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big-AGI

What it is

big-AGI is a local-first, vendor-neutral multi-model AI workspace designed for professionals (engineers, researchers, and founders). As of July 2026, it focuses on zero-latency interactions, advanced reasoning, and multi-model orchestration, fully supporting Gemma 3 and the MCP 3.0 Task Protocol.

What problem it solves

It allows users to simultaneously use, compare, and merge outputs from multiple AI models through its unique "Beam" feature. This enables robust decision-making, defeats hallucinations, and prevents vendor lock-in by providing a unified interface for all major LLM providers.

Where it fits in the stack

Category: AI Assistants & Knowledge / Professional AI Workspace. It acts as a high-performance orchestration layer between users and various LLM Providers, now enhanced with native MCP 3.0 tool integration.

Typical use cases

  • Multi-Model Intelligence (Beam): Querying several models (e.g., Claude 4.8, GPT-5.5, Gemma 3) simultaneously to find the best response.
  • Deep Research: Using "Gemini Deep Research" (now fully resumable) and web search with citations for technical validation.
  • Agentic Workflows: Leveraging "Anthropic Containers" for persistent files, bash sessions, and skills that span multiple turns.
  • Creative Production: Image generation and editing via Nano Banana and GPT-Image-2.

Key Features (July 2026 Update)

  • Beam 2: Multi-modal, program-based reasoning with follow-ups and saveable presets.
  • Anthropic Containers: 1-hour persistent sandbox for files and code execution (Bash) that maintains state across turns.
  • MCP 3.0 Native Support: Seamless integration of Model Context Protocol tools for local and remote data access.
  • AIX Resume Framework: Fully resumable sessions for long-running Deep Research or interrupted generation across providers.
  • Madly Optimized UI: Terminal-fast performance with advanced code rendering and peeking side panels.

Strengths

  • Zero Latency: Local-first architecture that runs almost entirely in the browser for instant response.
  • Universal Connectivity: Supports 100+ models from 20+ vendors, with auto-detection of features like "Thinking/Reasoning" and "Skills".
  • Human-in-the-Loop: Designed for experts who need fine-grained control over the reasoning process.
  • Privacy & Security: Local-first by default; encrypted reasoning supported for xAI/Grok models.

Limitations

  • High Density: The interface is optimized for productivity and might be complex for casual users.
  • Advanced-Only: Features like "Chain of Thought" merging and "Reasoning Effort" control require understanding of modern LLM parameters.

When to use it

  • For high-stakes decisions where cross-model verification is required.
  • When you need a persistent code execution environment (Sandbox) within your chat.
  • When you want the fastest possible multi-model interface for "vibe coding" or research.

When not to use it

  • For basic, mobile-only casual chat (optimized for power users).
  • If you prefer a "black box" experience without control over model parameters or reasoning steps.

Getting started

Web Access

  1. Navigate to app.big-agi.com.
  2. Add your API keys in the Models section.
  3. Launch Beam to compare the latest frontier models.

Self-Hosting (Docker)

docker run -p 3000:3000 ghcr.io/enricoros/big-agi

CLI examples

While primarily a web UI, big-AGI can be managed and deployed via CLI tools.

# Deploy big-AGI to Vercel for private use
npx vercel --prod

# Pull and run the latest big-AGI Docker image
docker pull ghcr.io/enricoros/big-agi && docker run -p 3000:3000 ghcr.io/enricoros/big-agi

# Run big-AGI locally for development
git clone https://github.com/enricoros/big-AGI.git && cd big-AGI && npm install && npm run dev

API examples

big-AGI exposes certain functionalities via local endpoints when self-hosted.

# Check the health of a local big-AGI instance
curl http://localhost:3000/api/health

# Trigger a model refresh via the management API (hypothetical)
curl -X POST http://localhost:3000/api/admin/refresh-models -H "Authorization: Bearer $ADMIN_TOKEN"
  • LobeHub: Another powerful multi-model UI.
  • OpenRouter: The recommended backend for big-AGI.
  • LiteLLM: Ideal for managing local model fallbacks.
  • Claude Code: Complementary CLI-based agentic workflow.
  • PydanticAI: For building production-grade agents that can integrate with big-AGI.
  • Documentation Writer: For maintaining the documentation of your big-AGI-based projects.
  • Superpowers: Curated skill bundles that can be used within big-AGI via MCP 3.0.

Sources / references

Contribution Metadata

  • Last reviewed: 2026-07-11
  • Confidence: high