D1V vs LM Pocket
Price, ratings, monetisation and update history for both apps, side by side — with what reviewers say about each.
D1V
This AI-powered mobile workspace allows developers and product teams to manage projects from idea to deployment. It integrates with GitHub, enables AI collaboration within project context, and provides visibility into code, files, and deployments.
- AI-native mobile workspace
- GitHub repository import
- AI collaboration in project context
- Inspect code and files
- Track deployments
- Manage account activity
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D1V is an AI-native mobile workspace for developers, founders, and modern product teams. It is not just an AI chat app and not just a notification companion. With D1V, you can create projects on mobile, import GitHub repositories, continue AI collaboration inside real project context, and inspect code, files, deployments, usage, and account activity in one place. D1V is built around workflow, not just chat. From idea to project, code, deployment, and release, the entire flow stays connected. You do not lose momentum when you step away from your desk. D1V helps you keep real product work moving from your phone. Why users stay with D1V: • Workflow first From idea to project, code, deployment, and operations, the flow stays connected. • Useful away from desktop You are not limited to reading updates. You can keep projects moving. • Built around real projects GitHub import, project context, AI collaboration, file access, and deployment visibility live in one product. What you can do with D1V: • Create a new AI project from a prompt • Import a GitHub repository or ZIP project • Continue AI collaboration in project context • Inspect project files, code, and structure • Track preview and production deployments • Review usage, orders, and account activity • Browse docs, community posts, and workflow references Who it is for: • Founders moving products forward faster • Developers who need project visibility on the go • Product teams managing projects and deployments from mobile • AI-native teams building with faster iteration loops If you want AI inside a real product workflow instead of a standalone chat window, D1V is built for that.
LM Pocket
Run open-source AI models directly on your device without cloud reliance. Discover, download, and chat with thousands of GGUF models privately. Offers a local API server and advanced management tools for power users.
- Run open-source AI models locally
- Discover and download GGUF models
- Private, on-device conversations
- OpenAI-compatible local API server
- Manage model library and performance
- GPU acceleration for fast inference
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Discover, download, and run open-source AI models directly on your device. No cloud. No subscription. No data leaves your device. LM Pocket brings the power of local AI models to your device. Browse thousands of GGUF models on Hugging Face, download them over WiFi, and chat with them entirely on-device. COMPLETELY PRIVATE Every conversation stays on your device. No server, no API key, no account required. Your prompts and responses never leave the device. DISCOVER MODELS Browse Hugging Face Hub for quantized GGUF models. Filter by size, quantization level, and popularity. See compatibility badges that tell you which models will run well on your device before downloading. CHAT WITH AI Stream token-by-token responses with full Markdown rendering. Manage multiple conversations. Adjust temperature, top-p, top-k, context length, and more. Supports ChatML, Llama, Mistral, Phi, Gemma, and other prompt formats automatically. LOCAL API SERVER Run an OpenAI-compatible HTTP server on your device. Expose /v1/chat/completions, /v1/models, and /v1/embeddings endpoints on your local network. Connect any app that supports the OpenAI API format. MANAGE YOUR LIBRARY Track installed models with storage usage. Import GGUF files from the Files app. Load and unload models with one tap. Monitor real-time performance: tokens per second, memory usage, and thermal state. BUILT FOR POWER USERS - GPU acceleration for fast inference - Background downloads with pause and resume - Hardware-aware model recommendations - Chat template auto-detection - Conversation export as JSON or Markdown - JSON mode with grammar-constrained output - Embeddings generation 100% FREE No subscriptions, no in-app purchases, no ads. Open-source AI should be accessible to everyone. SUPPORTED MODELS Run any GGUF-quantized model: Llama, Mistral, Phi, Gemma, CodeLlama, DeepSeek, Qwen, and thousands more from Hugging Face Hub. Model performance depends on device RAM and model size. Terms of Service: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/
Screenshots
Verdict
The clearest difference is price: LM Pocket at Free against D1V's $49.99. LM Pocket also leads on update cadence (every 3 days vs every 2 months). D1V's advantage is device support (4 vs 1) and iOS requirement (15.0 vs 26.0). On ads, in-app purchases and monetization model 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
LM Pocket is free to download; D1V costs $49.99 up front. Neither carries in-app purchases, so what you see is what you pay.
D1V ships an update every 2 months, LM Pocket every 3 days. The most recent releases landed on September 20, 2026 and September 25, 2026 respectively.
| Parameter | D1V | LM Pocket |
|---|---|---|
| Price | $49.99 | Free — better |
| Rating | — | 5.0 (1 ratings) — better |
| Positive reviews | 100.0% of reviews | — |
| Number of ratings | — | 1 — better |
| Update frequency | Every 2 months | Every 3 days — better |
| Ads | No | No |
| In-app purchases | No | No |
| Monetization | Free | Free |
| Devices | iPhone, iPad, iPod, Mac — better | iPhone |
| Requires iOS | 15.0 — better | 26.0 |
| Further details — not scored | ||
| Size | 100 MB | 19 MB |
| Age rating | 4+ | 4+ |
| Developer | HASH CLOUD LIMITED | Teo Bouancheau |
Customer experience
D1V
LM Pocket
In-app purchases
D1V
No in-app purchases
LM Pocket
No in-app purchases





