--- title: "🧪 64MB Ultra-Lightweight phonon-31m-en Beats Kokoro in Blind Test: Local AI Lab" description: "Want to run smooth English text-to-speech on your laptop or browser? The newly open-sourced phonon-31m-en has only 31M parameters, requiring just 64.5 MB after quantization, and its official blind test results actually beat the famous Kokoro model. In this episode, we'll also share a 28B reasoning model that fits on a single GPU, and a powerful ComfyUI video generation tool with over 780,000 downloads. How do you deploy them locally? I'll tell you in a moment." canonical_url: "https://blog.markkulab.net/en/local-ai-lab/local-ai-lab-2026-10-27" author: "Mark Ku" author_url: "https://blog.markkulab.net/en/author/mark-ku" site: "Mark Ku's Tech Notes" date_published: "2026-10-27T02:00:00.000Z" category: "On-Premise AI Lab" tags: ["local-ai", "podcast", "地端模型", "lora", "開源模型", "phonon-31m-en", "Raon-1-mini-preview", "Minimax-h3_Singularity"] language: "en" license: "CC BY 4.0" license_url: "https://creativecommons.org/licenses/by/4.0/" attribution: "when reusing or quoting, credit the author and link back to the original" --- # 🧪 64MB Ultra-Lightweight phonon-31m-en Beats Kokoro in Blind Test: Local AI Lab Want to run smooth English text-to-speech directly on your laptop or in your browser? The newly open-sourced phonon-31m-en has only 31M parameters, and after quantization, it takes up just 64.5 MB. Its official blind test results even beat the well-known Kokoro model. In this issue, we will also share a 28B reasoning model that can fit onto a single GPU, as well as a powerhouse video generation model dedicated to ComfyUI with over 780,000 downloads. We will show you how to deploy them locally in just a moment. --- ## Featured This Week ### 1. gradium/phonon-31m-en: Ultra-Lightweight 24 kHz Local Text-to-Speech Model - **What is it**: This is an ultra-lightweight text-to-speech (TTS) model licensed under Apache 2.0. With only 31M parameters, it is designed specifically for highly efficient local voice generation. - **Use Cases**: - **Independent and private local smart home voice assistants**: Instantly convert system status or smart home notifications into smooth 24 kHz English speech without an internet connection, completely eliminating concerns about private conversations being uploaded to the cloud. - **Offline games and interactive application NPCs**: Leverage its streaming capabilities to play audio in real-time as it generates, completely eliminating the network latency of cloud APIs to make in-game NPC dialogue responses more instant and natural. - **Local accessibility voice prompts**: Integrate it into Home Assistant or use it as an OpenAI API-compatible local voice server to provide ultra-fast, low-latency screen reading and accessibility voice prompts for visually impaired users. - **Can you run it**: The official model card indicates that the model is lightweight enough to run directly in a browser tab, on a mobile phone, or on a laptop CPU. The 8-bit quantized weight file (model.q8.gguf) requires only 64.5 MB. Available formats include GGUF and Safetensors. - **Community Traction**: It has reached 112 trending score on Hugging Face, currently accumulating 39.5k downloads and 115 likes. - **How it compares**: According to the blind pairwise comparison (Elo) and hard set LLM Word Error Rate (WER) benchmarks provided in the official model card, phonon-31m-en outperforms similar well-known open-source models like Kokoro (Elo 2043, WER 3.5%) and Magpie (Elo 1939, WER 28%) with an Elo rating of 2098 and a WER of 1.5%. - **How to get it**: The official documentation states that it can be loaded via Python's `ptts` library. First run `pip install ptts`, then use `tts = ptts.TTS("hf://gradium/phonon-31m-en", lang="en", quant="q8")` for initialization and voice generation. - **Link**: [Hugging Face Page](https://huggingface.co/gradium/phonon-31m-en) --- ### 2. KRAFTON/Raon-1-mini-preview: MoE Inference Model Supporting Ultra-Long Context and Thinking Mode - **What is it**: This is a 28.8B Mixture-of-Experts (MoE) architecture model released by KRAFTON under the Apache 2.0 license. Although the total parameter count is 28.8B, it only requires 4.3B active parameters per token and features extreme KV Cache optimization. - **Use Cases**: - **Local Agents and automated development**: Developers can use Agent frameworks like Hermes Agent, Pi, or OpenCode locally, calling Raon-1 mini via an OpenAI-compatible API to perform complex tool calling and automated code generation. - **Single-GPU local complex reasoning**: Perform complex local mathematical and scientific reasoning on consumer-grade graphics cards (such as a single RTX 5090) or Apple Silicon chips, utilizing its built-in "thinking mode" and long-context