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Docs/Models & providers

Models & providers

Gauntlet

Gauntlet works toward a defined chat goal and combines implementation with repeated result checks.

1 min readUpdated: October 2026

Step by step

  1. 01

    Choose Gauntlet.

  2. 02

    Describe the goal and verifiable success criteria.

  3. 03

    Follow tasks, checks, and any questions.

  4. 04

    Assess the result against the agreed criteria.

Gauntlet

Check availability for your account, provider, and model.

  • Chat goal
  • Implementation
  • Checks and iteration

Good to know

  • A time limit, missing access, or required question can interrupt the work.

Troubleshooting

If a surface is empty, select an existing document or ask Metis to create a plan or canvas.

Troubleshooting guide

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Documentation
Overview
Getting started
QuickstartChoose an installationWhat is Metis?Accounts and initial setupConnect your first providerYour first taskSign inInstall on LinuxInstall on macOSInstall on Windows
Chat & context
Navigation & chatsCompose messagesResponses & tool callsAnswer questionsApprove actionsSearch & quick actions
Workspace
Agent overviewCanvasPlansMemoryFilesTerminalBrowserDesktopsServer monitorArrange the workspaceExport workspaces
Projects & teams
Create a projectProject overviewChat visibilityProject picture, color, and iconProject instructionsProject memoryProject skillsProject filesProject notesAgent model defaultLet agents manage the teamMembers & invitationsAgent teamsTeam presetsTeam overview
Notes
Notes & scratchpad
Agent Hub
SkillsConnections / MCPsCustom modes & rulesGlobal agent rules
Settings
GeneralModels — ConnectionsAgent — Runtime & memoryDevices — Remote clientsAdmin / ChatsUpdatesSearch settingsAttachments and file sizeSubagent modelToken compressionPreview compressionSounds and notificationsNotification deliverySet up voice inputChoose a microphoneRecording and streamingDictionaryConfigure the browser previewManage website dataWebsite and source code
Models & providers
AgentDeep ResearchPlanAskGauntletCursorOpenAIAnthropicGoogle GeminixAI / GrokOpenRouterOllama / LocalOpenAI-compatibleOpenAI CodexClaude CodeGoogle AntigravityGrok BuildOpenCodeModel options
Account & sharing
ProfileNotificationsUsage & costsShare chatsPublic shares
Guides & operations
Charts, graphs & mediaAutomationsOperate your installationTroubleshootingSet up a complete projectWork on a connected PCResearch and produce a reportGlossary and scopes

Popular starting points

Getting startedQuickstartGo from installation to your first verifiable task: set up Metis, connect a model, and start with a small request.Getting startedChoose an installationNative installation is recommended for Linux, macOS, and Windows. Install Metis on the computer or server that will run it, then pGetting startedWhat is Metis?Metis is your self-hosted workspace for AI agents. Conversations, files, browser, tools, and persistent context stay together. YouGetting startedAccounts and initial setupOn first launch, you set up the instance with an administrator account. The single-use operator token confirms your authority to mGetting startedConnect your first providerMetis needs model access to generate responses and run agent tasks. Setup displays authentication methods supported by the selecteGetting startedYour first taskCheck your setup with a small task whose result you can assess directly. You can then add files, browser access, or project contexGetting startedSign inSign in with an account on the relevant Metis instance. Your displayed profile name may differ from your login username.
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