qwen3-coder-next
Qwen3-Coder-Next is an open-weight model optimized for coding agents and local development workflows. Its sparse MoE design has 80B total parameters with only 3B activated per token.
Pricing: Input 24 credits / 1M tokens (≈ $0.12), Output 160 credits / 1M tokens (≈ $0.80).
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This demo page does not include the full memory features of the client. For the complete experience, please use the client or the CLI.
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Qwen3 Coder Next API on ModelFold
Qwen3-Coder-Next is an open-weight model optimized for coding agents and local development workflows. Its sparse MoE design has 80B total parameters with only 3B activated per token. Try Qwen3 Coder Next in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Qwen3 Coder Next API
Qwen3 Coder Next at a glance
Qwen3 Coder Next is a chat model from Qwen. It accepts text as input and returns text, with a context window of up to 262K tokens.
Use it without hosting anything
On ModelFold you call Qwen3 Coder Next with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Qwen3 Coder Next
Up to 262K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Function calling
Qwen3 Coder Next supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Qwen3 Coder Next on ModelFold
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Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Qwen3 Coder Next responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "qwen3-coder-next" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Qwen3 Coder Next
AI coding assistants
Generate, explain, debug and refactor code, review pull requests and work through multi-file changes in developer tools and IDE plugins.
Autonomous agents
Build agents that plan multi-step tasks, call your tools and APIs, and keep working toward a goal across long sessions.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Tool-calling backends
Route requests, call functions and chain API calls as the worker model inside larger agent systems.
Frequently Asked Questions
What is Qwen3 Coder Next?⌄
Qwen3-Coder-Next is an open-weight model optimized for coding agents and local development workflows. Its sparse MoE design has 80B total parameters with only 3B activated per token.
Which inputs does Qwen3 Coder Next support?⌄
Qwen3 Coder Next accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Qwen3 Coder Next?⌄
Up to 262K tokens, shared between your input and the model’s output.
Does Qwen3 Coder Next support function calling?⌄
Yes. Qwen3 Coder Next supports tools / function calling through the standard tools parameter of the chat completions API.
How is Qwen3 Coder Next billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Qwen3 Coder Next through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "qwen3-coder-next", using your ModelFold API key as the Bearer token.
| Input | 24 credits 1M tokens≈ $0.12 |
| Output | 160 credits 1M tokens≈ $0.80 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qwen3-coder-next","messages":[{"role":"user","content":"Hello"}]}'