Jan vs Temporal AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionJanTemporal AI
PricingFree (open-source Apache 2.0)Freemium: free self-hosted; paid cloud with usage-based billing
Deployment100% local (offline) desktop app, CLI, web, local API serverSelf-hosted or Temporal Cloud (managed)
Primary Use CaseLocal AI chat & autonomous agents with privacyDurable execution & workflow orchestration for reliable AI agents
IntegrationsOpenAI, Claude, Gemini, local models (HuggingFace, llama.cpp)OpenAI Agents SDK, Google ADK, Slack, NVIDIA, Docker, Kubernetes
Latest Newsv0.8.3 adds message branching and HTML/SVG artifacts (June 2026)Usage-based billing & custom roles pre-release (June 2026)
Best ForPrivacy-conscious users, offline developers, local model runnersTeams building crash-resistant, long-running AI workflows

Choose Jan if you need fully offline, privacy-first AI with local agents and model control — it's free and runs on your hardware. Choose Temporal AI if you're orchestrating mission-critical, durable workflows that must survive failures, especially for AI agents in production. They solve different problems: Jan is an AI endpoint; Temporal is the plumbing behind reliable execution.

Jan
Jan

Jan is a free, open-source local AI assistant that runs open models — Llama, Mistral, Qwen, DeepSeek — right on your desktop.

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Temporal AI
Temporal AI

Durable execution platform that keeps AI agents and long-running workflows alive through crashes, retries, and abandoned sessions.

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Pricing
Free
Freemium
Plans
$0
$150 credits for 90 days
Starting at $50 per million actions
Greater of $500/mo or 10% of usage
Custom
Popularity
6 views
7.5k views
Skill Level
Intermediate
Advanced
API Available
Platforms
DesktopAPI
WebAPI
Categories
💾 Local & On-Device AI🤖 AI Assistants
🕸️ Agent Frameworks & Orchestration⚙️ Developer Infrastructure
Features
Offline chat with local open models from HuggingFace
Bundled llama.cpp engine 0.5.0 shipped inside the app (v0.8.5)
Native web_search and web_fetch tools (v0.8.4)
Per-model chat template kwargs for llama.cpp (v0.8.4)
Token counter for remote and MLX providers (v0.8.4)
Backend-managed settings and credentials store (v0.8.4)
Message version branching with history (v0.8.3)
HTML and SVG artifact previews in chat (v0.8.3)
Video input for local vision models (v0.8.3)
Unified reasoning and tool timeline (v0.8.3)
AMD ROCm/HIP backend support on Linux (v0.8.2)
Pause-and-resume model downloads (v0.8.2)
Anthropic-compatible custom providers (v0.8.1)
Multi-Token Prediction for llama.cpp models (v0.8.0)
MCP tool images delivered to the model (v0.8.6)
Durable execution captures Workflow state at every step with no checkpointing or recovery code
Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust
Activities retry automatically with backoff, four timeout classes, and heartbeating
Signals, Queries, and Updates read and mutate running Workflows mid-flight
Workflow Streams for real-time interactivity with running executions
Durable AI agents via OpenAI Agents SDK and Google ADK running LLM and tool calls as Activities
Serverless Workers host durable AI agents on Amazon Bedrock AgentCore
Serverless Workers on AWS Lambda (public preview) and GCP Cloud Run (pre-release)
Standalone Activities as a durable job-queue pattern, GA across six SDKs (2026-09-15)
Native Task Queue priority and fair distribution without a custom queueing layer
Durable Timers sleep for months; cron Schedules support backfill and Continue-As-New
Saga pattern via compensating transactions that read like try/catch
Worker Versioning pins Workflows to a version so deploys don't corrupt in-flight runs
Cloud UI Strict Session Mode enforces 15-min inactivity timeout and 12-hour max session (GA 2026-09-18)
Replay tests validate against real histories; time-skipping tests fast-forward long timers in CI
Integrations
HuggingFace
OpenAI
Anthropic
Google
OpenAI Agents SDK
Google ADK
AWS Lambda
Google Cloud Run
Amazon Bedrock AgentCore
Kubernetes
GitHub Actions
GCP Marketplace
Azure

Who should pick which

  • Privacy-conscious individual
    Pick: Jan

    Jan runs 100% offline without an account, ensuring data never leaves your machine.

  • DevOps team orchestrating AI agents
    Pick: Temporal AI

    Temporal's durable workflows guarantee AI agent tasks survive crashes and retries.

  • Developer needing local AI API server
    Pick: Jan

    Jan provides a local API server compatible with OpenAI's spec for prototyping.

  • Enterprise building long-running payment workflows
    Pick: Temporal AI

    Temporal's Saga pattern and human-in-the-loop are ideal for financial transactions.

  • Researcher needing reproducible offline model experiments
    Pick: Jan

    Jan's local model management and CLI enable reproducible offline research.

Frequently Asked Questions

Jan vs Temporal AI: which should you choose?

Choose Jan if you need fully offline, privacy-first AI with local agents and model control — it's free and runs on your hardware. Choose Temporal AI if you're orchestrating mission-critical, durable workflows that must survive failures, especially for AI agents in production. They solve different problems: Jan is an AI endpoint; Temporal is the plumbing behind reliable execution.

Can Jan be used with Temporal AI together?

Yes: Temporal can orchestrate Jan's local agents for durable execution, combining offline AI with reliability.

Is Jan completely free?

Yes, Jan is open-source (Apache 2.0) and free forever, with no paid tiers.

Does Temporal AI offer a free tier?

Yes, you can self-host the Temporal Server for free; Temporal Cloud has a usage-based paid model.

Which has better integration with Slack?

Jan includes native Slack agents; Temporal integrates via its SDK and signals for workflow notifications.

Do both support vision models?

Jan supports video input for local vision models; Temporal does not directly handle models but can orchestrate them.

Which is better for a solo founder?

Jan is better for simple offline local AI; Temporal is overkill unless building complex multi-step agent workflows.

Can I run Jan on a Raspberry Pi?

Hypothetically yes, but performance depends on models; lightweight models may work, but GPU is recommended.

Does Temporal require coding?

Yes, Temporal uses workflow-as-code with multiple SDKs (Python, Go, TypeScript, etc.), requiring developer effort.

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Last reviewed: July 3, 2026