Five ways to put AI on a phone, three licence traps

This review compares one front only: what forms an AI agent takes on a phone, not which vendor's model scores highest. Framing is fixed at the top: everything is a representative comparison assembled from official pages, repository READMEs and public reporting rather than independent benchmarking in a common environment, and exact numbers follow each vendor's live interfaces. It also states its division of labor against three existing articles on the site, the desktop computer-use agent comparison, the agent harness comparison covering the scaffolding that wraps a model as a different layer, and the phone-harness open-source piece, and limits itself to the phone side. The five contenders are Alibaba's Qwen Intelligence, a B2B stack for OEMs; Apple Intelligence with Siri AI, a system-level self-contained loop; OmniBot, an Android-native on-device open-source agent; OpenGUI, an Android phone GUI agent framework; and MobileGym, a browser-hosted phone simulation and evaluation platform. MobileGym is called out as a different layer, an evaluation and simulation base rather than an assistant, and is not compared as a peer assistant. Three licence red lines get their own section: OmniBot's segmented dual licence of AGPL v3 plus commercial that bars use by any organization; OpenGUI's Business Source License 1.1, source-visible but not OSI open source, with an Additional Use Grant of None limiting it to non-production use and commercial licensing needed for production, converting to Apache 2.0 on the 2030-04-29 change date; and MobileGym's split licence with Apache-2.0 code but CC BY-NC 4.0 non-commercial data. All three report NOASSERTION or inaccurate licence fields through the GitHub API, so the conclusions come from the LICENSE files. Cost is explicitly declared not directly comparable: Qwen at about 2.41 dollars per thousand tasks by vendor statement, Apple not billed separately but limited to expensive models with an unpriced paid tier, and the open-source options free as software but requiring your own models and devices with possible paid commercial licensing, never converted into a single ranked figure. Apple's framing is layered by source: public launch information spanning the September 14, 2026 release with iOS 27, English-only beta, five more languages in October, 16 languages including Simplified and Traditional Chinese, mainland China outside the launch, initial unavailability in the EU on iOS, iPadOS and watchOS but availability on macOS and visionOS, and daily usage limits on server-backed features with neither quotas nor paid-tier pricing published; the vendor table's description of Apple marked as source-side framing; and the report on the China-market Qwen backbone marked as media framing and distinguished from Qwen Intelligence.

Published September 23, 202610 min read

Putting AI on a phone is at least five non-overlapping roads: a platform sold to handset makers, a first-party system assistant, an open-source app running locally, a cross-app automation framework, and a simulated phone in a browser. This piece does not rank model scores. It asks what forms a phone-side AI agent takes, and where the boundaries, openness, and licence red lines are.

This is a representative comparison: details come from official pages, repository READMEs, LICENSE texts, and public reporting, collected 2026-09-23, not an independent stress test under one identical setup. Official interfaces and docs are authoritative.

Three site articles are easy to confuse with this one. The Computer Use Agent comparison covers desktop agents (Claude, OpenAI, Mariner, cua, Agent-S, fara); this piece is phone-side only. The Agent Harness comparison covers model scaffolding (DSH, Claude Code, OpenCode, Codex), another layer. The phone-harness article covers an iPhone driven through a Mac harness, not re-dissected here.

Five offerings, five layers

#	Offering	Vendor	Form	Where it runs	Layer
1	Qwen Intelligence	Alibaba Tongyi Qianwen	Full-stack AI solution for handset makers (model + platform + scenarios)	Phone + backend / cloud	B2B foundation
2	Apple Intelligence / Siri AI	Apple	First-party system assistant (on-device model + cloud-side AFM)	Device + cloud	First-party closed loop
3	OmniBot	omnimind-ai (open source)	On-device AI agent running directly on Android	On the Android device	Open-source on-device app
4	OpenGUI	Core-Mate	Android phone GUI agent framework	Phone + local backend	Source-available framework
5	MobileGym	Purewhiter (academic)	Browser-hosted phone simulation and evaluation platform	Browser simulation	Evaluation / simulation substrate

The fifth row is the one most often misread: the first four are assistants or near-assistants, the fifth is not. MobileGym sits on a different layer: it does not play assistant, it measures the others. Pitting it against the first four is the common category error here.

