OMessage vs LLM Bench
Price, ratings, monetisation and update history for both apps, side by side โ with what reviewers say about each.
OMessage
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OMessage is a simple and easy-to-use chat app designed for iOS, allowing you to interact with the your local AI service. With an iMessage-style interface, it provides a familiar and seamless chatting experience. Whether you need information, writing assistance, or just a casual chat, OMessage is here to help. Features: - Multimodal Model Support: Interact with different types of models, supporting text, image, and other input/output formats. - Reasoning Model Support: Engage in complex reasoning and analysis for intelligent conversations. - Message History Management: Easily view and manage your chat history to revisit past conversations. - Model Switching: Quickly switch between different models to meet your specific needs. Note: This app requires a self-hosted Ollama service to function. The icons and model names in the app are solely used to help users differentiate between different AI models and are not part of any commercial promotion.
LLM Bench
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LLM Bench is an iOS test bench for developers comparing on-device LLM behavior under real device constraints. Run the same prompt against selected local model targets and compare the evidence before choosing what belongs in your app. LLM Bench focuses on practical signals: load time, first output time, generation time, output speed, memory, thermal state, model readiness, raw output text, failures, and saved run history. Use LLM Bench to: - Compare GPU-capable local model runs on iPhone and iPad. - Run repeatable prompts against selected model targets. - Inspect model output, timing, memory, and thermal state in one place. - Save benchmark runs for later review. - Export benchmark evidence as CSV. - Add models from Hugging Face URLs, direct file URLs, or local imports when the artifact format is supported. LLM Bench is built for technical builders who want a compact measurement tool, not a leaderboard or generic AI chat app. It helps you answer the practical question: which local model behaves well enough on this device for this use case? The free tier includes one completed benchmark run. Subscribing unlocks ongoing benchmarking, saved comparison work, and export workflows. Premium is available as an auto-renewing subscription (monthly or yearly), or a one-time Lifetime purchase. Payment is charged to your Apple ID at purchase; subscriptions renew automatically unless canceled at least 24 hours before the period ends. Manage or cancel anytime in your App Store account settings. Privacy Policy: https://thedandano.github.io/michilotl-studios-docs/apps/llm-bench/privacy/ Terms of Use (EULA): https://www.apple.com/legal/internet-services/itunes/dev/stdeula/
Screenshots
Verdict
The clearest difference is in-app purchases: OMessage at none against LLM Bench's 3. OMessage also leads on update cadence (every 5 days vs every 4 months) and iOS requirement (16.0 vs 26.0). On price, ads and device support there is nothing between them.
Scored on Price ยท Rating ยท Positive reviews ยท Number of ratings ยท Update frequency ยท Ads ยท In-app purchases ยท Monetization ยท Best chart rank ยท Devices ยท Requires iOS
Both are free to download. LLM Bench sells 3 in-app purchases, starting at $2.99 per month. OMessage asks for nothing beyond the download.
OMessage ships an update every 5 days, LLM Bench every 4 months. The most recent releases landed on October 28, 2026 and October 29, 2026 respectively.
| Parameter | OMessage | LLM Bench |
|---|---|---|
| Price | Free | Free |
| Update frequency | Every 5 days โ better | Every 4 months |
| Ads | No | No |
| In-app purchases | No โ better | Yes |
| Devices | iPhone, iPad | iPhone, iPad |
| Requires iOS | 16.0 โ better | 26.0 |
| Further details โ not scored | ||
| Size | 12 MB | 92 MB |
| Age rating | 4+ | 4+ |
| Developer | ๅฏฐๅฎ ้ช | Dan Sedano |
In-app purchases
OMessage
No in-app purchases
LLM Bench
- Monthly Premium$2.991 Month
- Yearly Premium$29.991 Year
- Lifetime Premium$4.99









