google/gemma-3-27b-it
Run locally on Apple devices with Mirai
- Type
- local
- From
- Quantization
- No
- Parameters
- 27B
- Size
- 50.3 GB
- Source
Gemma 3 is Google's family of lightweight, state-of-the-art open models, built from the same research and technology behind the Gemini models. The 27B instruction-tuned (IT) variant is the largest in the Gemma 3 lineup, offering strong performance across a wide range of tasks while remaining deployable on accessible hardware.
Multimodal & Multilingual
Gemma 3 27B IT is a multimodal model that accepts both text and image inputs and generates text output. Images are normalized to 896×896 resolution, and the model can produce responses of up to 8,192 tokens. It supports a generous 128K context window, making it well-suited for tasks that require processing lengthy documents or extended conversations. Multilingual capability spans over 140 languages, significantly broadening its applicability across global use cases.
Key Capabilities
- Question answering — grounded responses across diverse domains
- Summarization — distilling long-form content into concise outputs
- Reasoning — multi-step inference over text and visual inputs
- Image understanding — interpreting and describing visual content alongside text
Architecture & Deployment
As an instruction-tuned model, Gemma 3 27B IT has been fine-tuned to follow natural language instructions, making it practical for conversational AI, assistants, and agentic workflows. Despite its 27 billion parameter scale, it is designed to run in resource-conscious environments — from custom cloud infrastructure down to high-end desktop setups — helping democratize access to capable open-weight models.
Provenance
Developed by Google and released with open weights, Gemma 3 27B IT carries forward Google's commitment to making frontier-grade AI research broadly available. Both pre-trained and instruction-tuned variants are offered across multiple sizes, with this 27B IT checkpoint representing the flagship configuration for users seeking maximum capability.
spm https://github.com/trymirai/uzu.git
| 1 | import Uzu |
| 2 | |
| 3 | public func runChat() async throws { |
| 4 | let engineConfig = EngineConfig.create() |
| 5 | let engine = try await Engine.create(config: engineConfig) |
| 6 | |
| 7 | guard let model = try await engine.model(identifier: "google/gemma-3-27b-it") else { |
| 8 | return |
| 9 | } |
| 10 | for try await update in try await engine.download(model: model).iterator() { |
| 11 | print("Download progress: \(update.progress())") |
| 12 | } |
| 13 | |
| 14 | let messages = [ |
| 15 | ChatMessage.system().withText(text: "You are a helpful assistant"), |
| 16 | ChatMessage.user().withText(text: "Tell me a short, funny story about a robot") |
| 17 | ] |
| 18 | let session = try await engine.chat(model: model, config: .create()) |
| 19 | let stream = await session.replyWithStream(input: messages, config: .create()) |
| 20 | var message: ChatMessage? = nil |
| 21 | for try await update in stream.iterator() { |
| 22 | switch update { |
| 23 | case .replies(let replies): |
| 24 | message = replies.last?.message |
| 25 | case .error(let error): |
| 26 | print("Error: \(error)") |
| 27 | } |
| 28 | } |
| 29 | print("Text: \(message?.text() ?? "empty")") |
| 30 | } |