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longcat-video
LongCat-Video served by LocalAI's dedicated CUDA backend. Generates video from a text prompt or a start image. The SDPA attention path works without FlashAttention and is suitable for CUDA 13 ARM64 systems such as DGX Spark. This is a very large checkpoint (roughly 83 GB in Hugging Face storage) and requires Linux with an NVIDIA CUDA GPU plus substantial memory and disk.

Repository: localaiLicense: mit

longcat-video-avatar-1.5
LongCat-Video-Avatar-1.5 served by LocalAI's dedicated CUDA backend. Turns speech plus a prompt into an avatar video, optionally conditioning on a portrait, and continues across multiple segments for longer audio. Avatar generation also loads tokenizer, text encoder, and VAE components from LongCat-Video. Plan for very large downloads and substantial NVIDIA GPU or unified memory; CPU and macOS execution are unsupported.

Repository: localaiLicense: mit

llm-compiler-13b-imat
LLM Compiler is a state-of-the-art LLM that builds upon Code Llama with improved performance for code optimization and compiler reasoning. LLM Compiler is free for both research and commercial use. LLM Compiler is available in two flavors: LLM Compiler, the foundational models, pretrained on over 500B tokens of LLVM-IR, x86_84, ARM, and CUDA assembly codes and trained to predict the effect of LLVM optimizations; and LLM Compiler FTD, which is further fine-tuned to predict the best optimizations for code in LLVM assembly to reduce code size, and to disassemble assembly code to LLVM-IR.

Repository: localaiLicense: other

llm-compiler-13b-ftd
LLM Compiler is a state-of-the-art LLM that builds upon Code Llama with improved performance for code optimization and compiler reasoning. LLM Compiler is free for both research and commercial use. LLM Compiler is available in two flavors: LLM Compiler, the foundational models, pretrained on over 500B tokens of LLVM-IR, x86_84, ARM, and CUDA assembly codes and trained to predict the effect of LLVM optimizations; and LLM Compiler FTD, which is further fine-tuned to predict the best optimizations for code in LLVM assembly to reduce code size, and to disassemble assembly code to LLVM-IR.

Repository: localaiLicense: other

llm-compiler-7b-imat-GGUF
LLM Compiler is a state-of-the-art LLM that builds upon Code Llama with improved performance for code optimization and compiler reasoning. LLM Compiler is free for both research and commercial use. LLM Compiler is available in two flavors: LLM Compiler, the foundational models, pretrained on over 500B tokens of LLVM-IR, x86_84, ARM, and CUDA assembly codes and trained to predict the effect of LLVM optimizations; and LLM Compiler FTD, which is further fine-tuned to predict the best optimizations for code in LLVM assembly to reduce code size, and to disassemble assembly code to LLVM-IR.

Repository: localaiLicense: other

llm-compiler-7b-ftd-imat
LLM Compiler is a state-of-the-art LLM that builds upon Code Llama with improved performance for code optimization and compiler reasoning. LLM Compiler is free for both research and commercial use. LLM Compiler is available in two flavors: LLM Compiler, the foundational models, pretrained on over 500B tokens of LLVM-IR, x86_84, ARM, and CUDA assembly codes and trained to predict the effect of LLVM optimizations; and LLM Compiler FTD, which is further fine-tuned to predict the best optimizations for code in LLVM assembly to reduce code size, and to disassemble assembly code to LLVM-IR.

Repository: localaiLicense: other

deepseek-v4-flash-q2
DeepSeek V4 Flash (IQ2XXS GGUF, ~81 GB) - only loadable via the ds4 backend. Requires >=128 GB RAM. Metal (Darwin) or CUDA (Linux). See https://github.com/antirez/ds4 for details.

Repository: localai

deepseek-v4-flash-q2-q4
DeepSeek V4 Flash (mixed q2/q4 GGUF, ~91 GB) - only loadable via the ds4 backend. The last 6 expert layers are kept at Q4_K (the rest IQ2XXS), trading a little extra memory for higher quality than the pure-q2 build while still fitting in RAM on a 128 GB machine. imatrix-tuned. Metal (Darwin) or CUDA (Linux). See https://github.com/antirez/ds4 for details.

Repository: localai

deepseek-v4-flash-q2-mtp
DeepSeek V4 Flash (IQ2XXS GGUF, ~81 GB) paired with the optional MTP speculative-decoding weights (~3.5 GB) for a slight speedup. Only loadable via the ds4 backend; requires >=128 GB RAM. MTP helps only with greedy decoding (temperature 0), so the override pins temperature to 0. Metal (Darwin) or CUDA (Linux). See https://github.com/antirez/ds4 for details.

Repository: localai