Official Technical Resources: Meta AI (page 1)
Official Technical Resources · Meta AI. Model cards, research and official project resources. This source has 141 entries admitted under this category's review policy, listed across 10 pages; each links directly to the original.
Authority tiers in this category: A1–A2.
Agent frameworks
Run your own agent loop on Muse Spark with the Claude Agent SDK or the OpenAI Codex app-server.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: AI Agent · Tool Calling · Agent Frameworks
Link last checked: 2026-09-24
Authentication
Create and manage API keys for authenticating requests to Meta Model API.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Model Deployment Options · LLM Observability and Tracing · Agent Identity, Authorization, and Secrets
Link last checked: 2026-09-24
Use Model API with coding agents
Connect coding agents like OpenCode, Codex, and Claude Code to Model API and drive Muse Spark for agentic coding workflows.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: AI Agent · Tool Calling · Agent Frameworks
Link last checked: 2026-09-24
Build a computer-use agent
Drive Muse Spark as a computer-use agent with the native computer tool, turning screenshots into structured mouse and keyboard actions that your own driver executes.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: AI Agent · Tool Calling · Agent Frameworks
Link last checked: 2026-09-24
Error handling
Handle API errors, troubleshoot common issues, and build resilient Meta Model API integrations with proper retry logic.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Model Deployment Options · LLM Observability and Tracing · Agent Identity, Authorization, and Secrets
Link last checked: 2026-09-24
File handling
Send files to the model inline in a Responses or chat completion request, or upload them once with the Files API and reference them by ID.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Multimodal Models · Retrieval-Augmented Generation (RAG) · Model Deployment Options
Link last checked: 2026-09-24
Image generation with Muse Image
Generate and edit images with Muse Image through a conversation: interleave text and reference images and refine across turns on the Responses API, or make one-off calls with the OpenAI-compatible images endpoints.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Multimodal Models · Diffusion Models · Multimodal Models
Link last checked: 2026-09-24
Image understanding
Analyze images with text prompts using URLs, base64 encoding, or uploaded files.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Multimodal Models · Diffusion Models · Multimodal Models
Link last checked: 2026-09-24
Media segmentation
Detect, segment, and follow objects in images and video from a short text prompt with Segment Anything Model (SAM).
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Image Editing · Multimodal Models · Multimodal Models
Link last checked: 2026-09-24
Models
The model families on Meta Model API, spanning Muse Spark, Muse Image, Muse Voice Transcribe, Segment Anything Model segmentation, and the open-weight Muse Glimmer, and how to choose the right model.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Model Selection and Cost · Multimodal Models
Link last checked: 2026-09-24
Build with Meta Model API and Muse Code
Build with Meta Model API and Muse Code: call Muse Spark for agentic and coding work, generate and edit images with Muse Image, transcribe speech with Muse Voice Transcribe, segment images and video with Segment Anything Model, or download Muse Glimmer open weights.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Image Editing · Multimodal Models · Multimodal Models
Link last checked: 2026-09-24
Pricing and rate limits
Standard and contributor pricing tiers, per-token pricing, image pricing, Muse Voice Transcribe pricing, Segment Anything Model segmentation pricing, and rate limits for Meta Model API.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Model Deployment Options · LLM Observability and Tracing · Agent Identity, Authorization, and Secrets
Link last checked: 2026-09-24
Prompt caching
Prompt caching is automatic — repeated prompt prefixes are served from cache to cut latency and input-token cost, with no key or setup required.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Structured Outputs · Context Window · Prompt Engineering
Link last checked: 2026-09-24
Reasoning
Control how much the model thinks before responding using the reasoning_effort parameter.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Structured Outputs · Context Window · Prompt Engineering
Link last checked: 2026-09-24
Segment Anything Model client libraries
Parse Segment Anything Model (SAM) segmentation output, render mask and box overlays, and play segmented video with the Meta-SAM TypeScript packages.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Meta's own implementation and claims. Recheck preview products, pricing and API versions before use.
Related concepts: Image Editing · Multimodal Models · Multimodal Models
Link last checked: 2026-09-24