The five, one by one

Alibaba Qwen Intelligence: a foundation sold to handset makers, not an app you download. A B2B full-stack offering that builds no hardware, selling handset makers "model + platform + scenario solutions"; it has landed with Honor. Three agents split the work: Mobile Planner for planning, 100-plus-step tasks, and dual-layer memory; Mobile-Use for cross-app operation on an "API first, GUI as fallback" path, with user confirmation for key decisions; Mobile Creative for images from colloquial requests.

Vendor-stated figures (vendor claims, not our re-test): 91.8% overall task accuracy; about USD 2.41 per thousand Planner calls; Mobile-Use 90% end-to-end success, 28.8% less time, 20% lower cost, 59.5 seconds per task; Creative's first image in 3 seconds; a security score 23 points above leading options. It opens four evaluation suites, but consumers only get Honor's shipped devices and a Qwen platform trial zone. Licence and pricing are undisclosed. Background: the Qwen Intelligence launch hotspot.

Apple Intelligence / Siri AI: a first-party closed loop with three hard constraints. Claims must be labelled by tier. Apple's public release information: launched 2026-09-14 with iOS 27 and its siblings, English only in Beta, with French, Japanese, Korean, Portuguese and Spanish in October; 16 languages including Simplified and Traditional Chinese. The regional red line matters most: mainland China is not in the first wave, pending Apple's completion of regulatory requirements, and the EU cannot use the features on iOS, iPadOS or watchOS initially, though macOS and visionOS can. Server-side features carry a daily usage limit with an undisclosed quota; a paid tier is coming with no announced price or date.

Two further framings must stay separate. Counterparty framing: the Qwen Intelligence table calls Apple "on-device in-house model, driven by Google Gemini". Press framing: a ZOL report on 2026-09-10 said Apple's initial release completed its in-country large-model filing in July 2026, supported by Alibaba's Qwen model. That is not Qwen Intelligence, the B2B foundation sold to handset makers.

OmniBot: an open-source on-device agent that truly runs on the Android phone. GitHub API snapshot, 2026-09-23: 2,007 stars, 144 forks, Dart, created 2026-03-18, last push the same day. It runs directly on the Android device (Kotlin plus Flutter, with a React + TypeScript WebUI). The surface is wide: Skills, an Alpine Linux environment, a browser, MCP, Android system tools, alarms, calendars, audio, memory, files, and a terminal. A Remote Codex bridge lets the phone use a signed-in computer's Codex via a QR code. The local service defaults to port 8899.

Unlike the site's phone-harness piece (iPhone via Mac harness), this is Android-native. Repo overview: OmniBot, the open-source on-device agent.

OpenGUI: an Android real-device GUI agent framework, source-available but not open source. GitHub API snapshot, 2026-09-23: 1,804 stars, 114 forks, TypeScript, created 2026-04-18, last push 2026-09-17. It lets an agent see, understand, and operate Android app interfaces on a real device. The shortest path is a DeepSeek Harness (DSH) plugin installed with one prompt to Codex; full-stack self-hosting is supported. It supports DSH 0.1.0-rc.7 through 0.1.1-rc.2 (default 0.1.1-rc.2), not 0.1.2-alpha.4; the macOS installer needs Node.js 22.19+.

The design is "plan before acting, summarise after execution": a supervisor keeps task state, the executor runs a screenshot-vision-action-callback loop, and a summariser closes with a structured result; planning and VLM execution can use different providers; Feishu, Telegram, Discord and REST dispatch are supported. Per the README: Android 11 (API 30) or newer, USB debugging and AccessibilityService permissions required; quality depends on model, app UI, network and task length; it is not an always-on assistant yet.

