Amazing AI vs BerriAI/litellm - GitHub
Side-by-side comparison · Updated October 2026
| Description | Amazing AI is Sindre Sorhus's free text-to-image app for compatible Apple devices. It runs Stable Diffusion 1.5 locally and is designed around a straightforward prompt-to-image workflow. It is useful for exploring visual ideas without buying cloud generation credits, especially when you want a native app with fewer model and editing choices. It is a fixed-model generator: choose a different workflow if importing LoRAs, editing an existing photo or generating video is central to your project. Describe the subject, composition and visual style in a detailed prompt, then review the generated image. To exclude unwanted elements, the developer documents adding a single ## separator followed by a negative prompt. On macOS you can preview thumbnails, move between images with arrow keys, save with Space and copy with Command+C. Saved images include prompt and generation metadata, which can help organize experiments and reproduce useful settings. The developer also lists batch generation for different prompts, Shortcuts support and automatic upscaling. These are workflow features, not a promise that every output is ready for commercial use. Compatibility is a practical decision point. The current App Store listing requires macOS 26 or later for Mac, and the developer specifies Apple silicon rather than Intel. The iPhone listing requires iOS 26 and an A17 Pro chip or later; the iPad listing requires iPadOS 26 and an M-series or A17 Pro chip. Check the device list in your local App Store before downloading. The model also uses substantial storage and memory, and the first generation may take longer because of model validation. We have not tested speed, battery use or output quality on specific hardware. Amazing AI is free without ads. The developer intentionally does not support custom models, inpainting or outpainting, and the FAQ says the current underlying library produces square images. Draw Things is a relevant alternative when you need imported models, local LoRA training, image-to-image editing or video; Amazing AI's simpler setup can suit people who want to concentrate on text prompts. The developer offers older macOS downloads and a non-App Store version, but says the latter does not receive automatic updates. Use the official download page to check the version and OS requirements. Local generation does not mean that the app never communicates externally. Its privacy statement says it collects no personal information and sends anonymous crash reports to Sentry. Review that distinction before using it in a sensitive workflow. The developer permits commercial and non-commercial use of generated images subject to the Creative ML OpenRAIL-M usage restrictions. That permission does not remove obligations concerning source material, recognizable people, trademarks or other third-party rights. The US App Store listing is rated 18+. Review the final image for artifacts and suitability before incorporating it into a design, presentation or publication. | LiteLLM is an AI gateway and Python SDK from Berrie AI Incorporated, published in the BerriAI GitHub repository. The SDK provides a common interface for model calls inside Python applications. The proxy gateway centralizes access for a team, with virtual keys, model routing, spend tracking, budgets and an administration interface. The official documentation lists support for more than 100 model providers. Supported endpoints and features vary by integration, so verify your model’s streaming, tool-calling, image, audio or embedding requirements. The router supports retries, fallbacks and load balancing; observability integrations can send request data to tools such as Langfuse, LangSmith and OpenTelemetry. LiteLLM also provides an MCP gateway. It can connect upstream servers using Streamable HTTP, SSE or stdio, expose tools through a fixed gateway endpoint, and scope access by key, team or organization. This requires configuring the upstream servers and authentication; the gateway does not automatically grant access to third-party tools. Agent-to-agent integrations are documented separately. The open-source offering has no software license fee for self-hosting. Code outside the enterprise directory is MIT-licensed, while enterprise code has separate terms. Enterprise pricing is quoted by annual gateway request capacity, deployment architecture and support needs, rather than a per-token license charge. Model-provider charges and infrastructure costs still apply. Enterprise adds controls and support such as SSO, SCIM, audit logs and service-level agreements. Compare New API for another self-hosted gateway with provider-channel management and usage accounting. Evaluate a representative workload, inspect request logging and secret handling, test budget and failure behavior, and decide whether SDK integration or a shared gateway best fits your application. |
| Category | Image Generation | Developer Tools |
| Rating | No reviews | No reviews |
| Pricing | Free | Open Source |
| Starting Price | Free | N/A |
| Plans |
| — |
| Use Cases |
|
|
| Tags | local AItext-to-imageStable Diffusion 1.5Apple siliconnegative prompts | AI gatewayPython SDKLLM routingMCP gatewayvirtual keys |
| Features | ||
| Local Stable Diffusion 1.5 image generation | ||
| Free access without ads | ||
| Negative prompt syntax using ## | ||
| Batch generation of different prompts | ||
| Shortcuts support and automatic upscaling | ||
| macOS keyboard controls and saved-image metadata | ||
| Fixed model and square-image workflow | ||
| Python SDK for direct application integration | ||
| Shared AI proxy gateway and administration UI | ||
| More than 100 documented model-provider integrations | ||
| Virtual keys, users, teams, budgets and rate limits | ||
| Spend tracking and observability integrations | ||
| Router retries, fallbacks and load balancing | ||
| MCP gateway for Streamable HTTP, SSE and stdio upstreams | ||
| Key, team and organization MCP permissions | ||
| Separate enterprise identity, audit and support features | ||
| View Amazing AI | View BerriAI/litellm - GitHub | |
Modify This Comparison
Also Compare
Explore more head-to-head comparisons with Amazing AI and BerriAI/litellm - GitHub.