear what you build with it.

Excellent quantisation on Devstral Small 2

We released ShapeLearn-optimized GGUFs for: • Devstral Small 2 24B, tuned for RTX 40/50 GPUs • Qwen3 Coder 30B, runs everywhere, yes even the Pi Maximum quality. Fastest TPS. Minimal compromise. GGUFs + interactive plots are live: byteshape.com/blogs/Devstral…

Edge computing is getting spicy! Shoutout to @geerlingguy for showcasing our model. Love seeing what the community is building and how hard it’s being pushed. Clip: youtube.com/watch?v=jRQaur…

Raspberry Pi has a new AI HAT. This time with built-in 8 GB of RAM, so you can run machine vision + LLM inference all without touching the Pi's CPU. It's $130 and a little bit of a niche item. Find out why in my video: youtube.com/watch?v=jRQaur…

A 30B Qwen Model Walks into a Raspberry Pi and Runs in Real Time #HackerNews byteshape.com/blogs/Qwen3-30…

New ShapeLearn GGUFs! Qwen3-30B-A3B-Instruct-2507, tuned for real hardware, not just “fewer bits.” We treat memory as a budget: fit first, then optimize TPS vs quality. And yes, a 30B runs on a Raspberry Pi 5. byteshape.com/blogs/Qwen3-30…

What if AI models could learn their own compression? ByteShape's tech learns the best datatype per tensor. On Qwen3-4B and Llama 3.1-8B: 2.5x–3.5x better accuracy vs GGUF, same quality faster or higher quality same speed, from RTX 5090 to Raspberry Pi 5. byteshape.com/blogs/Qwen3-4B…