MobileGym: another layer, an evaluation and simulation substrate, not an assistant. Up front: it is not an AI assistant on a phone; it is the substrate used to quantify the others, not a same-kind comparison. Paper figures (arXiv 2605.26114, EMNLP 2026 main conference): 28 simulated apps, 416 parameterised task templates, deterministic sub-millisecond judges; 256 parallel instances on one server at roughly 400 MB of RAM each and about 3 seconds of cold start. Sim-to-Real: a GRPO run on Qwen3-VL-4B gains 42.8 points in simulation and keeps 95.1% of that on a real device, or 40.7 points on hardware. Paper and README figures, not our re-test. To set up an on-device agent yourself, see the phone-side agent setup SOP.

Dimension	Qwen Intelligence	Apple Intelligence	OmniBot	OpenGUI	MobileGym
Cross-app path	API first + GUI fallback	Deep system integration	System tools + Skills + MCP	AccessibilityService, GUI vision	N/A (evaluation substrate)
Authorisation and safety	Three-layer controls; user confirmation for key decisions	On-device processing + daily server-side limit	Use constrained by licence	USB debugging and accessibility permissions	Sandbox, rollback, deterministic judging
Openness	Customisable for vendors; four evaluation suites	Closed ecosystem, developer APIs only	Open source (AGPL v3, scoped)	Source-available (BSL 1.1, not OSI)	Code Apache-2.0, data CC BY-NC 4.0
Licence red line	Undisclosed; official statements govern	Not applicable	Commercial use needs a licence	Production/commercial use needs a licence	Data non-commercial, academic only
Cost basis	About USD 2.41 per thousand tasks (vendor)	Not billed separately; high-end devices only	Software free; BYO model and device	Software free; BYO model and device	Open source; BYO servers and compute

Three licence red lines

All three report NOASSERTION or an inaccurate value in the GitHub API licence field; conclusions below come from the LICENSE text itself.

Red line one: OmniBot uses a Segmented Dual Licence. Its LICENSE says the open-source side is GNU AGPL v3, free only for non-commercial use or personal, educational, or research purposes, and it explicitly "prohibits use by any organisation"; AGPL source obligations still apply. Commercial use, or avoiding AGPL's source-release obligation, needs a commercial licence signed with the maintainer. Even research by an organisation falls outside the free scope; calling it "AGPL open source" or "free for commercial use" is wrong.

Red line two: OpenGUI uses Business Source License 1.1 (BSL 1.1), source-visible but not OSI open source. You may use the source for non-production purposes, but production or commercial use, hosted services, and commercial integration need a licence from Core-Mate. For this version, Additional Use Grant: None (non-production only), and the Change Date is 2030-04-29, when it converts to Apache 2.0. In 2026 it is public source, not open source. The GitHub API reports NOASSERTION here.

Red line three: MobileGym splits code and data licences. Code (core source and mobilegym-rl/) is Apache License 2.0; data and content (mobilegym-data/, per-app data and assets, synthetic content, simulated UGC, icons) is CC BY-NC 4.0, non-commercial academic use only. The split is deliberate: code stays permissively reusable, content (including derived representations of third-party brands) stays research-scoped. Academic evaluation is fine; a commercial product crosses the line on the data side.

Cost: three billing logics, not directly comparable

Bases only; never one number.

Qwen Intelligence: about USD 2.41 per thousand Planner calls (vendor figure), a fraction of leading models; per-call pricing, rules unpublished.
Apple Intelligence: not billed separately but limited to high-end new devices; server-side features carry a daily usage limit and the paid tier has no announced price or date. Hardware-tied.
The open-source side (OmniBot, OpenGUI): software free, but you bring your own model API or compute, devices and backend; commercial use may add a licence fee. Self-funded infrastructure.
MobileGym: open source, but you bring your own servers and compute.

Four different bases; converting them into one number would be wrong.

