Weekly archive

New local AI models, May 12–18, 2025

5 open models released May 12–18, 2025, with how each runs on five reference devices.

  1. Wan 2.1 VACE 14B

    Alibaba · Video · 17.3B ·

    78Great quality (A) · 78 of 100: how capable the model is at FP16, 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

  2. Skywork OR1 32B

    Skywork · LLM · 33B ·

    72Great quality (A) · 72 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking.

    Runs on

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

  3. dots.llm1 Instruct

    rednote · LLM · 143B (14.0B active) ·

    75Great quality (A) · 75 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.

    Runs on

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

  4. Devstral Small 2505

    Mistral AI · LLM · 24B ·

    62Good quality (B) · 62 of 100: how capable the model is at Q4_K_M, 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

  5. Wan 2.1 VACE 1.3B

    Alibaba · Video · 2.2B ·

    55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 57/100 (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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