DeepCode vs On Device
Price, ratings, monetisation and update history for both apps, side by side — with what reviewers say about each.
DeepCode
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DeepCode is a minimal, developer-first AI chat app built for one purpose: helping you write better code, faster. How it works 1. Enter your OpenAI-compatible API key and base URL. 2. Pick your model — GPT-4o, GPT-4o Mini, or any custom model. 3. Start a chat. Ask anything: explain a function, debug an error, refactor a block, or brainstorm an architecture. Built for developers 1. Code-first formatting — AI responses render with syntax-highlighted code blocks you can copy in one tap. 2. Session management — Keep multiple conversations organized. Jump between projects without losing context. 3. Bring your own API — Connect to OpenAI, Azure, Anthropic, Gemini, or any custom endpoint. You control the provider, the model, and the cost. 4. No subscriptions, no tracking — We don't collect your code, your conversations, or your API keys. Everything stays on your device. 5. Dark mode by default — Easy on the eyes during late-night debugging sessions. Perfect for 1. Quick code explanations on the go 2. Debugging when you're away from your IDE 3. Learning new languages and frameworks 4. Brainstorming architecture and design patterns 5. Reviewing pull requests from your phone Supported providers OpenAI Azure OpenAI Google Gemini Anthropic Claude Any OpenAI-compatible API endpoint DeepCode is designed to stay out of your way. No onboarding tutorials, no feature bloat, no upsells. Just a clean chat interface that gets you answers you can actually use. ToS: https://www.ygtai.com/deepcode/terms.html Privacy Policy: https://www.ygtai.com/deepcode/privacy.html STAY CONNECTED Email: callus@ygtai.com
On Device
This app provides a local AI workbench for your iPhone, running open-source language and vision models entirely on-device. Features include live camera captioning, hands-free voice conversation, and code assistance with various models. It prioritizes privacy with no servers, API keys, or telemetry.
- On-device LLM and VLM execution
- Live camera captioning
- Hands-free voice conversation
- Code assistant with multiple models
- Document scanner and live OCR
- Model benchmarking and A/B comparison
- Mac pairing for inference server
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On Device LLM is a local-first AI workbench for your iPhone. Open-source language and vision models run entirely on-device via Apple's MLX framework — no servers, no API keys, no telemetry, no accounts. LIVE CAMERA CAPTION Point your camera at anything. SmolVLM describes the scene every few seconds, streaming the caption right onto the viewfinder. Tune the refresh interval from 500ms to 30s. Tap the refresh icon for an on-demand caption between cycles. VOICE CONVERSATION Hands-free chat with an on-device LLM. Industry-standard voice activity detection ignores TV chatter and background noise; speaks back through the same audio session it's listening on — no clipped first words, no delayed replies. CODE ASSISTANT Pick from Qwen 2.5 Coder, Llama 3.2, Phi-3.5, Gemma 2, Qwen3 and dozens of MLX-converted models on HuggingFace. The app auto-selects a model that fits your device's RAM (1.5B on older iPhones, up to 7B on Pro Max). Streamed token-by-token output, code-block syntax highlighting, conversation export to Markdown. POWER TOOLS • Document scanner — capture multi-page code via the native four-corner doc cam • Live OCR — text on a screen, sign, or whiteboard recognized in real time • A/B compare — run two models side-by-side and watch the speed/quality tradeoff • Benchmark — measure tokens per second, time to first token, peak memory, thermal impact • Macros — chain prompts together (lint → refactor → test) • Snippets — save reusable prompt templates • Persona memory — different facts remembered per persona • Mac Bridge — pair your Mac, use the iPhone as an MLX inference server PRIVACY YOU CAN VERIFY • Every model runs on the device — your prompts never leave the phone • A network-activity indicator surfaces every outbound request (only model downloads) • Conversations stored with at-rest encryption • One-tap "wipe all on-device data" in Settings • No analytics SDKs, no sign-up, no account required OPTIMIZED FOR YOUR DEVICE • First-launch device-tier auto-pick for both the chat model and the camera VLM • SmolVLM 2.2B (bf16) on Pro Max; SmolVLM 4-bit on entry-tier iPhones • Automatic fallback chain when a model mirror is unreachable • Thermal awareness — clamps response length only at .critical (matches peer on-device apps) • Cancels in-flight Metal work when the app backgrounds so iOS won't kill it REQUIREMENTS • iOS 18.0 or later • Recommended: iPhone 12 or newer • Wi-Fi recommended for the initial model download (≈1.5 GB minimum) Open source models. Open standards. None of your data on someone else's server.
Screenshots
Verdict
The clearest difference is update cadence: On Device at every 3 days against DeepCode's every 6 weeks. DeepCode's advantage is iOS requirement (15.0 vs 18.0). On price, ads, in-app purchases and device support there is nothing between them.
Scored on Price · Rating · Positive reviews · Number of ratings · Update frequency · Ads · In-app purchases · Monetization · Best chart rank · Devices · Requires iOS
Both are free to download. Neither carries in-app purchases, so what you see is what you pay.
DeepCode ships an update every 6 weeks, On Device every 3 days. The most recent releases landed on September 24, 2026 and October 1, 2026 respectively.
| Parameter | DeepCode | On Device |
|---|---|---|
| Price | Free | Free |
| Rating | — | 5.0 (1 ratings) — better |
| Number of ratings | — | 1 — better |
| Update frequency | Every 6 weeks | Every 3 days — better |
| Ads | No | No |
| In-app purchases | No | No |
| Monetization | — | Free |
| Devices | iPhone, iPod — better | iPhone |
| Requires iOS | 15.0 — better | 18.0 |
| Further details — not scored | ||
| Size | 33 MB | 642 MB |
| Age rating | 4+ | 17+ |
| Developer | Nanjing Yibuxilong Intelligent Technology Co., Ltd | MESUT CAN YAGCI |
In-app purchases
DeepCode
No in-app purchases
On Device
No in-app purchases