Selection by scenario, and the verdict

Your need	Pick	Why
A vendor-customised foundation	Qwen Intelligence	A one-stop AI foundation for handset makers, customisable
A first-party system assistant	Apple Intelligence	Deep system integration, but bound by region and device
A controllable on-device open option	OmniBot	Runs directly on Android; commercial use must clear the licence first
A cross-app automation framework	OpenGUI	A real-device GUI framework, usable as a DSH plugin; production needs a commercial licence
Large-scale evaluation	MobileGym	Another layer: a simulation substrate that buys reproducible, quantified results

Three conclusions. First, these five are not pick-one-of-five; they are three non-overlapping tracks plus one evaluation layer: a foundation platform, device-side apps and frameworks, and the simulation substrate that quantifies them. Second, openness is tiered, not binary: Apple is closed, Qwen is vendor-customisable, OpenGUI is source-available but not open source, and OmniBot and MobileGym are open source with red lines. Treating "source-available" as "open source", or "open source" as "free for commercial use", are the two most common traps. Third, licence and cost must be read together: whether "free" includes commercial rights decides if it can enter production.

FAQ

Q1: Of these five, which is most worth using today? A1: It depends on region and device. Apple's option is limited because mainland China is not in the first wave; Qwen Intelligence only reaches consumers through Honor devices and a Qwen platform trial zone. What you can try today is OmniBot and OpenGUI, at the cost of your own hardware and licence constraints.

Q2: Why is MobileGym not counted as a phone assistant? A2: Because it is a browser-hosted simulation and evaluation platform, not an assistant that runs on a real device to do work for the user. It provides a programmable, rollback-capable, deterministically judged environment. It is the layer that measures assistants, not one of them.

Q3: OpenGUI calls itself "open source", so why can it not be used commercially? A3: Because it uses BSL 1.1, source-visible but not an OSI-approved open-source licence. Additional Use Grant: None grants non-production use only; production and commercial use need a separate commercial licence until the Change Date of 2030-04-29, when it becomes Apache 2.0. The LICENSE text governs, not the GitHub API's NOASSERTION field.

Q4: Is a self-hosted open-source option always cheaper? A4: No. OmniBot and OpenGUI are free as software, but you supply model APIs or compute, devices and backend, and commercial use may add a licence fee. Qwen is priced per call (vendor figure, about USD 2.41 per thousand tasks). Different bases should not be reduced to one number.

Q5: Are Apple Intelligence and the Qwen foundation a China-market iPhone may use the same thing? A5: No. The ZOL report of 2026-09-10 (press framing) said Apple's initial release completed its in-country large-model filing, supported by Alibaba's Qwen model: the foundation of an in-country system. Qwen Intelligence is the B2B full-stack offering Alibaba sells to handset makers. Both carry the name "Qwen", but they are not the same thing.

Sources

Official pages and READMEs: Qwen Intelligence official comparison table (counterparty framing), Apple Intelligence / Siri AI release information, omnimind-ai/OmniBot, Core-Mate/OpenGUI, Purewhiter/mobilegym
LICENSE texts: OmniBot's LICENSE (AGPL v3 plus commercial dual licence), OpenGUI's LICENSE (BSL 1.1, Change Date 2030-04-29), MobileGym's LICENSE and LICENSE-DATA (Apache-2.0 / CC BY-NC 4.0)
GitHub API snapshots (2026-09-23): OmniBot 2,007 stars; OpenGUI 1,804; MobileGym 798. All three licence fields read NOASSERTION or are inaccurate; the LICENSE text governs
Paper: MobileGym, arXiv 2605.26114, EMNLP 2026 main conference
Public reporting: ZOL, 2026-09-10 (press framing); Apple launch information relayed by Mac Observer, AI Insiders, ET Now and HandWiki

Collected 2026-09-23; star counts are same-day snapshots; features, licences, and prices follow the official sources. Related reading: Qwen Intelligence launch hotspot | OmniBot, the open-source on-device agent | Phone-side agent setup SOP | Agent Harness comparison | Computer Use Agent comparison

