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Ornith-1.5-35B-A3B-NVFP4

ornith-ai · Kit

Writes code and handles terminal agent tasks, a mixture-of-experts model using about 3B parameters per token, packaged as an NVFP4 copy. For developers hosting…

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Serves Qwen3.6 35B A3B in a fast NVFP4 build by Unsloth for vLLM on NVIDIA GPUs. The card says it has 1.79x the throughput of other NVFP4 builds and fits a 32…

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Serves the 122B Ornith 1.5 model through vLLM with DFlash2 speculative decoding, using an unquantized output head. Made for RTX Spark laptops with 128 GB of me…

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A pre-quantized NVFP4 copy of Qwen3.8-27B that reads text, images and video and answers in text, served with SGLang on NVIDIA Blackwell GPUs. Suits developers…

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Qwen3.8-27B-QUASAR-NVFP4

QUASAR-QAT · Kit

Runs Qwen3.8-27B in 4-bit NVFP4 at 19.7 GB, trained with the QUASAR method to stay close to the full BF16 model. For people serving it with vLLM on an NVIDIA B…

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Laguna-XS.2-jlens

PrimeIntellect · Kit

Holds Jacobian lens files that compare a bf16 and an NVFP4 copy of Laguna-XS-2.1, plus a version comparison with Laguna-XS.2. Research files for people who stu…

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Reads text and images and writes text, as a smaller NVFP4 copy of DeepSeek-V4.1-Flash made by NVIDIA. For developers deploying agents, chatbots and retrieval s…

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Serves Qwen3.8-27B in NVFP4 on one RTX 5090 with vLLM, with a checksum-verified download, FP8 KV cache, tool calls and reasoning support. For developers self-h…

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Speeds up Qwen3.8-27B NVFP4 decoding about 3.9 times on a DGX Spark, using the same weights and a tuned speculative-decoding setup. For teams serving it with v…

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Runs Qwen3.8-27B as a smaller MXFP4-quantized copy made with AMD Quark and AWQ, served through vLLM. Made for developers who want a compressed 27B vision-langu…

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MiMo-V2.6-Flash-RL-NVFP4

primitive-ai · Kit

Serves Xiaomi's MiMo-V2.6-Flash-RL as an NVFP4 build for Blackwell GPUs, with the release's exact expert values and more throughput on two 96 GB cards. For peo…

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Occamy-1.0

Accio-Lab · Kit

An open 35B image and text model from Accio-Lab, based on Qwen3.6-35B-A3B, in BF16, GGUF, FP8, NVFP4 and MLX formats. For teams that serve a large model.

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Beam-1.0-501B-A23B-NVFP4

reflection · Kit

Reads and writes text with a 1M-token context, built for coding, agent tool use and math reasoning, as a 501B-parameter mixture-of-experts model in NVFP4 form.…

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Flint NVFP4 GGUF

RecursiveSI · Kit

A 4-bit NVFP4 copy of the Recursive Flint text model as one GGUF file, built for NVIDIA GPUs through llama.cpp. For developers running a large local model with…

New

Hydrogen-1.0 NVFP4

deep-principle · Kit

A 4-bit NVFP4 build of Hydrogen-1.0, a 381B science and research assistant model from Deep Principle, based on GLM-5.3. It needs a multi-GPU NVIDIA Blackwell s…

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Hydrogen-1.0-MXFP4

deep-principle · Kit

An MXFP4 quantized copy of Deep Principle's 384B Hydrogen-1.0 science assistant, for AMD Instinct hardware. For labs that want a text model for scientific ques…

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A 17.1 GB mixed-precision GGUF of Qwen3.8-27B that keeps its multi-token prediction layer, tuned for 256K context with vision on a 24 GB GPU. For people who ru…

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Inkling-Small-NVFP4

thinkingmachines · Kit

The NVFP4 copy of Inkling-Small, a multimodal mixture-of-experts model that takes text, images and audio and writes text. For developers building agents, codin…

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Ornith-1.5-122B-NVFP4

ornith-ai · Kit

Gives you an NVFP4 quantized copy of Ornith-1.5-122B, a 122B mixture-of-experts text model meant for single-GPU use and strong in coding tests. For developers…

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A 27B reasoning model tuned to answer plainly instead of hedging, quantized to MXFP4 so vLLM can serve it on a single 32 GB GPU, for developers who run local r…

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