MXFP4
PulseAugur coverage of MXFP4 — every cluster mentioning MXFP4 across labs, papers, and developer communities, ranked by signal.
8 day(s) with sentiment data
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Xiaomi releases trillion-parameter MiMo LLM family with open weights
Xiaomi has released its MiMo family of large language models, featuring a trillion parameters in its latest MiMo-V2.5-Pro version. These models are notable for their open-weight status under the MIT license and their na…
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ESTS details WMT26 model compression using GPT-OSS-20B and GPT-5.1
Researchers from ESTS have detailed their submissions to the WMT26 Model Compression Shared Task, focusing on English-to-Simplified Chinese and English-to-Egyptian Arabic translation. Their approach involved pruning exp…
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NVIDIA releases DeepSeek-V4-Pro-0813 with DSpark-Draft-Head
NVIDIA has released DeepSeek-V4-Pro-0813 as an NVFP4 checkpoint, integrating a DSpark-Draft-Head. This release features MXFP4 experts from the draft module losslessly mapped to NVFP4, ensuring consistent quantization be…
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New EFQ-Softmax method optimizes low-bit quantization for Transformers
Researchers have developed EFQ-Softmax, a novel method for low-bit quantization in Transformer models that bypasses the traditional exponential calculation for softmax. This approach directly maps shifted attention scor…
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Scale-QLoRA enables lossless merging of LLM adapters in 4-bit models
A new research paper introduces Scale-QLoRA, a method for merging LoRA adapters into native 4-bit quantized LLMs without accuracy loss. Traditional merging methods can degrade performance, but Scale-QLoRA preserves the …
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Older LLM quantization format outperforms newer one on Apple M2
A recent test comparing two local Large Language Models (LLMs) on an Apple M2 laptop revealed that the older Q4_K_M quantization format outperformed the newer MXFP4 format. The Q4_K_M format achieved 4.7 tokens/second, …
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New FlashAttention-4 method boosts FP4 performance on Blackwell hardware
Researchers have developed a new method called Direct-P to optimize FlashAttention-4 for Blackwell's 4-bit floating-point (FP4) tensor cores, addressing performance bottlenecks caused by softmax conversion and on-chip d…
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New research tackles FP4 pretraining stability with 2D block scaling
A new research paper introduces a method for stable FP4 pretraining by addressing a critical issue with transpose-invariant 2D block scaling. Previous methods using 1D scaling groups suffered from scale inconsistency wh…
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Qwen3.8 27B model hits 280 tok/s with new MXFP4 optimization
A developer has achieved significant performance gains with the Qwen3.8 27B model by implementing MXFP4 kernels on dual R9700 GPUs. This optimization, which utilizes W4A8 quantization, has reportedly surpassed FP8 perfo…
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New LLM compression techniques yield smaller, more accurate models
Researchers have developed new methods for compressing large language models (LLMs) while preserving or even improving their performance. One approach, Quantization-Aware Healing (QAH), distills a compressed, 4-bit mode…
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Kimi K3's 2.8T parameters highlight LLM deployment as a systems engineering challenge
The Kimi K3 model, with 2.8 trillion total parameters and approximately 104 billion active parameters per token, presents significant deployment challenges beyond its sheer size. Its architecture incorporates a mixture-…
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DeepSeek V4 Flash quantized for DwarfStar inference engine
A user has created and shared quantized versions of the DeepSeek V4 Flash model, specifically tailored for the DwarfStar (DS4) inference engine. These GGUF files aim to provide faster performance than standard llama.cpp…
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Moonshot AI releases Kimi K3, a 2.8T parameter open-weight MoE model
Moonshot AI has released Kimi K3, a 2.8 trillion parameter open-weight Mixture of Experts (MoE) model. This model, featuring Kimi Delta Attention and other architectural innovations, offers improved scaling efficiency a…
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Unsloth releases Kimi K3 GGUF models, including large MXFP4 version
Unsloth has started releasing GGUF model files for Kimi K3. The initial releases include the MXFP4 model, which is 1.5 TB in size, and the mmproj component. These files are available for users to download and utilize.
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MXAttention framework optimizes MXFP4 attention for video generation
Researchers have developed MXAttention, a novel data-free post-training quantization framework designed to optimize MXFP4 attention in diffusion-based video generation models. This framework addresses numerical issues l…
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Moonshot AI releases open-weight Kimi K3 model, challenging Fable 5 and GPT-5.6 Sol
Moonshot AI has released an open-weight version of its Kimi K3 model, utilizing the MXFP4 format and capable of processing 1.56TB of data. This release positions Kimi K3 as a competitor to advanced models like Fable 5 a…
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Moonshot releases Kimi K3, a 2.8T parameter multimodal model with 1M context
Moonshot has released Kimi K3, a new 2.8 trillion parameter multimodal model featuring a 1 million token context window and native vision capabilities. The model demonstrates impressive speed, achieving 460 tokens per s…
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Kimi K3's massive scale demands intensive networking despite optimizations · 8 sources tracked
SemiAnalysis reports that the Kimi K3 model, with its 2.8 trillion parameters, requires significant network bandwidth despite optimizations like Kimi Delta Linear Attention (KDA). The model's architecture necessitates t…
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DynamiQ framework accelerates LLM training with optimized gradient synchronization
Researchers have developed DynamiQ, a new framework designed to accelerate the training of large language models by optimizing gradient synchronization. This method addresses the network bottleneck issue in large-scale …
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GLM5.2 deployed on AMD MI355X for cheaper inference · 5 sources tracked
Wafer.ai has successfully deployed GLM5.2 on AMD MI355X hardware, achieving a throughput of 2626 tokens/second/node and 213 tokens/second for single-stream inference. This deployment offers a cost advantage, with MI355X…