ling-3-1-flash
Ling 3.1 Flash is a hybrid reasoning Mixture-of-Experts model from inclusionAI, with 25B active parameters out of 560B total.
Pricing: Input 9 credits / 1M tokens (≈ $0.04), Output 27 credits / 1M tokens (≈ $0.14).
Prices updated
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Ling 3.1 Flash API on ModelFold
Ling 3.1 Flash is a hybrid reasoning Mixture-of-Experts model from inclusionAI, with 25B active parameters out of 560B total. Try Ling 3.1 Flash in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Ling 3.1 Flash API
Ling 3.1 Flash at a glance
Ling 3.1 Flash is a chat model from inclusionAI. It accepts text as input and returns text, with a context window of up to 1M tokens.
Use it without hosting anything
On ModelFold you call Ling 3.1 Flash 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 Ling 3.1 Flash
Up to 1M 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
Ling 3.1 Flash 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.
Reasoning mode
Ling 3.1 Flash can produce reasoning before its final answer; in the Playground you can switch reasoning on or off to compare results.
How to Use Ling 3.1 Flash 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 Ling 3.1 Flash 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.
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Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "ling-3-1-flash" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
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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 Ling 3.1 Flash
Analysis and complex reasoning
Work through research questions, data interpretation, planning and other problems that need careful step-by-step reasoning.
Autonomous agents
Build agents that plan multi-step tasks, call your tools and APIs, and keep working toward a goal across long sessions.
Long-document workflows
Feed in long reports, contracts, manuals or codebases and ask for summaries, comparisons and answers grounded in the material.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Frequently Asked Questions
What is Ling 3.1 Flash?⌄
Ling 3.1 Flash is a hybrid reasoning Mixture-of-Experts model from inclusionAI, with 25B active parameters out of 560B total.
Which inputs does Ling 3.1 Flash support?⌄
Ling 3.1 Flash 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 Ling 3.1 Flash?⌄
Up to 1M tokens, shared between your input and the model’s output.
Does Ling 3.1 Flash support function calling?⌄
Yes. Ling 3.1 Flash supports tools / function calling through the standard tools parameter of the chat completions API.
How is Ling 3.1 Flash 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 Ling 3.1 Flash through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "ling-3-1-flash", using your ModelFold API key as the Bearer token.
| Input | 9 credits 1M tokens≈ $0.04 |
| Output | 27 credits 1M tokens≈ $0.14 |
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":"ling-3-1-flash","messages":[{"role":"user","content":"Hello"}]}'