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.
Make metrics answer a business question.
Connect request lifecycles, alert actions, and recovery records without inventing performance guarantees.
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
Application-side observation methods. Choose thresholds from your workload and operational goals; these articles contain no measured ranking.
Observing Multimodal AI Workflows Without Logging Private Content
When text, images, or audio pass through one application request, a final error message rarely identifies the failing stage. Use application-side traces and privacy-safe checks to locate it.
8 min readTrace an API migration without losing request context
Keep task boundaries, application identifiers and state evidence consistent when comparing an API migration, including interruptions and asynchronous callbacks.
8 min readMeasure the complete lifecycle of an AI request
Separate queue time, first useful content, and validated completion instead of relying on one duration.
6 min readWrite alerts an on-call engineer can act on
Connect business impact, observation windows, and runbooks while controlling notification noise.
6 min readReconcile interrupted jobs before retrying
Use explicit task states to separate completion, failure, and uncertainty without duplicating effects.
6 min read