ByteShape

ByteShape is a Startup Sponsor at #PyTorchCon 2026! Come visit us at Booth #52 for fun interactive demos, conversations about efficient AI, and a special surprise! 📸 Take a photo and bring home a printed keepsake! 📍 San Jose Convention Center 📅 October 20–21 See you there!

1/3 We updated our Qwen3.8 benchmarks to include Prism-LM’s new Bonsai 2 QAT models. These are our results, not the benchmark numbers reported by Prism. We ran Bonsai 2 using Prism’s runtime, while keeping the rest of the setup consistent with our other Qwen3.8 evaluations.

We released ShapeLearn-Lite days after Qwen 3.8 27B, and it already delivered some of the best quality/speed trade-offs we tested. Now full ShapeLearn is even better: 99.63% of BF16’s aggregate benchmark score at just 3.84 bpw. Models & results: byteshape.com/blogs/Qwen3.8-…

We recently released two optimized image-generation models: Qwen-Image-2512 and Krea-2-Turbo. We pushed both into the ~3 bpw range while preserving their ability to generate high-quality images. Each model comes in two flavors: (1/2)

We released Qwen 3.6 35B A3B GGUF quants in both NTP and MTP. The benchmark results made one thing clear: size, speed, and quality do not move in a straight line. GPU-5 was hard to beat. If it fits, try it first. Blog: byteshape.com/blogs/Qwen3.6-…

We recently released our Qwen 3.5 35B A3B quants. If your setup can run GPU-7, you should try it. If not, we’ve got options across all hardware. Pi → 5090. Blog: byteshape.com/blogs/Qwen3.5-…

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-…

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=jRQaur0L…

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…