Weekly archive

New local AI models, Oct 6–12, 2025

5 open models released Oct 6–12, 2025, with how each runs on five reference devices.

  1. Qwen3-VL 8B Instruct

    Alibaba · LLM · 8.8B ·

    62Good quality (B) · 62 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.

    Runs on

    Memory, every quant and how to run it Check your own device

  2. Qwen3-VL 4B Instruct

    Alibaba · LLM · 4.4B ·

    54Fair quality (C) · 54 of 100: how capable the model is at F16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.

    Runs on

    Memory, every quant and how to run it Check your own device

  3. LFM2 8B-A1B

    Liquid AI · LLM · 8.3B (1.5B active) ·

    38Basic quality (D) · 38 of 100: how capable the model is at F16, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking.

    Runs on

    Memory, every quant and how to run it Check your own device

  4. Granite 4.0 H 1B

    IBM · LLM · 1.5B ·

    28Basic quality (D) · 28 of 100: how capable the model is at F16, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking.

    Runs on

    Memory, every quant and how to run it Check your own device

  5. Granite 4.0 H 350M

    IBM · LLM · 0.3B ·

    12Basic quality (D) · 12 of 100: how capable the model is at F16, whatever it runs on. Match score 47/100 (quality, fit, speed and memory use) sets the ranking.

    Runs on

    Memory, every quant and how to run it Check your own device

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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