Bigjpg vs New API
Side-by-side comparison · Updated October 2026
| Description | Bigjpg enlarges existing artwork, illustrations and photographs with AI reconstruction. It can smooth noise and redraw edges, but cannot guarantee that reconstructed details match the original scene. Check faces, linework, lettering and product details at the final viewing size. It is an image upscaler, not a text-to-image generator. Free allows 20 pictures per month, up to 4x enlargement and a 5MB upload. Basic costs $6 for two months with 500 pictures per month; Standard costs $12 for six months with 1,000 per month; Premium costs $22 for twelve months with 2,000 per month. All three paid packages allow up to 16x enlargement and 50MB files, with priority processing, parallel jobs and batch mode. Package duration and monthly image allowance are separate. Offline processing is available with an account, including Free. If you submit without logging in, keep the browser open while processing. The official API is available to paid members after login; check its account-specific limits before building an automated workflow. Compare VanceAI for an online credit-based workflow or a separate Windows application. The June 23, 2026 terms name Guangzhou Datu Technology Co., Ltd. as the operator and leave ownership of uploaded images with the user. You must have the rights needed to process them. The privacy policy says uploads are not used to train models and are removed from active systems within 24 hours after processing on Free, or 72 hours on Premium. It also describes cloud storage and content moderation, so this is a cloud service rather than local-only processing. Save results before the retention window ends. | New API is a self-hosted AI gateway and model-management project maintained in the QuantumNous repository. It brings provider channels, access tokens, model restrictions, usage statistics and cost accounting into one interface. Teams supply their own authorized model-provider access and operate the gateway in their chosen environment. The gateway supports several API formats, including OpenAI-compatible requests, Claude Messages and Google Gemini. Compatibility has boundaries: the README marks Gemini-to-OpenAI conversion as text-only without function calling, and OpenAI-compatible to Responses conversion as in development. Test the exact endpoints, streaming behavior and tool calls your application uses before switching traffic. Routing features include weighted channel selection, automatic retry after failures and user-level model rate limits. The dashboard supports request-based, usage-based and cache-hit cost accounting, with token grouping and model-access controls. These controls can help organize usage, but retries and a common API format do not guarantee uninterrupted service or identical behavior across providers. The current repository license is AGPLv3. Docker Compose is the recommended quick-start path in the README, which also documents Docker commands with SQLite or MySQL. Running the software still involves infrastructure, operations and upstream model charges. Review the current license, secure your deployment and validate accounting against provider bills. Compare LiteLLM if you also want a Python SDK or a documented gateway for MCP servers and agents. |
| Category | Image Improvement | Developer Tools |
| Rating | No reviews | No reviews |
| Pricing | Freemium | Open Source |
| Starting Price | Free | N/A |
| Plans |
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| Use Cases |
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| Tags | image upscalinganime upscalingphoto enlargementillustrationbatch processing | AI gatewayLLM routingmodel managementrate limitingusage accounting |
| Features | ||
| AI reconstruction for photos and illustrations | ||
| Free 4x enlargement and 20 pictures/month | ||
| Paid 16x enlargement and 50MB uploads | ||
| Paid parallel processing and batch mode | ||
| Account-based offline processing, including Free | ||
| Paid-member API access | ||
| Published image-retention and model-training policies | ||
| Self-hosted AI gateway and model management | ||
| Provider channels, token groups and model restrictions | ||
| OpenAI-compatible, Claude Messages and Gemini format support | ||
| Documented limits on protocol conversion | ||
| Weighted channel selection and failure retries | ||
| User-level model rate limiting | ||
| Request, usage and cache-hit cost accounting | ||
| Docker Compose deployment documentation | ||
| View Bigjpg | View New API | |
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