Bring model access, usage and costs into one workspace.
NexoToken is an AI API relay platform for developers, providing multi-model access, account credits and usage records. Choose a model for your task, validate a real request, then expand your usage.
Anthropic · DeepSeek · Doubao · Google · MiniMax · Moonshot · OpenAI · Qwen · Zhipu · xAI
Entry-model price examples
Platform credits / million tokens
| Model ID | Input | Output | Cached input |
|---|---|---|---|
claude-haiku-4-5-20251001 | 0.25 | 1.25 | 0.025 |
deepseek-v4.1-flash | 0.45 | 1.8 | 0.045 |
gemini-3.1-flash-lite-preview | 0.15 | 0.9 | — |
minimax-m3.1-flash | 0.3 | 1.2 | 0.03 |
kimi-k2.5 | 1.2 | 6.3 | 0.12 |
gpt-6-luna | 0.07 | 0.35 | 0.007 |
qwen3.8-flash | 0.24 | 0.81 | 0.03 |
glm-5.3-flash | 0.24 | 0.84 | 0.024 |
grok-4.5 | 0.5 | 1.5 | 0.125 |
Price snapshot checked: · Pricing & billing ↗
Platform credits are an account balance unit, not US dollar cash. These are complete public offer examples, not every group or discount. Current availability and charges follow the live platform catalog and your usage record.
This snapshot is over 48 hours old. Check live prices before budgeting.
From a first request to an integration you can maintain.
Validate protocols, streaming, and tool behavior with explicit acceptance criteria.
First-request checklist
Turn a working request into a repeatable check.
{
"model": "YOUR_MODEL_ID",
"messages": [
{ "role": "user", "content": "Hello" }
]
}Ask better questions before you connect.
Separate input, output and cache.
Compare the same workload using the same units.
A model label is not a test result.
Validate images, tools and context separately.
Read the sample, not just the percentage.
Keep the observation window and sample count visible.
Field notes
For developers integrating APIs: begin with small, non-sensitive samples before expanding context, concurrency, or application permissions.
Production Observability for AI API Integrations
Make an AI API integration diagnosable by defining request configuration, parsing responses, handling streams, and bounding error handling; verify actual behavior with your own run records.
8 min readIntegrate streaming into an existing app: completion and failure checks
A practical integration checklist for request boundaries, stream completion, failure recovery and release checks in an existing application.
8 min readMake your first API request reproducible
Check the protocol, address, and model ID, then validate a short request before adding complexity.
5 min readTest streaming and tool calls separately
Validate the event lifecycle, then check tool arguments, result handling, and execution limits.
6 min readKeep a capability checklist for each model configuration
Separate task quality, protocol behavior, and operating limits, and keep unknowns visible.
5 min read