What architecture powers Qwen 3.5 Flash?

It uses a Gated DeltaNet plus sparse mixture-of-experts design with a 3:1 linear-to-full attention ratio, enabling efficient processing of very long sequences at lower compute cost than dense transformer models.

Can Qwen 3.5 Flash analyze video clips?

Yes. The model natively accepts video inputs alongside text and images, allowing you to include short video segments in the same prompt as text instructions without preprocessing.

How does the context of 1M tokens affect RAG architecture decisions?

For many document retrieval tasks the full context window eliminates the need for a separate vector search layer, since entire documents or codebases can be passed directly. However, chunking and retrieval still benefit latency and cost for very large corpora.

Does Qwen 3.5 Flash support tool calling?

Yes. Tool calling, structured JSON outputs, and function-calling patterns are fully supported across all AI Gateway interfaces.

What does the configurable reasoning parameter do?

Callers can adjust how much internal chain-of-thought computation the model performs before responding. Lower settings optimize for speed; higher settings improve accuracy on multi-step reasoning tasks at the cost of added latency.

What is the difference between Qwen 3.5 Flash and Qwen3.5-Plus?

Flash is the cost-optimized, lower-latency variant built on the 35B-A3B architecture, while Plus is the higher-capability tier suited for more demanding reasoning and visual analysis tasks. Both share the context window of 1M tokens.

Is Qwen 3.5 Flash suitable for production agentic workflows?

Yes. The model was specifically designed for agentic use: it supports adaptive tool use, structured outputs, and the long context required to maintain agent state across many tool-call turns.

Alibaba Cloud

Qwen 3.5 Flash

Qwen 3.5 Flash is Alibaba Cloud's production-hosted multimodal model built on a hybrid linear-attention MoE architecture, offering a context window of 1M tokens and sub-second responsiveness for high-throughput agentic workloads.

View API reference

Input and output price: Input $0.10, Output $0.40, Per 1M tokens
24h uptime: Loading AI Gateway uptime

Get API key Read the docs

import { streamText } from 'ai'

const result = streamText({
  model: 'alibaba/qwen3.5-flash',
  prompt: 'Why is the sky blue?'
})

Read docs

Overview Playground Providers Uptime Status Throughput Latency API Similar About FAQ

Copy link to headingPlayground

Try out Qwen 3.5 Flash by Alibaba Cloud. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.

Qwen 3.5 Flash

Copy link to headingProviders

Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.

Provider

Context	Max Output	Latency	Throughput	Input	Output	Cache	Web Search	Capabilities	ZDR	No Training	Free Tier	Release Date

Alibaba Cloud

Legal:Terms•Privacy

64K

0.8 s

169 tps

$0.10/M

$0.40/M

Read$0.001/M

Write$0.13/M

—

02/24/2026

Getting started

Call Qwen 3.5 Flash through AI Gateway with the AI SDK generateText and streamText functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider.

Install the AI SDK (pnpm add ai dotenv), create an API key from the API Keys page, and set it as AI_GATEWAY_API_KEY in your environment. Full setup is covered in the text generation quickstart.

index.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'alibaba/qwen3.5-flash',
    prompt: 'Why is the sky blue?',
  });

  console.log(result.text);
}

main().catch(console.error);

Top-level parameters

The same Qwen 3.5 Flash request in each API format AI Gateway supports.

top-level-params.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'alibaba/qwen3.5-flash',
    system: 'You are a concise technical assistant.',
    prompt: 'Summarize the tradeoffs between static generation and SSR.',
    maxOutputTokens: 1024,
  });

  console.log(result.text);
}

main().catch(console.error);

Standard parameters like prompt, messages, temperature, and tools work as documented in the AI SDK docs. These are the parameters with model-specific behavior.

Parameter	Type	Required	Description
`model`	`string`	Yes	Model ID in the form `creator/model`, e.g. `alibaba/qwen3.5-flash`. AI Gateway routes the request to an available provider.
`maxOutputTokens`	`number`	No	Hard cap on generated tokens. Qwen 3.5 Flash supports up to `64,000` output tokens. Reasoning tokens count toward this limit.
`reasoning`	`'provider-default' \| 'none' \| 'minimal' \| 'low' \| 'medium' \| 'high' \| 'xhigh'`	No	Provider-agnostic reasoning effort, available in AI SDK 7 or later. Maps to the provider’s native reasoning configuration; reasoning settings under `providerOptions` take precedence when both are set. See the Reasoning section below.
`providerOptions`	`Record<string, JSONValue>`	No	AI Gateway routing options under `gateway`, plus any provider-native options under the provider’s own namespace — see the table below.

Input limits

Input	Formats	Sources	Max count	Max size	Limits
Text	—	—	—	—	Prompt and response share the 1M-token context window
Image	—	URL, base64, Uint8Array	—	—	Sent as image parts in messages; counts as input tokens
PDF	—	URL, base64, Uint8Array	—	—	Sent as file parts in messages; counts as input tokens

Provider options

Set AI Gateway routing options under providerOptions.gateway. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK.