support of up to 262,144 tokens. - **Ultra-fast inference output**: Pair it with the officially released DFlash2 lightweight draft model for speculative decoding, achieving over 2x faster inference output on local GPUs. - **Can you run it**: The official README indicates that in its MoE architecture, only 7 MLA layers retain the KV Cache (requiring only about 8 KiB per token in BF16 precision). The official release provides MXFP8 and NVFP4 quantized versions, where the NVFP4 version allows inference on a single NVIDIA RTX 5090 (32 GB VRAM). GGUF (Q4_K_M) and MLX versions are also available, offering native support for llama.cpp and MLX. - **Community Traction**: It has reached 185 trending score on Hugging Face, currently with 1.4k downloads and 200 likes. - **How it compares**: According to tests in the official README, in comparisons with other MoE baseline models (including Qwen3.6-35B-A3B and Gemma 4 26B-A4B), Raon-1 mini preview achieved the best results in knowledge and reasoning benchmarks such as MMLU Pro (76.5), GPQA Diamond (84.3), and IFBench (84.2). - **How to get it**: The official documentation states that the model repository is currently gated. You need to request automatic access on the Hugging Face page first, and then run it using llama.cpp: `./build/bin/llama-cli -hf KRAFTON/Raon-1-mini-preview-gguf:Q4_K_M --ctx-size 262144 --reasoning on`. - **Link**: [Hugging Face Page](https://huggingface.co/KRAFTON/Raon-1-mini-preview) --- ### 3. WarmBloodAban/Minimax-h3_Singularity: Ultra-Smooth Fine-Tuned Video Generation Model for ComfyUI - **What is it**: This is a video generation model dedicated to ComfyUI, fine-tuned and merged based on the MiniMax-H3 base model. Licensed under Apache 2.0, it is designed specifically for engineers who love self-hosting and local creation. - **Use Cases**: - **High-action combat video generation**: Creators can use Image-to-Video (I2V) workflows in local ComfyUI to transform static High Dynamic Range (HDR) images into smooth, motion-blur-free, high-speed martial arts or sword combat videos. - **Distant face restoration in medium-to-long shots**: Video post-production editors can leverage its "Distant Face Restoration" feature when generating medium-to-long shots, preventing character faces in the generated videos from distorting or collapsing structurally. - **Dynamic assets for game art**: Game artists can take advantage of its optimization for visual effects (VFX) to quickly generate dynamic assets locally, such as magic auras, particle effects, or spell-casting animations. - **Can you run it**: The official release includes a V2 INT8 quantized version. To achieve high-speed generation, the author recommends pairing it with the `minimax_h3_ref2v_turbo_4step_v0.1` acceleration LoRA, enabling fast inference in just 4 steps. - **Community Traction**: It has reached 127 trending score on Hugging Face, accumulating a massive 783.2k downloads and 916 likes, making it highly popular among community creators. - **How it compares**: According to the author's model card, this model is based on the MiniMax-H3 base model, merging multiple key fine-tuning checkpoints such as ref, fl, and b25-49, and undergoing 3 full days of precise pruning and weight optimization. Compared to the original MiniMax-H3, it significantly reduces overly oily skin and unnatural gloss, and fixes the issue in the V1 version where Audio Reference Conditioning failed to work. - **How to get it**: The official documentation states that after downloading the weights, you can place them directly into the corresponding model folder in ComfyUI. It supports various workflows including Text-to-Video, Image-to-Video, Reference-to-Video, and Video-to-Video. - **Link**: [Hugging Face Page](https://huggingface.co/WarmBloodAban/Minimax-h3_Singularity) --- ## Conclusion Looking at the models introduced today, the trend of local AI is clearly moving toward extreme lightweighting and specialization. Whether it is a text-to-speech model that runs on just 64MB or a highly optimized 28B reasoning model that fits on a single GPU, local deployment is becoming much more accessible. If you have some spare hardware lying around, why not start playing with phonon-31m-en, which takes up the least space? See you in the next episode. --- ## About this article and its author Originally published on [Mark Ku's Tech Notes](https://blog.markkulab.net/en/local-ai-lab/local-ai-lab-2026-10-27) License: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — when reusing or quoting, credit the author and link back to the original ### About the author **[Mark Ku](https://blog.markkulab.net/en/author/mark-ku)** — Software engineer - 10+ years as a software engineer - Built North-American e-commerce and AI SaaS subscription billing ### Free tools