This article is AI-assisted and human-edited. Last updated: 2026-09-23

FAQ

Of these five, which is most worth using today?: It depends on region and device. Apple's option is limited because mainland China is not in the first wave; Qwen Intelligence only reaches consumers through Honor devices and a Qwen platform trial zone. What you can try today is OmniBot and OpenGUI, at the cost of your own hardware and licence constraints.
Why is MobileGym not counted as a phone assistant?: Because it is a browser-hosted simulation and evaluation platform, not an assistant that runs on a real device to do work for the user. It provides a programmable, rollback-capable, deterministically judged environment. It is the layer that measures assistants, not one of them.
OpenGUI calls itself "open source", so why can it not be used commercially?: Because it uses BSL 1.1, source-visible but not an OSI-approved open-source licence. `Additional Use Grant: None` grants non-production use only; production and commercial use need a separate commercial licence until the Change Date of 2030-04-29, when it becomes Apache 2.0. The LICENSE text governs, not the GitHub API's NOASSERTION field.
Is a self-hosted open-source option always cheaper?: No. OmniBot and OpenGUI are free as software, but you supply model APIs or compute, devices and backend, and commercial use may add a licence fee. Qwen is priced per call (vendor figure, about USD 2.41 per thousand tasks). Different bases should not be reduced to one number.
Are Apple Intelligence and the Qwen foundation a China-market iPhone may use the same thing?: No. The ZOL report of 2026-09-10 (press framing) said Apple's initial release completed its in-country large-model filing, supported by Alibaba's Qwen model: the foundation of an in-country system. Qwen Intelligence is the B2B full-stack offering Alibaba sells to handset makers. Both carry the name "Qwen", but they are not the same thing.

Field SOP

Put an agent on your phone: two routes, one red line

A hands-on SOP for putting a phone AI agent onto real hardware, offering two routes side by side. The first section decides whether it is worth doing at all: it fits a spare handset used to test whether a phone can genuinely run errands, and it does not fit a daily driver, an unattended long task, or anything involving payment, password changes, sending messages or account settings. Route A is OmniBot's on-device app form: install the APK from Releases, then configure AI capability, provider and scene models in settings, where Memory embedding strictly needs an embedding model and other scenes are best served by multimodal or vision models; the Alpine environment initializes on startup; sending a skills repository link to the assistant installs skills; scheduled tasks run subagent flows while alarms only remind; an optional Remote Codex bridge lets the phone scan a code to borrow a computer's Codex; and an optional WebUI takes an address and token from the in-app local service, defaulting to port 8899 with no trailing path. Development requires Flutter 3.47.2+, JDK 17+, Node.js 20.19+ or 22.12+ and pnpm 10.28.0. Route B is OpenGUI's framework form reached through DeepSeek Harness: the hard prerequisites are an Android 11 (API 30) or newer device or emulator plus USB debugging and accessibility permission; the shortest path is pasting the official install prompt to Codex, after which the installer verifies SHA-256, installs only the OpenGUI plugin and preserves unrelated plugins and settings; version discipline supports DSH 0.1.0-rc.7, 0.1.0-rc.8, 0.1.1-rc.1 and 0.1.1-rc.2 with new installs defaulting to 0.1.1-rc.2, does not support 0.1.2-alpha.4, and refuses a downgrade from a 0.1.1 RC to a 0.1.0 RC. Once a real device is connected, a single prompt verifies the setup. The safety section covers a spare device, least privilege, a hard rule of per-action human confirmation, trusted LAN only, tokens that never leave the machine, retained logs for audit, and short tasks before long ones, backed by a pre-flight checklist and a seven-row pitfall table. Licence boundaries get their own section: OmniBot requires a commercial licence for commercial use since AGPL v3 covers only non-commercial and personal, educational or research use, while OpenGUI is BSL 1.1 for non-production use only. The article also notes it does not overlap with the site's desktop computer-use build SOP, and invents no pricing or limits absent from the official docs, writing instead that the vendor governs.

