LLM Reference

Qwen3.5-Omni Flash

Released
2026-03-30
Last refreshed
2026-05-04
Status
Researched 135d ago
ProprietaryCommercial use: conditionalMultimodalRAGAgentsLong contextVisionJSON / Tool use

Qwen3.5-Omni Flash is worth evaluating for rag, agents, and long context when its provider route and context window match the workload.

Use it for

  • Teams evaluating rag, agents, and long context
  • Workloads that can use a 262k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Workloads where another current model has stronger sourced task evidence
Specifications
Released
2026-03-30
Context
262k
Specialization
general
Openness
Proprietary
License
ProprietaryCommercial use: conditional
Weights
Not released
Code
Unknown
Training
Pretrained
Created by

AI research institute of Alibaba Group.

Hangzhou, Zhejiang, China
Founded 2017
Website
Pricing
Output / 1M
$0.800
Input / 1M
$0.100

Cheapest of 1 route · Alibaba Cloud PAI-EAS

About

Qwen3.5-Omni Flash is Alibaba's lower-latency omnimodal API model, released March 30, 2026. It keeps the Qwen3.5-Omni text, image, audio, and video input surface while reducing cost and latency for short video analysis and high-throughput multimodal workloads. API model ID: qwen3.5-omni-flash.

Top use-case fit: coding, agents, and build tasks

RAG

Included by capability and metadata signals in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Long context

Included by capability and metadata signals in the decision map.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Alibaba Cloud PAI-EAS$0.100$0.800
Serverless

Capabilities

VisionMultimodalJSON / Tool useStructured OutputsAudio

Benchmark peer barsfor RAG

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.