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Mirai vs Ollama

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors. Ollama publishes a starting price ($20); Mirai does not. Only Ollama has a free tier. Both ship a public API.

MiraiOn-device AI inference stack for Apple Silicon, aimed at fast, private, local model execution.OllamaRuns open-weight language models locally from one command, with a hosted tier for larger models

Side by side

FactMiraiOllama
CategoryModel Hosting & InferenceModel Hosting & Inference
Pricing modelContactFreemium
Starts at—$20 month
Public APIYesYes
PlatformsmacOS, APImacOS, Windows, Linux, API, Web
CompanyMirai LabsOllama Inc.
Launched—2023
Last verifiedSep 1, 2026Sep 6, 2026

What our research says

Mirai

Mirai is a local inference stack purpose-built for Apple Silicon rather than a cloud model ported down, which matters for latency-sensitive or privacy-sensitive AI features. The catch is that pricing is entirely undisclosed and Android support is still on the roadmap, so today it mainly serves iOS/macOS-first teams.

Pros

  • Runtime and models are co-designed specifically for device constraints rather than a cloud model squeezed down
  • Ships a macOS chat app plus a CLI and SDK for developers to build on
  • Founding team has previously shipped consumer AI apps at real scale (Prisma, Reface)

Cons

  • No pricing is published anywhere on the site
  • Android support is listed as not yet available
  • No detail on how the SDK is licensed or billed for production use

Ollama

The simplest way to get an open-weight model answering on your own hardware, and its local API has become a default target that most agent frameworks already speak. The cloud tier is the practical escape hatch when a model will not fit in your RAM. What you do not get is fleet-scale serving: this is a single-node runtime, not an inference platform with autoscaling and usage metering.

Pros

  • One command pulls and runs a model, with no environment wrangling
  • Local HTTP API that most agent frameworks already support
  • Works fully offline once weights are downloaded
  • Cloud tier covers models too large for local hardware, in US, EU and Singapore regions
  • Runtime is open source under a permissive licence

Cons

  • Single-node runtime with no autoscaling or multi-tenant serving
  • Max tier signups were paused for capacity when checked
  • Local speed is capped by your own GPU or RAM

Which one fits

Choose Mirai if you need

  • iOS/macOS developers wanting local LLM inference
  • privacy-sensitive on-device AI features
  • teams avoiding per-call cloud inference costs

Choose Ollama if you need

  • developers prototyping against local models
  • privacy-constrained work that cannot leave the machine
  • running an offline model behind an existing OpenAI-shaped client

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