qwen3-5-flash-02-23
Qwen3.5-Flash is a native vision-language Flash model with a hybrid linear-attention and sparse mixture-of-experts architecture, built for efficient inference with a 1M-token context window.
Precio: Entrada: 15.6 créditos / 1 M de tokens (≈ $0.08); salida: 62.4 créditos / 1 M de tokens (≈ $0.31).
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Qwen3.5-Flash API on ModelFold
Qwen3.5-Flash is a native vision-language Flash model with a hybrid linear-attention and sparse mixture-of-experts architecture, built for efficient inference with a 1M-token context window. Try Qwen3.5-Flash in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Qwen3.5-Flash API
Qwen3.5-Flash at a glance
Qwen3.5-Flash is a chat model from Qwen. It accepts text, images and video as input and returns text, with a context window of up to 1M tokens.
Use it without hosting anything
On ModelFold you call Qwen3.5-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 Qwen3.5-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.
Understands images and video
Besides text, Qwen3.5-Flash accepts images and video as input, so a single request can combine instructions with visual or other media.
Function calling
Qwen3.5-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
Qwen3.5-Flash can produce reasoning before its final answer; in the Playground you can switch reasoning on or off to compare results.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Qwen3.5-Flash on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Qwen3.5-Flash responds before writing any code.
- 2
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": "qwen3-5-flash-02-23" 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 Qwen3.5-Flash
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Low-latency experiences
Power chat interfaces, autocomplete and interactive tools where users expect fast responses.
Screenshot and image understanding
Read screenshots, charts, diagrams and photos alongside text — for UI review, visual QA or turning images into structured data.
Long-document workflows
Feed in long reports, contracts, manuals or codebases and ask for summaries, comparisons and answers grounded in the material.
Frequently Asked Questions
What is Qwen3.5-Flash?⌄
Qwen3.5-Flash is a native vision-language Flash model with a hybrid linear-attention and sparse mixture-of-experts architecture, built for efficient inference with a 1M-token context window.
Which inputs does Qwen3.5-Flash support?⌄
Qwen3.5-Flash accepts text, images and video and returns text. Through ModelFold you can send text and images (OpenAI-style image_url content); in the Playground you can also attach documents, which are converted to text.
How long is the context window of Qwen3.5-Flash?⌄
Up to 1M tokens, shared between your input and the model’s output.
Does Qwen3.5-Flash support function calling?⌄
Yes. Qwen3.5-Flash supports tools / function calling through the standard tools parameter of the chat completions API.
How is Qwen3.5-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 Qwen3.5-Flash through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "qwen3-5-flash-02-23", using your ModelFold API key as the Bearer token.
| Entrada | 15.6 créditos 1M tokens≈ $0.08 |
| Salida | 62.4 créditos 1M tokens≈ $0.31 |
Se cobra por token, con tarifas separadas para entrada y salida. Los tokens de razonamiento cuentan como salida. El entorno de pruebas aplica exactamente el mismo cálculo.
Leer la documentación de la API →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":"qwen3-5-flash-02-23","messages":[{"role":"user","content":"Hello"}]}'