Sep 23, 20269 min read

Hardcore Reviews

Who truly goes prompt to final cut? 5 AI video workspaces

This review looks at a single front, the workbench form factor: how far a tool pulls scripting, storyboarding, assets, generation, editing and post into one entry point, how open that entry is to agents and self-hosting, and its pricing units, explicitly not which one generates better images. Discipline is set at the top: every comparison is representative, based on official pages and source framing rather than independent benchmarking here, and exact numbers follow each official client and live site. Five contenders are covered: JianYing Hub (ByteDance, closed-source closed-loop workbench), LibTV 1.5 (LiblibAI, infinite canvas with a human-and-agent dual entry, a Skill repo ltv-labs/libtv-skills on GitHub), Jimeng AI (ByteDance JianYing team, generation-side full chain), OpenCreator (krillinai, Apache-2.0 open source, local-first, Codex CLI driven) and TapNow (Shenzhen Tianke Intelligent, node-based infinite canvas Tapflow). Each is placed across six stages, scripting, storyboard and assets, generation, assembly, refinement and batch, then openness gets its own section, and pricing sets two red lines: currencies are not directly comparable (LibTV in yuan per year, Jimeng in yuan per month, TapNow in USD recharged into Tapies, JianYing Hub unpublished) and credits are not money (conversion rates differ), so units are listed without any unified ranking. It closes with scenario-based picks and a clear division of labor against the site's existing generation-model comparison, open-source production tools comparison, API cost comparison and Shotcut review. A caveat is noted that TapNow's information is a 2025-11 snapshot and its agent support is a second-hand, contradictory claim without an official source.

Sep 22, 20269 min read

Hardcore Reviews

Hire no interpreter? 5 realtime translation engines compared

This review scopes itself to one front, realtime simultaneous interpretation and streaming speech translation, and sets three entry bars first: streaming input is mandatory, at least one party must publish a checkable engineering figure, and both cloud APIs and self-hosted open source must be covered. It lands on five options, three cloud and two self-hosted: Qwen3.8-LiveTranslate, the OpenAI GPT-4o Realtime API, kyutai-labs/hibiki, ictnlp/StreamSpeech (MIT, 1,291 stars, Python) and iFlytek's interpretation service. The discipline is stated at the top: latency figures are not directly comparable, so average lag, first-packet latency, end-to-end latency and unpublished numbers are never ranked against each other, and without a common baseline the article does not declare who is fastest. Each option is taken apart on deployment shape, language coverage, license boundaries and a same-day repository snapshot, surfacing how differently they are shaped, since the three closed cloud APIs cover more languages but send data off-premises and cannot be modified, while the two self-hosted projects can be changed and run locally but cover fewer pairs. It closes with scenario-based selection advice and a clear division of labor against three existing articles on cloud versus local cost, voice cloning tools and realtime voice model releases, so no two reviews overlap.

Sep 21, 20268 min read

Core conclusion

FAQ

Of these five, which is most worth using today?: It depends on region and device. Apple's option is limited because mainland China is not in the first wave; Qwen Intelligence only reaches consumers through Honor devices and a Qwen platform trial zone. What you can try today is OmniBot and OpenGUI, at the cost of your own hardware and licence constraints.
Why is MobileGym not counted as a phone assistant?: Because it is a browser-hosted simulation and evaluation platform, not an assistant that runs on a real device to do work for the user. It provides a programmable, rollback-capable, deterministically judged environment. It is the layer that measures assistants, not one of them.
OpenGUI calls itself "open source", so why can it not be used commercially?: Because it uses BSL 1.1, source-visible but not an OSI-approved open-source licence. `Additional Use Grant: None` grants non-production use only; production and commercial use need a separate commercial licence until the Change Date of 2030-04-29, when it becomes Apache 2.0. The LICENSE text governs, not the GitHub API's NOASSERTION field.
Is a self-hosted open-source option always cheaper?: No. OmniBot and OpenGUI are free as software, but you supply model APIs or compute, devices and backend, and commercial use may add a licence fee. Qwen is priced per call (vendor figure, about USD 2.41 per thousand tasks). Different bases should not be reduced to one number.
Are Apple Intelligence and the Qwen foundation a China-market iPhone may use the same thing?: No. The ZOL report of 2026-09-10 (press framing) said Apple's initial release completed its in-country large-model filing, supported by Alibaba's Qwen model: the foundation of an in-country system. Qwen Intelligence is the B2B full-stack offering Alibaba sells to handset makers. Both carry the name "Qwen", but they are not the same thing.