AppiReview
Poe - Fast AI Chat
Productivity

Poe - Fast AI Chat

by Quora, Inc.
4.4Rated 4.4 out of 5
Ratings
452K
Downloads
10M+
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Our Take Best for the right user

Poe is one of the most practical ways to keep several leading AI models in one app and compare their answers, and its custom-bot builder is easy to pick up. The main caveat is the points system: top reasoning models use up the allowance quickly, so free users and heavy coders should plan around lighter models or a subscription.

4.2Rated 4.2 out of 5 / 5 · AppiReview Editor's Score
Who it's for
  • People who want GPT, Claude, Gemini, and open models in one app instead of juggling separate accounts and subscriptions
  • Writers, students, and developers who like running the same prompt past several models and keeping the best answer
  • Teachers and hobbyists who want a custom tutoring or coding bot without handling API keys or servers
Who it's NOT for
  • Anyone who relies on one model all day; that provider's own app usually offers deeper features for it
  • Free-tier users who plan long coding or analysis sessions on top reasoning models, where daily points run out quickly
  • People who want an assistant built into Android itself, with screen reading or system-level shortcuts
  • Teams whose data rules bar routing documents through an intermediary service
Reviewed Nov 2026 by AppiReview Editors
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Overview

If you already find yourself pasting the same question into ChatGPT, then Claude, then Gemini to see which answer holds up, Poe is built for exactly that habit, and it remains one of the most convenient ways to do it on Android. It puts models from OpenAI, Anthropic, Google, Meta, and a range of open-source projects behind one login, one chat history, and one bill. The catch is the bill itself: Poe meters everything in compute points, and the most capable reasoning models spend those points fast enough that free users and heavy coders will feel the ceiling quickly.

That trade-off shapes the whole review. For people who value breadth — trying a new model soon after it launches, checking one answer against another, or building a small custom bot for a class — Poe is an easy app to like. For people who live inside a single model all day, that provider’s own app usually gives more depth, and Poe’s main advantage matters much less.

What Poe does best

The core idea is simple: one chat app with many engines underneath. You pick a bot — GPT, Claude, Gemini, Llama, or one of many specialised models — and chat with it the same way regardless of who built it. Conversations, custom bots, and account settings sync across Android, iOS, and the web, so a thread started on the phone can be finished at a desk.

What sets Poe apart is how easily you can move between models mid-task. Within an active conversation you can switch to a different model, which turns comparison from a chore into a habit. Ask one model to summarise a contract clause, then ask another whether anything was missed. Generate a function with one model and have a second review it. For coding, writing, and research, where the “best” model genuinely varies by prompt, that side-by-side workflow is the main reason to install Poe, and it’s the strength users praise most consistently.

There’s a practical money argument too. Poe lets you try premium models without opening an account or subscription with each vendor, which makes it a sensible way to work out which model you actually prefer before committing money anywhere.

How the points system works

This is the part to understand before installing, because it shapes the entire experience. Poe doesn’t simply count messages; it charges compute points. Free accounts receive a recurring daily allowance, and each message deducts points according to the chosen model’s computational cost. Lightweight, optimised models cost little. Top-tier reasoning models and long-context versions cost far more per message, so extended sessions with them can use up a free day’s allowance quickly.

Poe also sells a subscription that comes with a much larger points allowance, and that is the real monetization model: Poe is free to try, but sustained use of the strongest models is a paid product. The upside of points is a kind of transparency — each bot shows its point cost, so you can pick a cheaper model for routine questions and save the expensive ones for hard problems. The downside is that it asks you to keep an eye on your budget while you work, rather than simply chatting.

The habit that makes Poe work is routing: send everyday tasks such as rewording an email to cheaper models, and reserve premium reasoning engines for problems that need them. Defaulting to the most powerful model for every message is the fastest way to exhaust the allowance.

Custom bots and the bot directory

Poe’s second strength is how approachable it makes custom bots. You write instructions, define a role, and optionally upload reference files the bot draws on when answering — a small knowledge base, in effect — without touching an API key or hosting anything yourself. Bots can stay private or be published to Poe’s public directory.

This is where educators and hobbyist developers get the most from the app. A teacher can set up a tutoring bot tuned to a course; a developer can build a coding assistant that follows a preferred style. Users often mention having a working bot within minutes, and that low barrier is one of the app’s most valued features.

The public directory is more of a mixed picture. Because anyone can publish, quality varies, and finding a well-built community bot can take some browsing. Before relying on one, read its description and check its listed point cost and the model it runs on, since those shape both the answers and what each message costs you.

Files, images, and multimodal work

Poe isn’t text-only. You can upload documents, photos, diagrams, or screenshots into chats with models that support them, and ask for text extraction, summaries, or analysis. Image-generation models sit in the same app, so you can draft a description with a language model and then generate artwork from it in the same workspace. For people whose work mixes reading PDFs, analysing screenshots, and producing quick visuals, keeping all of that under one history is a real convenience.

The caveat is that capability depends on the model you’ve chosen. Not every bot accepts every kind of input, and larger documents that need long-context models carry a higher point cost.

Where it frustrates

Points depletion is the main recurring complaint. Users running extended debugging sessions or multi-step analysis on the strongest models report burning through their reserves faster than they expected. The system is working as designed, but the design means the free tier is best suited to lighter models, and serious daily use of premium reasoning engines realistically needs a subscription.

Speed is the second issue. Because Poe routes each prompt to the model provider and back, responses can arrive a little slower than in a first-party app, and some users report occasional slowdowns during busy periods. When an upstream provider has an outage, the matching bots on Poe are affected as well; an aggregator depends on the services behind it. The mitigating factor is that a model from a different provider is usually a tap away, which helps when one service is having problems.