built by the author All of these are free to use: - [Free PDF Sign Tool](https://blog.markkulab.net/en/tools/pdf-sign): Online PDF sign tool — draw, type, or upload a signature, then drag, resize, and download. Everything runs in your browser; nothing is uploaded. - [VS Code Refactory](https://blog.markkulab.net/en/tools/refactory): Refactory is a VS Code refactoring extension: 34 actions plus a 37-rule code-smell inspection layer with a Code Health dashboard, across 18 languages, backed by 534 tests. It learns your repo's conventions: where interfaces live, where DI is registered, whether 'use client' belongs. It ranks files by git churn × complexity so you know what to fix first, and hands any smell to the Claude Code already on your machine. Free to use, and your source never leaves your computer. - [DB-Kit Database Manager](https://blog.markkulab.net/en/tools/db-kit): DB-Kit is a lightweight, cross-platform database manager built with Tauri + Rust + React. Manage MySQL, MariaDB, PostgreSQL, SQL Server, Oracle, SQLite, MongoDB, Redis, Kafka, Elasticsearch and RabbitMQ from one consistent interface: passwords encrypted in the OS keychain, SSH tunnels, full CRUD, a visual query builder, stacked multi-statement result sets, cross-connection data transfer, schema & data compare with sync SQL and schema snapshots, Excel / CSV import & export, visualized execution plans, ER diagrams, scheduled backups, SQL stress testing with p50–p99 latency percentiles, a 15-rule SQL review engine, Review & Run (AI review plus per-statement backups and an auto-generated rollback script), Kafka message browsing with monitoring & alerts, an SSH terminal with SFTP / FTP, Docker / Kubernetes, remote desktop (RDP / VNC / RustDesk), file / folder compare, stored procedure integration tests, six UI languages, a built-in AI assistant (a local CLI or any Anthropic / OpenAI-compatible API; natural-language SQL, AI review and tuning advice) and the dbk CLI. Free and open source (MIT), with installers for Windows, macOS and Linux. - [VS Code Super Mermaid](https://blog.markkulab.net/en/tools/super-mermaid): Super Mermaid is a VS Code extension for beautiful Mermaid diagrams out of the box: auto-colored live preview, mouse pan & zoom, high-res PNG / SVG export, 21 templates and multiple themes. Free and open source (MIT). - [React Super Mermaid](https://blog.markkulab.net/en/tools/react-super-mermaid): react-super-mermaid is an open-source React component library: render beautiful Mermaid diagrams with a single , with built-in colorful / sketch themes, pan & zoom, in-diagram search, and high-res SVG / PNG export. Lightweight, SSR-safe, fully typed. Free and open source (MIT). - [Jira / Confluence Super Mermaid](https://blog.markkulab.net/en/tools/jira-super-mermaid): An Atlassian Forge app: write Mermaid syntax directly inside a Jira issue or a Confluence page and get flowcharts, sequence diagrams, state machines and Gantt charts. 11 diagram types, SVG / PNG export, light and dark themes, full CJK support. Runs on Atlassian: your diagrams live in your own site and the app calls no third-party service. Free, coming soon to the Atlassian Marketplace. - [Mermaid Live Preview](https://blog.markkulab.net/en/tools/mermaid-preview): Write Mermaid in your browser, see it render instantly, and share the whole diagram as a single link. No sign-up, nothing uploaded to a server, and mermaid.live share links work as-is. - [React Intl Phone Number](https://blog.markkulab.net/en/tools/react-intl-phone-number): react-intl-phone-number is an open-source React component: framework-agnostic and antd-free, with E.164 in/out, a searchable flag / country-code dropdown, configurable validation levels (strict / mobile-strict / loose), themeable CSS, and i18n — phone logic powered by google-libphonenumber. Lightweight and fully typed. Free and open source (MIT). - [Uptime Kuma Cluster](https://blog.markkulab.net/en/tools/uptime-kuma-cluster): Turn single-node Uptime Kuma into a highly available cluster: OpenResty + Lua smart load balancing, shared MariaDB state, health checks and automatic failover, plus cluster-management REST APIs. One Docker Compose command to start. Free and open source (MIT). - [AI Podcast Cut](https://blog.markkulab.net/en/tools/ai-podcast-cut): Drop in a recording and it removes fillers and stutters, levels loudness segment by segment, and sends a second agent to review every cut. Cut points snap to word boundaries and zero crossings, every splice gets a fade, and sentence-end breaths are preserved. Desktop app for Windows, macOS and Linux. MIT licensed; the Windows installer bundles ffmpeg. - [AI Video Cut](https://blog.markkulab.net/en/tools/ai-video-cut): Pick something in your video: type it (face, license plate, phone screen, logo), click points