Speed
Output tokens / second
Qwen3.5 Omni Flash overview
Qwen3.5 Omni Flash specs
- Model ID
alibaba/qwen3.5-omni-flash- Developer
- Alibaba Cloud
- Context window
- 256,000 tokens
- Max output
- 192,000 tokens
- Input
- Text, Image, Audio, Video
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
What Qwen3.5 Omni Flash actually is
Most models that claim multimodal support are really just text models with extra adapters bolted on. Qwen3.5 Omni Flash is different. It processes text, speech, image, and video natively, all inside one unified architecture, and can generate both text and streaming speech as output. The Flash variant is the production-default recommendation from Alibaba: the middle path between maximum quality and minimum cost.
Architecture: Thinker and Talker
Qwen3.5 Omni Flash builds on the Thinker–Talker architecture introduced in Qwen2.5-Omni, then adds five major technical upgrades for the 3.5 generation. Understanding the design matters if you're integrating this into latency-sensitive pipelines.
Thinker, the reasoning core
Handles all understanding tasks. Ingests text, image, audio (via the AuT encoder), and video frames simultaneously. Uses a Hybrid-Attention Mixture-of-Experts (MoE) design, meaning only a subset of parameters activates per token, which is how the model achieves fast inference without sacrificing model capacity.
Talker, the speech synthesizer
Receives high-level representations directly from Thinker during decoding and autoregressively predicts multi-codebook speech tokens. A causal ConvNet then reconstructs the waveform frame-by-frame, enabling streaming speech output with very low latency. The Talker also supports a dedicated voice system prompt for zero-shot voice cloning.
ARIA, alignment for real-time interaction
A new technique introduced in 3.5 that dynamically aligns text and speech units during streaming decoding. This solves a long-standing naturalness problem in auto-regressive speech: the output sounds more fluid and less robotic, especially in multi-turn spoken dialogue.
Multi-codebook codec
Rather than synthesizing audio frame by frame at high latency, a multi-token prediction (MTP) module models residual codebooks for each frame, enabling single-frame, immediate synthesis. This is what keeps voice response latency in the sub-300ms range even on long utterances.
Use cases
Qwen3.5 Omni Flash is documented as being used for text creation, voice assistants, and multimedia analysis.
It is also described as suitable for natural, fluent multimodal interaction experiences across text, image, audio, and audio-visual understanding.
The model is further presented as fitting audio-visual understanding and interaction scenarios, including meeting analysis and live translation.
Alibaba Cloud also describes it as suitable for long-form audiovisual analysis, real-time voice interaction, video understanding, intelligent assistants, and multimodal agents.
Capabilities
- Function calling
- Streaming
- Structured outputs
- Reasoning
Qwen3.5 Omni Flash benchmarks by 
Artificial Analysis
See how Qwen3.5 Omni Flash compares in generation speed and latency. Data retrieved Nov 3, 2026.
Benchmark results
Compare 15 models available on AI/ML API across 5 independent benchmarks.
Humanity's Last Exam
Expert-written questions across academic subjects.
GPQA Diamond
Graduate-level science questions written to resist web search.
AA-LCR
Reasoning across long documents of about 100k tokens.
IFBench
Following precise instructions about the shape of the answer.
τ²-Bench Telecom
Customer support agent tasks with tool calls.
Qwen3.5 Omni Flash API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.4 | 1M tokens |
| Output | $2.2 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
Qwen3.5 Omni Flash vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
 Qwen3.5 Omni Flash | $0.4 | $2.2 |
| Qwen3.8 Omni Flash | $0.15 | $0.47 |
| Qwen3.8-Flash | $0.16 | $0.47 |
| Qwen 3.8 27B | $0.4761 | $3.39 |
| Qwen3.8 Max Prime | $4.23 | $12.7 |
How to use the Qwen3.5 Omni Flash API
View docs
Build with your agent
Give your agent the model details, code and documentation.
Paste it into your coding agent to build the integration.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "alibaba/qwen3.5-omni-flash",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "alibaba/qwen3.5-omni-flash",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "alibaba/qwen3.5-omni-flash",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to Qwen3.5 Omni Flash
Related articles
Qwen3.5 Omni Flash FAQ
How much does Qwen3.5 Omni Flash cost?
Qwen3.5 Omni Flash costs $0.4 input and $2.2 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Does Qwen3.5 Omni Flash have reasoning capability?
Yes, reasoning is listed among its features and capabilities.
What is the Qwen3.5 Omni Flash model ID?
Use alibaba/qwen3.5-omni-flash as the model parameter. Requests go to the OpenAI-compatible endpoint with your AI/ML API key.
What is the context window of Qwen3.5 Omni Flash?
Qwen3.5 Omni Flash accepts up to 256,000 tokens of context and returns up to 192,000 output tokens.