AI frameworks at Apple

San Francisco, CA
💯
Replying to @peterfriese
Jev is typesafe, so it's only natural to map Swift types directly to Jev decision primitives:
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Richard Wei retweeted
Want to use @typesafeai's Jev in your @SwiftLang apps using the convenience of Apple's Foundation Models framework? Well - here you go (GitHub repo link in the replies)! (h/t to @rxwei for the inspiration!)
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Jev is a fantastic example of co-designing SDKs and models to unlock a new paradigm! When we were designing the Swift API for Apple’s Foundation Models framework two years ago, we wanted to make type-safe structured responses the standard for apps on our platform. That is why we created the `@​Generable` API, making constrained decoding approachable to app developers. This effectively eliminated structural hallucinations in both tool call arguments and responses, which were especially important for a small on-device model. developer.apple.com/document… It would be fascinating to see decision models conform to the `LanguageModel` protocol and work with `@​Generable` natively! The best part is that all the APIs are already there: Bools are "noul", enums represent choices, and `@​Guide` descriptions are instructions. A Swift model implementation simply needs to handle a schema conversation, and output probabilities can be stored directly in the response metadata. developer.apple.com/document…
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I clearly made some typos in the code example! 😅 The request should look like this:
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It supports both the on-device model and Private Cloud Compute! We built it to enable effortless automations for Mac users. It's free, zero setup, no privacy compromises.
TIL macOS 27 now comes with new fm cli 🤯 We can now use Apple's Foundation Models (on device) from CLI!
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Richard Wei retweeted
I've been using the on-device Apple foundation model to test out the SoC performance on the iPhone 17 Pro Max and 18 Pro Max A19 Pro Long Prompt: 2340ms TTFT, 45 tok/s Medium Prompt: 946ms TTFT, 70 tok/s Short Prompt: 638ms TTFT, 100 tok/s A20 Pro Long Prompt: 1125ms TTFT, 55 tok/s Medium Prompt: 437ms TTFT, 71 tok/s Short Prompt: 354ms TTFT, 150 tok/s
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Richard Wei retweeted
With iOS 27 Apple introduced its most powerful on-device model: AFM 3 Core Advanced It’s a 20 billion parameters model activating only between 1 to 4 billion parameters depending on the request Here’s the model running on iPhone 17 Pro
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Richard Wei retweeted
At our WWDC26 Recap event this week, I shared an overview of bringing intelligence into your apps on Apple platforms. 1/ Foundation Models Framework: Native Swift API for on-device, PCC & third-party LLMs (e.g. @GoogleDeepMind gemini, @claudeai, and others.) 2/ Core AI: Purpose-built framework for bringing custom models into your apps on Apple Silicon 3/ MLX: Open-source framework for model research, fine-tuning, local inference servers, and distributed computing 4/ Agentic Experiences: Multi-model workflows and context handoffs with specialized agents 5/ Evaluations: Automated tools to measure quality, uncover failures, and help you ship with confidence Watch: piped.video/live/V2i8f_NeKDI…
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Richard Wei retweeted
The overview maps everything else, including the bit nobody mentions: macOS 27 ships an fm CLI, and fm serve gives you a local OpenAI-compatible endpoint backed by Apple's models. I'll update the post as I publish the rest: ivanmagda.dev/posts/wwdc26-f…
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Richard Wei retweeted
My favorite part: Dynamic Profiles. One session swaps instructions, tools, and the model mid-conversation via a SwiftUI-style body. I built these mechanisms by hand for my coding-agent series, so I mapped Apple's versions onto ours, footguns included: ivanmagda.dev/posts/foundati…
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Richard Wei retweeted
PrivateCloudComputeLanguageModel: a 32K-context server model with reasoning, switched on with one line. No account, no keys, no per-token bill for eligible apps. Each user spends from a daily quota instead, and that quota deserves real UI. Deep dive: ivanmagda.dev/posts/foundati…
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Richard Wei retweeted
Last June, Foundation Models was a Swift API to one small on-device model. After WWDC26 the same session API runs Apple's server model, Claude, Gemini, or a local Qwen. I spent the week in the betas. Three posts on what changed:
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Richard Wei retweeted
We had a blast at the Machine Learning & AI Group Lab today! ML technologies, frameworks, models, evaluations, and lots of fun with @trebolloc, @LouisDhauwe and others. 🎬 Video is up on YouTube - questions and discussions on Core AI, MLX, Foundation Models framework, Evaluations and more! WWDC26 was amazing for AI/ML. Super excited for all the incredible experiences you’ll build with these technologies! Thank you! piped.video/live/n6TdbD7nh2k…
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Richard Wei retweeted
You can now use Gemini via Apple's Foundation Model framework. This means: - same calls for on-device and cloud-hosted inference - you can use Grounding with Google Search / Google Maps - access to Gemini's large context window (up to 1M tokens)
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Foundation Modelsめっちゃ進化してる😲iOS 27では、オンデバイスモデルにVision機能が追加されたことにより、画像に関する質問にも答えられるように。 UIImage, NSImage, CGImage, Core Image 型, CoreVideo, Pixel Buffer, ファイル URLの形式に対応。 大きな画像ほどトークンを消費する #wwdc26
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Richard Wei retweeted
If you missed our AI/ML Group Lab yesterday, we're doing another one on Friday June 12, 2026 9:00 AM – 10:00 AM PT. We'll discuss Core AI, Foundation Models framework, Evaluations framework and MLX. Join us! developer.apple.com/wwdc26/s…
We wrapped up an amazing panel discussion on the latest in AI and Machine Learning at WWDC26. Thank you for all your questions about agents in Xcode, Core AI, Evaluations framework, Foundation Models framework, MLX. Here is the recording ICYMI. piped.video/live/bXb18GwYQS8…
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Apple developers can now use @ㅤGenerable, LanguageModelSession and many familiar Swift APIs directly with Claude!
New for Apple developers: Foundation Models support for Claude lets developers use Apple's Foundation Models framework to call Claude for multi-step reasoning, code generation, and longer context.
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Richard Wei retweeted
For WWDC26, Apple has introduced a shift in how you think about the foundation models framework. The broad "Foundation Models" term could now refer to any of these 3 things, which can be confusing. → Apple Foundation Models (AFM) - the actual on- device and server LLMs from Apple . → Foundation Models Framework - a model-agnostic layer for running LLMs on Apple devices (both local AND server, Apple AND Third-Party) . → Foundation Models Framework Utilities - An open source package that adds extra utilities for working with LLMs. Supported on apple platforms and linux. The Framework is now the main product. AFM is just one of the options you can plug in.
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RT @conspirator: Anthropic and Google recently announced support for Apple's Foundation Models framework, making state-of-the-art Claude an…
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Richard Wei retweeted
Wait, what? 😱 Apple Foundation Model on Private Cloud Compute is working on fm CLI! Here's a video!
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