Discover and install AI models from our curated collection
Repository: localaiLicense: qwen-community-1.0
Qwen3.8-Flash-Next, a 125B-parameter hybrid mixture-of-experts model, in Unsloth's Dynamic quantization (UD-Q6_K_XL, 6-bit) (about 170 GB to download). It reads images through the vision projector published for the original model, and the Strata backend parses its reasoning and tool calls. Needs about 118 GB of RAM to keep every expert in memory; with less, the mapped experts are read from the SSD while it answers, which works and is much slower. Keep the files on an SSD. Needs a GPU the strata backend supports; NVIDIA with 12 GB of VRAM or more is the class Strata tests. Runs only on the experimental strata backend. On the first load the strata backend builds the Strata pack from the GGUF files (a few minutes, a few GB of extra disk); a finished pack is never rebuilt. The experts are read from the GGUF files in place (mapped); add --resident-experts to engine_args to copy them into RAM when there is room. Licensed under the Qwen Community License 1.0 (inherited from Qwen/Qwen3.8-Flash-Next): free use, but a Model as a Service or AI Work Assistant business needs a licence from Qwen. Read the LICENSE file in the repository first. The GGUF files are the Unsloth quantization; the vision projector is ISTA-DASLab's file for the original model; Strata is by Niko1221. The MTP draft layer is not configured here.
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Repository: localaiLicense: apache-2.0
Qwen3.6-35B-A3B, a 35B-parameter mixture-of-experts model with 3B active parameters, in Unsloth's 6-bit (Unsloth Dynamic), closer to the full model GGUF with the MTP layer (about 34 GB to download). It reads images through Unsloth's vision projector, and the Strata backend parses its reasoning and tool calls. Needs an NVIDIA or AMD GPU (the Intel Arc and Apple builds of Strata do not run this model) and about 44 GB of RAM: the engine keeps every expert it can in VRAM and computes the rest on the CPU. Runs only on the experimental strata backend. On the first load the strata backend exports the tokenizer and chat template from the GGUF file (seconds); the engine reads the GGUF as it is. The MTP draft layer inside the file is used for speculative decoding. Licensed under the Apache License 2.0 (Qwen/Qwen3.6-35B-A3B). The GGUF files are the Unsloth quantization; Strata is by Niko1221.
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Repository: localai
Kimodo SOMA RP v1.1 text-to-motion on CPU or Vulkan, with F32 motion weights and the shared monolithic Q6_K Llama-3/LLM2Vec text encoder. Exports an animated skeleton GLB without a mesh or skin. Motion and text weights retain their respective NVIDIA Open Model License and Llama 3 terms.
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Repository: localai
Kimodo SOMA SEED v1.1 text-to-motion on CPU or Vulkan, with F32 motion weights and the shared monolithic Q6_K Llama-3/LLM2Vec text encoder. Exports an animated skeleton GLB without a mesh or skin. Motion and text weights retain their respective NVIDIA Open Model License and Llama 3 terms.
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Repository: localai
Kimodo G1 RP v1 text-to-motion on CPU or Vulkan, with F32 motion weights and the shared monolithic Q6_K Llama-3/LLM2Vec text encoder. Exports an animated skeleton GLB without a mesh or skin. Motion and text weights retain their respective NVIDIA Open Model License and Llama 3 terms.
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Repository: localai
Kimodo G1 SEED v1 text-to-motion on CPU or Vulkan, with F32 motion weights and the shared monolithic Q6_K Llama-3/LLM2Vec text encoder. Exports an animated skeleton GLB without a mesh or skin. Motion and text weights retain their respective NVIDIA Open Model License and Llama 3 terms.
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