Showing 4 open source projects for "embedded compact browser"

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  • 1
    FLUX.2-klein-4B

    FLUX.2-klein-4B

    Flux 2 image generation model pure C inference

    FLUX.2-klein-4B is a compact, high-performance C library implementation of the Flux optimization algorithm — an iterative approach for solving large-scale optimization problems common in scientific computing, machine learning, and numerical simulation. Written with a strong emphasis on simplicity, correctness, and performance, it abstracts the core logic of flux-based optimization into a minimal C API that can be embedded in broader applications without pulling in heavy dependencies. ...
    Downloads: 9 This Week
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  • 2
    MiniMax-M2

    MiniMax-M2

    MiniMax-M2, a model built for Max coding & agentic workflows

    MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real...
    Downloads: 1 This Week
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  • 3
    Ministral 3 8B Instruct 2512

    Ministral 3 8B Instruct 2512

    Compact 8B multimodal instruct model optimized for edge deployment

    Ministral 3 8B Instruct 2512 is a balanced, efficient model in the Ministral 3 family, offering strong multimodal capabilities within a compact footprint. It combines an 8.4B-parameter language model with a 0.4B vision encoder, enabling both text reasoning and image understanding. This FP8 instruct-fine-tuned variant is optimized for chat, instruction following, and structured outputs, making it ideal for daily assistant tasks and lightweight agentic workflows. Designed for edge deployment,...
    Downloads: 0 This Week
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  • 4
    Ministral 3 3B Instruct 2512

    Ministral 3 3B Instruct 2512

    Ultra-efficient 3B multimodal instruct model built for edge deployment

    ...It includes a 3.4B-parameter language model paired with a 0.4B vision encoder, enabling it to understand both text and visual inputs. As an FP8 instruct-fine-tuned model, it is optimized for chat, instruction following, and compact agentic tasks while maintaining strong adherence to system prompts. Despite its small size, it delivers efficient real-time performance and can run locally on a single 8GB GPU, with further memory reductions through quantization. It supports dozens of languages across major global regions, making it well-suited for multilingual and embedded applications. ...
    Downloads: 0 This Week
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