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 assistant-generated changes reviewable.
Prepare useful context, challenge patches, and separate client configuration from code.
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
Engineering procedures for coding-assistant workflows. Verify specific client capabilities through its current documentation and your own tests.
Make AI coding workflows reviewable with context, tests and request traces
Organize context around the task, validate changes with repository checks, and use redacted request traces to investigate interruptions and usage questions.
8 min readA Practical AI-Assisted Codebase Migration Guide
Break a migration into reviewable steps: define repository context and acceptance criteria, inspect each patch, run the project’s checks, and record what actually happened.
8 min readA Practical Application Security Workflow for AI-Assisted Coding
Use AI assistance to examine a bounded repository change, then verify each security claim against the implementation and your own checks; treat generated findings as hypotheses, not proof.
8 min readPrepare a minimal repository context packet for a coding assistant
Define scope, dependencies, and acceptance commands so the assistant has less to guess.
6 min readReview a coding assistant’s patch against observable behavior
Inspect requirements, access boundaries, and regressions instead of judging code neatness alone.
6 min readKeep coding-assistant configuration separate from project code
Use an auditable checklist and minimal integration checks without committing credentials.
6 min read