Poe also stays inside its own window, without the OS-level features of native assistants such as screen reading or system-assistant duty. If you want AI woven into Android itself, Gemini is designed for that role.

Finally, consider the data path. Your prompts pass through Poe and on to the provider that runs the model you selected. That’s inherent to how an aggregator works, and it’s worth reading the privacy terms before uploading sensitive work documents or anything covered by an employer’s data policy.

What users keep saying

The praise is steady: users value having Claude, GPT, and open-source models side by side without paying for each separately, and educators single out the bot builder as quick and useful. The recurring complaints are narrower and centre on cost and speed: how fast premium models consume points, and occasional slowdowns at peak times.

How it compares to alternatives

ChatGPT, Claude, and Gemini. Each first-party app usually offers the fullest experience for its own model, including provider-specific extras such as their own voice features and, for Gemini, deeper Android integration. If you’ve already settled on one model, its own app is usually the better choice. Poe’s advantage is breadth: it suits people who haven’t settled, or don’t want to.

Perplexity. Perplexity also lets subscribers choose among several models, but it’s built around web search and cited answers. If sourced research is your main use, Perplexity fits more naturally; if you want open-ended chat, custom bots, and a wider model catalogue, Poe covers more ground.

A note on recency and scale

Poe has been on Android since May 2023, has passed 10 million downloads, and carries more than 450,000 Play Store ratings. Its listing was last updated on August 27, 2026, and the model lineup shifts often as providers release new versions. That pace is part of the appeal: Poe tends to add notable new models quickly, so you can try them without new sign-ups.

Who it’s not for

If you use one AI model for hours every day, its own app will usually offer more for that model. Free-tier users planning long coding sessions on top reasoning models will likely find the daily allowance falls short. Poe isn’t designed to be a system-level phone assistant. And if your workplace restricts third-party services, check that policy before uploading documents.

The verdict

For comparison-minded users, Poe offers what a single-provider app can’t: a second opinion from another company’s model, one tap away. The bot builder is quick to learn, sync keeps work in one place, and the free allowance lets you sample premium models before paying for anything. Go in knowing that the points system rewards thoughtful model choice and that heavy daily use of the strongest engines is a paid proposition. For people who want breadth over depth, it’s an easy app to recommend.

How We Evaluate

We assess every app against the same questions: what problem it solves, how reliably it solves it, what it costs in practice, and who it genuinely suits. This review draws on the app's Play Store listing and update history, its documented feature set and points-based pricing model, recurring themes in Google Play reviews and community discussions, and Poe's broader public reputation among AI chat apps. Model availability and point costs change often, so specifics reflect the listing at the time of review.

Pros & Cons

Pros
  • Aggregates leading foundational models from OpenAI, Anthropic, Google, and Meta into a unified interface.

  • Simplifies the development and deployment of custom system-prompted bots and knowledge-base assistants.

  • Uses a flexible compute-point allocation system that permits evaluation of premium models without separate vendor accounts.

  • Synchronizes chat histories, custom bots, and account preferences across Android, iOS, and desktop web interfaces.

  • Integrates multimodal text reasoning, visual analysis, and generative image tools within a unified chat window.

  • Facilitates direct model benchmarking by allowing identical prompts to run across distinct AI architectures.

✕Cons
  • ✕

    Queries directed at top-tier reasoning engines can rapidly deplete daily compute points.

  • ✕

    Upstream outages across third-party foundational provider APIs can lead to intermittent service downtime.

  • ✕

    Lacks native OS-level deep assistance triggers and screen-reading integrations found in platform-native assistants.

  • ✕

    High computational loads across upstream networks can introduce response latency compared to direct API calls.

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FAQs

How does Poe integrate models from different competing AI companies?

Poe operates as an API-level aggregator. The platform maintains enterprise-tier infrastructure integrations with model developers, routing user prompts to the designated engine and returning the output within Poe's unified interface.

What is the purpose of Poe's compute-point system?

The compute-point system normalizes token and server costs across different foundation models. Rather than billing distinct token fees for each model, the app assigns point weights per query based on the model's computational footprint.

Can users build and share their own custom AI bots?

Yes. Users can define custom instructions, system roles, and uploaded reference files to build specialized bots. These configurations can remain private or be published to the broader community directory.

Does Poe support image analysis and multimodal inputs?

Yes. Users can upload documents, photographic assets, diagrams, or screenshots directly into compatible multimodal model chats for text extraction, analysis, and reasoning.

Are conversations conducted in Poe accessible on desktop computers?

Yes. Poe uses a unified profile architecture that synchronizes all chat histories, custom bots, active threads, and compute allocations across web browsers and mobile apps.

Hot Reviews

Summarized from Google Play reviews and community discussions.

Unified Multi-Model Aggregation

Users consistently praise the platform's multi-model architecture, which allows them to compare responses from Claude, GPT, and open-source models without maintaining individual paid subscriptions across multiple vendors.

Point Depletion Velocity on Complex Reasoning Models

A recurring criticism focuses on how quickly compute allocations are exhausted when querying top-tier reasoning or long-context models. Users note that running extensive code debugging or multi-step analysis can deplete point reserves rapidly.

Accessible Custom Bot Virtualization

Technologists and educators value the simplified custom bot creation workflow. The ability to deploy a customized tutoring or coding assistant in minutes—without managing developer keys or personal server hosting—remains a major positive.

Upstream API Latency Fluctuations

Reviews occasionally point out latency spikes during peak usage periods. Users observe that secondary aggregation routing can introduce slight response delays compared to first-party API connections.