Learn more in the AI SDK alibaba provider docs.

provider-options.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'alibaba/qwen3.5-flash',
    prompt: 'Why is the sky blue?',
    providerOptions: {
      gateway: {
        only: ['alibaba'],
      },
    },
  });

  console.log(result.text);
}

main().catch(console.error);

These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example providerOptions.anthropic) exactly as documented by the AI SDK.

Parameter	Type	Required	Description
`providerOptions.gateway.only`	`string[]`	No	Restrict routing to these provider slugs. Requests fail over only within the listed providers.
`providerOptions.gateway.order`	`string[]`	No	Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks.
`providerOptions.gateway.sort`	`'cost' \| 'ttft' \| 'tps'`	No	Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order.
`providerOptions.gateway.zeroDataRetention`	`boolean`	No	Route only to providers with a zero-data-retention policy for this model.

Routing across providers

AI Gateway serves the same model through multiple providers and fails over automatically. order expresses a preference while keeping every provider eligible; only is a hard allowlist — if none of the listed providers are available the request fails instead of falling back.

Options under a provider's own namespace (for example providerOptions.anthropic) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside gateway routing options.

Reasoning

AI Gateway bridges reasoning across every API format. The AI SDK exposes a provider-agnostic top-level reasoning level (none, minimal, low, medium, high, or xhigh); the Chat Completions and Responses formats take the same effort under reasoning.effort; and the Anthropic Messages format uses a native thinking token budget. Whichever you send, the gateway maps it to the target model’s native configuration, converting between effort levels and token budgets as needed. Reasoning-related settings under providerOptions take full precedence over the top-level reasoning value and are never merged. Reasoning tokens typically count toward your output-token usage, though how they’re reported and billed varies by provider.

Learn more in the AI Gateway reasoning guide.

reasoning.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'alibaba/qwen3.5-flash',
    prompt: 'Explain the Monty Hall problem step by step.',
    reasoning: 'high',
  });

  console.log(result.text);
}

main().catch(console.error);

Image input

Send images alongside text as message parts. Images count as input tokens.

image-input.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'alibaba/qwen3.5-flash',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Describe this image.' },
          { type: 'image', image: 'https://example.com/photo.jpg' },
        ],
      },
    ],
  });

  console.log(result.text);
}

main().catch(console.error);

PDF input

Attach PDFs as file parts. Their contents count as input tokens.

pdf-input.ts

import { generateText } from 'ai';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'alibaba/qwen3.5-flash',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Summarize this document.' },
          {
            type: 'file',
            mediaType: 'application/pdf',
            data: 'https://example.com/document.pdf',
          },
        ],
      },
    ],
  });

  console.log(result.text);
}

main().catch(console.error);

Tool calling

Expose tools the model can call. Define each tool’s inputs with a Zod schema.

tool-calling.ts

import { generateText, tool } from 'ai';
import { z } from 'zod';
import 'dotenv/config';

async function main() {
  const result = await generateText({
    model: 'alibaba/qwen3.5-flash',
    prompt: 'What is the weather in San Francisco?',
    tools: {
      getWeather: tool({
        description: 'Get the current weather for a location',
        inputSchema: z.object({ location: z.string() }),
        execute: async ({ location }) => ({ location, temperatureC: 18 }),
      }),
    },
  });

  console.log(result.text);
}

main().catch(console.error);

Copy link to headingMore models by Alibaba Cloud

Model

Context	Latency	Throughput	Input	Output	Cache	Web Search	Capabilities	Providers	ZDR	No Training	Free Tier	Release Date

alibaba/qwen3.8-max-0902

991K

3.9 s

50 tps

$2/M

$6/M

Read$0.25/M

Write$2.50/M

—

09/01/2026

alibaba/qwen3.8-flash

991K

1.1 s

96 tps

$0.16/M

$0.47/M

Read$0.02/M

Write$0.20/M

—

08/26/2026

alibaba/qwen3.8-27b

0.6 s

133 tps

$0.10/M

$0.40/M

Read$0.01/M

Write$0.63/M

—

08/14/2026

alibaba/qwen3.8-max

2.5 s

154 tps

$2/M

$6/M

Read$0.25/M

Write$2.50/M

—

08/02/2026

alibaba/qwen3.7-flash

991K

2.5 s

140 tps

$0.03/M+2 more

$0.13/M+2 more

Read$0.006/M

Write$0.04/M

—

07/28/2026

alibaba/qwen3.7-plus

2.0 s

58 tps

$0.40/M+1 more

$1.60/M+1 more

Read$0.08/M

Write$0.50/M

—

06/02/2026

Copy link to headingAbout Qwen 3.5 Flash

Qwen 3.5 Flash is built on Alibaba Cloud's fifth-generation Qwen3.5 architecture, which combines Gated DeltaNet linear attention with sparse mixture-of-experts layers in a 3:1 linear-to-full attention ratio. This design allows the model to process very long documents and codebases efficiently while keeping inference costs low, the hosted Flash tier makes contexts of 1M tokens the default rather than an opt-in premium.

