<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s3i83m/fully_local_voice_ai_on_iphone/"> <img alt="Fully local voice AI on iPhone"
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sarlb8/gemma_4_running_on_raspberry_pi5/"> <img alt="Gemma 4 running on Raspberry Pi5"
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sffz0e/gemmatunermultimodal_finetune_gemma_4_with_audio/"> <img alt="gemma-tuner-multimodal: Fine-tune
<!-- SC_OFF --><div class="md"><p><a href="https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF">https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF</a></p> <p><a
<!-- SC_OFF --><div class="md"><p>Fully on-device at 4bit with 256 experts.</p> <p>It uses SSD streaming to the GPU of the experts in MoE models.</p> <p>I saw the article from Dan
<!-- SC_OFF --><div class="md"><p>I've tried Gemma-4-E2B-it on my iPhone 16 with Google Edge Gallary app.<br /> The TTFT is very short (even with image input).<br /> And the
<table> <tr><td> <a href="https://www.reddit.com/r/OpenAI/comments/1t174ov/bringing_codex_computer_use_to_ios/"> <img alt="Bringing Codex computer use to iOS"
<!-- SC_OFF --><div class="md"><p>I'm continuing to play around with local llms on my framework13 laptop. </p> <p>So, limited memory bandwith and processing power means exploring
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