BigMoeOnEdge

Run MoE models bigger than your RAM. Frontier-size MoE on a 12 GB phone, CPU only, lossless, on stock llama.cpp (by Helldez)
Review Android CPP edge-ai gguf gpt-oss Inference llama-cpp LLM mixture-of-experts moe on-device-ai qwen gemma
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BigMoeOnEdge Alternatives

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Helldez
BigMoeOnEdge

  1. QuantumLeap---Llama.cpp-TurboQuant

    1 BigMoeOnEdge VS QuantumLeap---Llama.cpp-TurboQuant

    🚀 Run any LLM on any hardware. 130% faster MoE inference with ExpertFlow + TurboQuant KV compression. Ollama-compatible API. Built on llama.cpp.

  2. Kargo

    Stop Scripting Promotions. Start Shipping with Kargo. Kargo automates promotion across dev, staging, and prod with approval gates and verification. Open source, built by the team behind Argo CD. Download now.

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  3. xyntetik-runner

    1 BigMoeOnEdge VS xyntetik-runner

    Single-binary GGUF model runtime in C — CPU/CUDA/Metal, OpenAI-compatible. Serves, scores, and trains LoRA directly through the quantized weights it deploys, with byte-reproducible adapters. Tool calls survive the token limit; sparse MoE and schema-constrained decoding included.

  4. fitllm-engine

    1 BigMoeOnEdge VS fitllm-engine

    Accurate LLM memory & speed calculator — models sliding-window/linear/MoE attention where naive VRAM/RAM calculators are 4–11× off. Apple Silicon + NVIDIA RTX · GGUF · one MIT file. Powers fitllm.run.

  5. TensorSharp

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    A C# inference engine for running large language models (LLMs) locally using GGUF model files. TensorSharp provides a console application, a web-based chatbot interface, and Ollama/OpenAI-compatible HTTP APIs for programmatic access. It supports Windows/MacOS/Linux with full GPU capability

  6. runanywhere-sdks

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    Production ready toolkit to run AI locally

  7. Qwen-3.5-16G-Vram-Local

    2 BigMoeOnEdge VS Qwen-3.5-16G-Vram-Local

    Discontinued Configs, launchers, benchmarks, and tooling for running Qwen3.5 GGUF models locally with llama.cpp on a 16GB NVIDIA GPU [GET https://api.github.com/repos/willbnu/Qwen-3.5-16G-Vram-Local: 404 - Not Found // See: https://docs.github.com/rest]

  8. mbolt

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    Profile-guided layout optimization for llama.cpp GGUF MoE models — BOLT/PGO for LLM weights. Trace expert routing, rewrite the file so co-activated experts sit together, prefetch as merged reads.

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Helldez/BigMoeOnEdge is an open source project licensed under Apache License 2.0 which is an OSI approved license.

The primary programming language of BigMoeOnEdge is C++.


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