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Mirai Labs

@trymirai
Frontier on-device AI lab. Models, runtime & infrastructure to make on-device AI interactive, ambient & continuous.
San Francisco
trymirai.com
Joined January 2025
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  • user avatar
    Mirai Labs
    @trymirai
    Jul 9
    📣 We've just published our latest research on state-of-the-art speculative decoding in interactivity. Introducing a new approach that achieves a 4.37× speedup over autoregressive decoding in small batch setting and outperforms the strongest tuned DFlash baseline by 24.7%.
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  • user avatar
    Mirai Labs
    @trymirai
    Apr 2
    Google DeepMind released Gemma 4. Our engineer @norpadon analyzed the architecture
    user avatar
    Artur Chakhvadze
    @norpadon
    Apr 2
    Gemma 4 architecture analysis thread Just as Gemma3n, this thing has a galaxybrained architecture, very much not a standard transformer
  • user avatar
    Mirai Labs
    @trymirai
    Apr 2
    If you've implemented speculative decoding, you've run into this: your speculator predicts the distribution correctly and still gets rejected. Let’s take an example: "The random number from 1 to 10 inclusive is" Ideal LLM: uniform 1/10 across all numbers. Good speculator: same
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  • user avatar
    Mirai Labs
    @trymirai
    Mar 31
    Day 0 on-device support of the latest and the smallest @liquidai model LFM 2.5 350M is now available on @trymirai
    user avatar
    Liquid AI
    @liquidai
    Mar 31
    Replying to @liquidai
    Day 0 support across the stack: > Hardware: @AMD, @Intel, @Qualcomm > On-device: @lmstudio , @Cactuscompute, @RunAnywhereAI , @zeticai_ , @trymirai > Customization: @distil_labs
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  • user avatar
    Mirai Labs
    @trymirai
    Mar 31
    LFM2.5-350M is now available on Mirai. @liquidai smallest model outperforms Qwen3.5-0.8B on reasoning and agentic tool use. Running on Mirai in full precision, it exceeds 70 tokens/second on iPhone.
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