Alibaba
Qwen3.8 Omni Flash
qwen3.8-omni-flash
Total Context
1M
Max Output
131.1K
Released
N/A
Input$0.1143 / M tokens
Output$0.3857 / M tokens
Qwen3.5 Flash
qwen3.5-flashQwen3.5 Flash is the efficient entry in the Qwen3.5 native vision-language family. Alibaba’s model list positions Flash as a fast and cost-effective option for simpler tasks, while still inheriting the 3.5 generation’s multimodal direction. It is a practical choice for extraction, routing, lightweight content generation, and high-frequency calls.
Context Window
262.1K tokens
Maximum Output
65.5K tokens
Release Date
Feb 23, 2026
Modalities
Qwen3.5 Flash Pricing
| Token Tier | Input Price | Output Price | Cache Create 5m | Cache Read 5m |
|---|---|---|---|---|
| <=128K | $0.0286/M | $0.2857/M | $0.0357/M | $0.0029/M |
| 128K-256K | $0.1143/M | $1.1429/M | $0.1429/M | $0.0114/M |
| >256K | $0.1714/M | $1.7143/M | $0.2143/M | $0.0171/M |
Qwen3.5 Flash API Capabilities
Reasoning
Supported
Tool calling
Supported
Temperature parameter
Supported
Attachments
Supported
Knowledge Base
—
Endpoint Protocols
Completions APIMessages APIgemini
Qwen3.5 Flash Model Highlights
Qwen3.5 Flash combines fast inference, native multimodal understanding and long-context reasoning for responsive production workloads.
Efficient Inference
A hybrid linear-attention and sparse MoE architecture is designed to provide fast responses while retaining general text and multimodal performance.
Native Multimodality
The model accepts text, images and video as input and produces text, enabling mixed-media understanding in one model.
Million-Token Context
A one-million-token context window supports analysis of extensive documents, long conversations and large collections of mixed inputs.
Qwen3.5 Flash Use Cases
Qwen3.5 Flash is suited to responsive multimodal assistants, rapid content processing and long-context information review.
Multimodal Support
Answer customer questions using accompanying screenshots, product images or short videos and return concise text guidance.
Content Triage
Classify, summarize or extract key facts from high volumes of text and visual content for downstream review.
Long-Context Review
Review large document sets or extended conversation histories, locate relevant details and produce a focused summary.
How to Use Qwen3.5 Flash via the TokenHub API
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)Qwen 3.5 Flash FAQ
Qwen 3.5 Flash: capabilities, use cases, limits, and TokenHub guidance.
What role does Qwen 3.5 Flash play?+
Qwen 3.5 Flash is a Alibaba Qwen model for fast multimodal understanding and high-volume use.
What should I try first with Qwen 3.5 Flash?+
Best for high-volume requests, image and video understanding and general conversation, especially when speed and cost efficiency is the priority.
Why choose Qwen 3.5 Flash?+
Key strength: fast multimodal operation while approaching the Plus tier and hybrid thinking that can switch between deliberate and direct responses.
What tradeoff comes with Qwen 3.5 Flash?+
It belongs to an older generation and may lack newer capabilities. For the latest capabilities matter, consider Qwen 3.6 Flash.
How should I start in TokenHub?+
Use the exact ID shown by TokenHub; follow your account docs and verify current features.
Ready to use Qwen3.5 Flash?
Use one API key to access Qwen3.5 Flash and more AI models through TokenHub.
Media and Discussions
Selected public videos and posts related to this model.
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