Verify first, list later
For key models, we do not only check whether they answer. We also verify identity, capability, protocol behavior, and exact model matching.
Infinite Galaxy AI · Multi-model API entry pointUnleash infinite ideas
Unleash infinite ideas
Bring AI power
to everyone
For individuals and enterprises, with API access to mainstream AI models and a unified chat experience.
Use one API key for integration, or call models directly from the web without setup.
These top GitHub projects all recommend Infistar
From API proxying to AI creation — the heavier a team's model usage, the better it knows how to pick a dependable relay service
Why Infinite Galaxy AI: Understand the model, price, source, and route before you start
Many API platforms look different only in price. What really affects the experience is whether models are swapped, account pools are controllable, routes are stable, cache prices are real, and billing is understandable.
Group prices are shown directly
Input, output, cache read, and cache creation prices are shown separately, making pay-as-you-go costs easier to understand.
Pay as you go · unified balanceCache costs explained separately
Long context, codebases, and multi-turn tasks repeatedly read content, so cache pricing directly affects the real cost.
Self-built account pool and multi-route redundancy
In scenarios covered by the self-built account pool, the platform controls the supply source and reduces single-point risk through multi-route observation, exit, and replacement.
Owned source · multi-route fallbackModel Coverage: Mainstream models in one entry point
Covers mainstream models such as ChatGPT, Claude, Gemini, Grok, Qwen, and DeepSeek. Exact model coverage and pricing follow the real-time model marketplace.
OpenAI
Claude
Gemini
DeepSeek
Qwen
GLM
Hunyuan
Kimi
Midjourney
Volcengine
Wenxin
Grok
30+
More models
OpenAI
Claude
Gemini
DeepSeek
30+
More models
Verification: We turn "legitimate" into a checkable standard
Infinite Galaxy AI is not a few manually selected endpoints. It is continuously governed around self-built account-pool supply, model verification, pricing, cache behavior, redundant routes, and runtime observation.
Trusted model/capability
Call performance observation
Pricing and cache costs
Self-built account-pool supply capability
Issue detection and replacement
Where our self-built account pool covers the scenario, the platform controls the supply source. This does not mean every route will never fail, but failures become detectable, explainable, fixable, and replaceable.
Unified chat: Use every platform model without API integration
Users can choose models, upload files, and start conversations directly on the web. Advanced users can test models first, then connect the right ones to their own tools.
Frictionless model switching
Multi-model comparison
File and image input
Tools and coding capabilities
Unified chatChoose a model and start
Model readyText Q&AFile understandingCode assistance
Type a question, choose a model, then send
Pricing & Cache: Transparent billing: see model calls and cache costs clearly
Large-model cost is not limited to basic input and output. For long documents, code analysis, or multi-turn conversations, context cache fees are often overlooked, and this part can sometimes differ by up to 10x.
To keep every cost clear, we break billing into separate items: input and output prices, cache read and creation fees, official prices, and group discounts. You can see exactly how each type of usage is charged.
Pay as you goUnified balanceOne top-up for every available model
Sample model
Pay as you go50% of official price with 1M context, tool calling, image understanding, and file understanding, suitable for multimodal Q&A, data analysis, and content creation.
Sample groupTool callingFile understandingImage understanding1M context
Input price/M$3.0000
Output price/M$12.0000
Cache read/M$0.7500
Cache create/M$3.7500
Choosing a group: Choose groups by scenario without learning every technical detail first
Standard, Enterprise, Curated, and Brand groups serve different scenarios. Choose by task first, then check exact prices and supported models in the model marketplace.
Universal Standard
Start here for everyday use
Good for Q&A, writing, information organization, learning, and light code assistance, with friendlier pricing.
View supported modelsUniversal EnterpriseBuilt for teams and frequent tasks
Prioritizes model consistency, owned supply capacity, cache hits, business continuity, and runtime observability.
View enterprise groupsCurated Chinese modelsOne entry point for mainstream Chinese models
Covers model combinations such as Qwen, DeepSeek, Kimi, GLM, and MiniMax, suitable for Chinese tasks and batch processing.
View Chinese modelsBrand groupsChoose by model brand
For users who already know the model brands they want, with Standard, Enterprise, and Premium routes under each brand.
View brand modelsData Privacy & Security
Data Privacy and Security Commitment
We value every user's data privacy and information security. The platform processes data only within the scope necessary to provide services and maintain security, and reduces leakage and misuse risks through encrypted transmission, permission isolation, access auditing, and anomaly monitoring.
Data involved in content safety review is used only for necessary identification through lawful, compliant information-security review channels with appropriate safeguards, and is not used for unrelated purposes. We do not sell, rent, publicly disclose user data, or use it for unauthorized commercialization.
If suspected illegal activity, threats to national security or public interests, or infringement of others' lawful rights are found, we will retain necessary clues in accordance with law and cooperate with competent authorities.
Encrypted transmissionPermission isolationAccess auditingAnomaly monitoringCompliant review channelUnauthorized commercialization limits
FAQ: Clarify choices and risks first
I am new. Which one should I choose?
Start with Universal Standard. If you do not integrate APIs, try the unified chat first, confirm model quality, then connect your own tools.
Does the Standard group mean lower quality?
No. The Standard group is priced for everyday use, while still keeping checks for model authenticity, baseline availability, and transparent pricing.
Why does cache pricing matter?
Long documents, codebases, and multi-turn tasks repeatedly read context, so cache read prices and hit rates directly affect real cost.
How do you avoid fake models?
We judge by model identity, exact model matching, capability results, and protocol behavior. We do not treat "can answer" as proof of a real model.
Every simple call is backed by an end-to-end, always-on compute network
Behind the scenes, we handle countless account configurations, safety rules, and node maintenance. You only need to try models here, compare transparent quotes, and start with one click.
Start now