Mirai vs Temporal AI

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

Analysis reviewed Live tool data as of 2026-09-15
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At a glance

DimensionMiraiTemporal AI
PricingContact salesFree open-source + Cloud usage-based billing
Best ForOn-device AI on Apple SiliconReliable AI agents & multi-step workflows
PlatformApple Silicon (macOS/iOS)Cloud + self-hosted (K8s, Docker)
Key FeatureHardware-aware local inference engineDurable execution with automatic recovery
IntegrationsNone listedOpenAI, Google ADK, Slack, Twilio, Salesforce
Latest NewsSparse buffers for KV cache, new quantization (June 2026)Usage-based billing, Custom Roles pre-release (June 2026)

Choose Temporal AI if you need reliable, fault-tolerant orchestration for AI agents and microservices—it's battle-tested at scale (OpenAI, Cursor). Choose Mirai if you are building on-device AI for Apple Silicon and can tolerate a lower-level, more experimental SDK. They solve different problems: durability vs. local latency.

Try MiraiTry Temporal AI
Mirai
Mirai

On-device inference engine and SDK for Apple Silicon, built for real-time, always-on AI on iOS and macOS.

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Temporal AI
Temporal AI

Open-source durable execution platform that keeps long-running workflows and AI agents alive through crashes, retries, and flaky APIs.

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Pricing
Contact Sales
Freemium
Plans
—
$0
Starting at $50 per million actions
Starting at $100/mo
Starting at $500/mo
Custom
Custom
Popularity
2 views
7.5k views
Skill Level
Advanced
Intermediate
API Available
Platforms
DesktopCLIWeb
WebAPICLIPlugin
Categories
💾 Local & On-Device AI⚙️ Developer Infrastructure
🕸️ Agent Frameworks & Orchestration⚙️ Developer Infrastructure
Features
On-device inference on Apple Silicon (M-series)
uzu: open-source Rust inference engine
lalamo: model optimization and conversion tooling
Batch-size-1 runtime for latency-first execution
Hardware-aware tensor operation optimization
Quantization co-designed with model architecture
CLI that chats with models and serves them as a local API
macOS app for testing and deployment
Pre-optimized models library
Sparse buffers for KV cache (June 2026)
Mirai Quantization method for local LLMs on Apple silicon (June 2026)
Autoregressive drafting research, Trees from Marginals (July 2026)
Cloud inference option
Apple device automation application layer
Android support (listed as coming soon)
Durable execution with automatic state capture at every Workflow step
Workflow-as-code orchestration with replay, pause, and recovery
Activities that retry automatically with backoff, four timeout classes, and heartbeating
Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust
Rust SDK in public preview with quickstart and API docs
Signals, Queries, and Updates for mid-flight interaction with running Workflows
Workflow Streams for real-time interactivity with running executions
Human-in-the-loop orchestration without duct-taped workflow wrappers
Saga pattern via compensating transactions
Durable Timers that sleep for months plus cron Schedules with backfill
Task Queue Priority and Fairness (GA)
Worker Versioning for safe deploys, with Replay tests against real histories
Child Workflows and Temporal Nexus for durable cross-team composition
Temporal Worker Controller for Kubernetes lifecycle management (GA)
Serverless Workers for AWS Lambda (public preview) and Google Cloud Run (pre-release)
Integrations
LangGraph
OpenAI Agents SDK
Google ADK
Google Gemini
Google Cloud Run
AWS Lambda
Azure
Kubernetes
LlamaIndex
Slack
Salesforce
Twilio
NVIDIA
Braintrust

Who should pick which

  • Solo founder building AI agents
    Pick: Temporal AI

    Temporal's free open-source server and extensive SDKs allow building reliable, crash-resistant agents without upfront cost.

  • iOS/macOS developer creating on-device AI app
    Pick: Mirai

    Mirai is specifically designed for Apple Silicon, enabling low-latency local inference ideal for real-time interactive experiences.

  • Enterprise team orchestrating microservices
    Pick: Temporal AI

    Temporal's durable execution, Saga pattern, and human-in-the-loop features are proven in production at companies like Stripe and Snap.

Frequently Asked Questions

Mirai vs Temporal AI: which should you choose?

Choose Temporal AI if you need reliable, fault-tolerant orchestration for AI agents and microservices—it's battle-tested at scale (OpenAI, Cursor). Choose Mirai if you are building on-device AI for Apple Silicon and can tolerate a lower-level, more experimental SDK. They solve different problems: durability vs. local latency.

Which tool is better for AI agent workflows?

Temporal AI is better for building reliable, long-running AI agents that need automatic retries, state recovery, and human oversight. Mirai is not designed for workflow orchestration.

Can Mirai run on non-Apple hardware?

No, Mirai is exclusively for Apple Silicon (M-series). Temporal AI runs on any infrastructure that supports its server (Kubernetes, Docker, cloud).

Does Temporal AI offer on-device inference?

No, Temporal AI is an orchestration platform, not an inference engine. It can integrate with cloud or local AI services via Activities.

What is the pricing of Mirai?

Mirai's pricing is not publicly listed; you must contact their sales team. Temporal Cloud has usage-based billing, and the open-source server is free.

Which tool has better support for retries and failures?

Temporal AI excels with built-in automatic retries, timeouts, and recovery from crashes. Mirai does not provide workflow-level fault tolerance.

Can I use Temporal AI for on-device AI on Apple Silicon?

Temporal AI can orchestrate on-device AI if you write Activities that call local inference (e.g., Mirai), but it's not optimized for Apple Silicon itself.

What integrations does Mirai have?

Mirai's integration list is empty, meaning it's a standalone SDK. Temporal AI integrates with OpenAI, Slack, Twilio, Salesforce, and more.

Which tool is more mature?

Temporal AI is more mature, with broad adoption (OpenAI, Stripe, Snap), multiple SDKs, and a large community. Mirai is newer and more niche.

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Mirai
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Last reviewed: July 3, 2026