The model handles text, images, and video natively in a single forward pass, without requiring separate vision adapters. That native multimodality makes it well-suited for workflows that mix screenshot analysis, document review, and code generation in the same conversation. Structured outputs, tool calling, and seed-based reproducibility are all supported out of the box.

Qwen 3.5 Flash ships with configurable reasoning depth, letting callers dial up or down the amount of internal chain-of-thought the model performs before responding. At lower reasoning settings the model behaves like a fast instruction-follower; at higher settings it performs multi-step decomposition suitable for mathematical problem solving or complex agentic tasks.

Copy link to headingWhat To Consider When Choosing a Provider

Configuration: For latency-sensitive pipelines, compare time-to-first-token across available providers using the AI Gateway playground before committing to a routing configuration.
Zero Data Retention: Zero Data Retention is available for this model. It is offered on a per-provider and model basis. See the documentation for details.
Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.

Copy link to headingWhen to Use Qwen 3.5 Flash

Best for

Whole-codebase and long-PDF processing: Handling entire repositories or long reports in a single request using the default context of 1M tokens
Fast agentic tool loops: Low-cost structured JSON responses for agents that chain many tool calls
Multimodal conversation threads: Pipelines where text, screenshots, and short video clips arrive in the same thread
Latency-sensitive reasoning: Applications that need reasoning capability but can't tolerate the cost of the Plus tier

Consider alternatives when

Maximum reasoning depth: Consider Qwen3.5 Plus for heavier analytical workloads when cost is secondary
Lowest text-only pricing: A dedicated text model is cheaper for pipelines that never need vision
Image or video generation: This model understands multimodal inputs but doesn't generate images or video

Copy link to headingConclusion

Qwen 3.5 Flash delivers Alibaba Cloud's fifth-generation multimodal reasoning at a cost point suited for production scale, with a context of 1M tokens that eliminates most RAG pipeline overhead. For teams building document-heavy or agentic applications on Vercel, it occupies the efficiency end of the Qwen3.5 lineup without sacrificing vision support.

Copy link to headingFrequently Asked Questions

What architecture powers Qwen 3.5 Flash?
It uses a Gated DeltaNet plus sparse mixture-of-experts design with a 3:1 linear-to-full attention ratio, enabling efficient processing of very long sequences at lower compute cost than dense transformer models.
Can Qwen 3.5 Flash analyze video clips?
Yes. The model natively accepts video inputs alongside text and images, allowing you to include short video segments in the same prompt as text instructions without preprocessing.
How does the context of 1M tokens affect RAG architecture decisions?
For many document retrieval tasks the full context window eliminates the need for a separate vector search layer, since entire documents or codebases can be passed directly. However, chunking and retrieval still benefit latency and cost for very large corpora.
Does Qwen 3.5 Flash support tool calling?
Yes. Tool calling, structured JSON outputs, and function-calling patterns are fully supported across all AI Gateway interfaces.
What does the configurable reasoning parameter do?
Callers can adjust how much internal chain-of-thought computation the model performs before responding. Lower settings optimize for speed; higher settings improve accuracy on multi-step reasoning tasks at the cost of added latency.
What is the difference between Qwen 3.5 Flash and Qwen3.5-Plus?
Flash is the cost-optimized, lower-latency variant built on the 35B-A3B architecture, while Plus is the higher-capability tier suited for more demanding reasoning and visual analysis tasks. Both share the context window of 1M tokens.
Is Qwen 3.5 Flash suitable for production agentic workflows?
Yes. The model was specifically designed for agentic use: it supports adaptive tool use, structured outputs, and the long context required to maintain agent state across many tool-call turns.

Your use is subject to Alibaba Cloud's Terms & Privacy Policies.

Agent Stack

Core Platform

Tools

Learn

Build

Explore

Qwen 3.5 Flash

Copy link to headingPlayground

Copy link to headingProviders

Copy link to headingUptime24 hours

Copy link to headingThroughput24 hours

Copy link to headingLatency24 hours

Getting started

Top-level parameters

Input limits

Provider options

Routing across providers

Reasoning

Image input

PDF input

Tool calling

Copy link to headingMore models by Alibaba Cloud

Copy link to headingAbout Qwen 3.5 Flash

Copy link to headingWhat To Consider When Choosing a Provider

Copy link to headingWhen to Use Qwen 3.5 Flash

Best for

Consider alternatives when

Copy link to headingConclusion

Copy link to headingFrequently Asked Questions