2.5x faster Qwen3.6 NVFP4 Unsloth quants
Summary
Unsloth releases quantized Qwen3.6 models using NVFP4 format, achieving 2.5x faster inference speeds.
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@MiaAI_lab: Nvidia did it again! @NVIDIAAI's Qwen 3.6 27B NVFP4 is faster than Unsloth's Qwen 3.6 27B NVFP4 by a whopping ~41% on D…
Nvidia's optimized Qwen 3.6 27B NVFP4 model achieves 41% faster single-session inference and 23-25% faster concurrent inference on DGX Spark compared to Unsloth's version.
@MiaAI_lab: FYI the best Qwen 3.6 35b nvfp4 to run is the @NVIDIAAI nvfp4. Do not use unsloth nvfp4, it performs worse. https://hug…
NVIDIA's nvfp4 quantized version of Qwen 3.6 35B is recommended over the Unsloth variant, offering better performance. The model is available on HuggingFace for use in AI applications.
@TeksEdge: Unsloth released the fastest Qwen3.6-27B MTP GGUF I've tested. Time to upgrade. Compared to the previous GGUF, Q4/Q6 XL…
Unsloth has released an optimized GGUF version of the Qwen3.6-27B MTP model, achieving significantly faster inference speeds (up to 114 tok/s on an RTX 5090) compared to previous quantizations.
@witcheer: everyone says NVFP4 makes blackwell cards "faster." I benchmarked Qwen3.6-27B three ways on my 5090: >NVFP4 >plain Q4_K…
A benchmark of NVFP4 on an RTX 5090 with Qwen3.6-27B shows prefill speed gains of 32-42% over equal-bit Q4_K_M and 52-68% over Q6_K, but decode gains are modest (+9% vs Q4) as decode is memory-bandwidth bound. The quality loss compared to Q6 is minimal (-0.8 average), making NVFP4 a good choice for local inference.
@mr_r0b0t: Call the homies, new @UnslothAI NVFP4 just dropped
Unsloth AI releases new NVFP4 quantized Qwen3.6 models that run 2.5x faster on GPUs, with improved accuracy and tool calling capability.