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View details ↗DISCOVER & COMPARE
Explore AI models 12
Krea-2-Turbo-GGUF
byteshapeThis is a GGUF-quantized version of the **Krea-2-Turbo** diffusion transformer, produced with **ByteShape's ShapeLearn**, which learns the optimal datatype per tensor to maintain high quality even at very low bitlengths. Five sizes are available, from **14.31 GB (8.93 bpw)** down to **6.26 GB (3.91 bpw)**. All variants generate high-quality images. These files run in **ComfyUI** via the ComfyUI-GGUF extension.
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View details ↗Llama-3.1-8B-Instruct-GGUF
byteshape基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen-Image-2512-GGUF
byteshapeThis is a GGUF-quantized version of the **Qwen-Image-2512** diffusion transformer, produced with **ByteShape's ShapeLearn**, which learns the optimal datatype per tensor to maintain high quality even at very low bitlengths. Six sizes are available, from **16.87 GB (6.61 bpw)** down to **7.77 GB (3.04 bpw)**. All variants generate high-quality images. > Looking for more speed? We also publish a **vLLM-Omni** build of the same model with optimized Humming kernels, roughly **2-3x faster** per step. See byteshape/Qwen-Image-2512-Humming.
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View details ↗Qwen3-30B-A3B-Instruct-2507-GGUF
byteshape基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3-4B-Instruct-2507-GGUF
byteshape基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.5-35B-A3B-GGUF
byteshape基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.5-9B-GGUF
byteshape基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.6-35B-A3B-GGUF
byteshapeThis is a GGUF-quantized version of Qwen3.6-35B-A3B produced with **ByteShape's ShapeLearn**, which learns the optimal datatype per tensor to maintain high quality even at very low bitlengths. To learn more about ShapeLearn and to see detailed benchmarks across GPUs, CPUs, and even the Raspberry Pi, please visit our blog. Pick a model from the tables below and click **Get llama.cpp command** to get a ready-to-run command with all the correct sampling parameters for this model.
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View details ↗Qwen3.6-35B-A3B-MTP-GGUF
byteshapeThis is a GGUF-quantized version of Qwen3.6-35B-A3B with **Multi-Token Prediction (MTP)** support, produced with **ByteShape's ShapeLearn**, which learns the optimal datatype per tensor to maintain high quality even at very low bitlengths. MTP allows the model to predict multiple tokens per forward pass, accelerating decoding on GPUs by accepting speculative tokens that match what the base model would have produced. These models are optimized for **GPU-only** inference. Pick a model from the table below and click **Get llama.cpp command** to get a ready-to-run command with all the correct sampling parameters for this model.
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View details ↗Qwen3.8-27B-GGUF
byteshapeThis is a GGUF-quantized version of Qwen3.8-27B produced with **ByteShape's ShapeLearn**, which learns the optimal datatype per tensor to maintain high quality even at very low bitlengths. This release replaces our earlier ShapeLearn-Lite quantizations of Qwen3.8-27B. Every model here has been through our **full multi-benchmark evaluation suite**, covering math, coding, general knowledge, instruction following and agentic tool use in both thinking and instruct modes, scored against the BF16 baseline. To learn more about ShapeLearn and to see detailed benchmarks across GPUs, please visit our blog.
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View details ↗Qwen3-Coder-30B-A3B-Instruct-GGUF
byteshape基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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