or drag a box, or let Claude Code / Codex pick it. AI Video Cut tracks it frame by frame, then mosaics or blurs it, recolors it, pins stickers and text to it, swaps a screen or poster for your own image or video, or removes it using background that other frames actually captured. Plus sequence editing, local captions and an AI assistant. Free, open-source (MIT) Windows desktop app (macOS / Linux experimental) that runs locally, nothing uploaded. - [open-pos restaurant POS](https://blog.markkulab.net/en/tools/open-pos): One computer and one receipt printer is enough to open the shop. Your data lives on your own disk, no subscription, no lock-in, MIT licensed. Money is integer New Taiwan dollars with tax split by the statutory formula, so sales + tax always equals the total. Printing goes straight over ESC/POS on TCP 9100, with no vendor driver. Tauri + Rust + SQLite desktop app, v1.0 in development. - [.NET e-commerce API template](https://blog.markkulab.net/en/tools/dotnet-ecommerce-api): An e-commerce backend API template built on .NET 10: Controller → Service → Repository layering, Autofac convention-based registration, SqlSugar for MySQL / MariaDB and SQL Server, Redis cache and message queue, Hangfire jobs, JWT auth, and an extensible payment provider module (ECPay, Newebpay). Apache 2.0. - [Open Token Monitor team AI usage](https://blog.markkulab.net/en/tools/open-token-monitor): Collect token usage and equivalent cost from every employee's AI coding tools into a hub you host yourself: PostgreSQL, org roster, dashboards compared by company and department, and a reports API. Electron and Rust/Tauri clients upload every 30 minutes. MIT licensed, one Docker command. - [ai-security-monitor defensive security](https://blog.markkulab.net/en/tools/ai-security-monitor): ai-security-monitor is a single Rust binary for your computers and servers. It finds unusual connections, rates them safe / unknown / suspicious / dangerous against 26 public threat-intel sources, and checks firewalls, open ports, vulnerabilities and 60 hardening rules. Security Hub shows the whole fleet, and Claude Code / Codex explain it in plain words. MIT, free, self-hosted. ### Daily podcasts - [Mark's Tech Insights — Daily AI News](https://blog.markkulab.net/en/category/tech-news): Daily curated AI and tech trends. Catch the latest developments via audio summaries — covering AI applications, software architecture, DevOps, and engineering practice. — RSS: https://blog.markkulab.net/feed.xml - [AI股市蝦聊](https://blog.markkulab.net/en/category/ai-stock-chat): Every trading day, an AI-analyzed take on the Taiwan stock market, delivered as a two-host conversation covering the session and the next-day outlook. — RSS: https://blog.markkulab.net/ai-stock-chat/feed.xml - [開源好物日報](https://blog.markkulab.net/en/category/open-source-weekly): A daily two-host pick of free open-source tools surfaced from real Hacker News, GitHub, and Reddit buzz — what pain they solve and the fastest way to get started. — RSS: https://blog.markkulab.net/open-source-weekly/feed.xml - [AI 運動日報](https://blog.markkulab.net/en/category/sports-weekly): Two hosts talk NBA, MLB and world sport every day — scores, records and the stories behind them, from a Taiwanese fan perspective. — RSS: https://blog.markkulab.net/sports-weekly/feed.xml - [AI 國際新聞快報](https://blog.markkulab.net/en/category/world-news): A daily two-host briefing that makes sense of the past 24 hours in world news — geopolitics, the global economy, conflict and security, disasters and climate — from a Taiwanese perspective, neutral and fully sourced. — RSS: https://blog.markkulab.net/world-news/feed.xml - [地端 AI 實驗室](https://blog.markkulab.net/en/category/local-ai-lab): Every day, a two-host look at open-weight models and LoRAs you can actually run on your own machine: what they are for, whether your GPU can handle them, and how they compare — sourced from official model cards. — RSS: https://blog.markkulab.net/local-ai-lab/feed.xml - [AI 行銷日報](https://blog.markkulab.net/en/category/ai-marketing): Every day, two hosts break down the latest in AI for marketing, advertising, SEO/GEO and content marketing: practical, never sponsored, every story sourced. — RSS: https://blog.markkulab.net/ai-marketing/feed.xml - [AI 資安日報](https://blog.markkulab.net/en/category/ai-security): Every day, two hosts cover the latest where AI meets cybersecurity: LLM and AI agent vulnerabilities, prompt injection, model supply-chain risks and AI-powered attacks, from a defense-first angle with every story sourced. — RSS: https://blog.markkulab.net/ai-security/feed.xml ### Newsletter [Subscribe to the newsletter](https://blog.markkulab.net/en/subscribe) — Be the first to know about new posts. 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