Model Detail
Qwen: Qwen VL Max
—Qwen: Qwen VL Max is a multimodal model released by Qwen. And supports text+image->text inputs.
Qwen: Qwen VL Max is priced at $0.52/M input tokens and $2.08/M output tokens. Operationally the model offers a 131K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. Pricing in this range is the working middle of the API market — neither the cheapest nor the most expensive option per token, so cost-fit is usually a function of how much output you generate.
The published knowledge cutoff is 2025-03-31, so newer events will not be reflected in zero-shot answers without retrieval.
Qwen: Qwen VL Max is best fit for mixed text-and-image reasoning tasks such as document understanding. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
Qwen-Audio-Jev: A Unified Interface for Audio Decisions
arXiv:2610.21614v1 Announce Type: cross Abstract: Large audio language models (LALMs) have made substantial progress in audio understanding. However, in high-throughput applications requiring frequent selection, judgment, and scoring, autoregressive text generation introduces additional computationa
Qwen-MT-Lumen at WMT2026: Instruction-Specialized Translation via Quality-Aware Training and On-Policy Distillation
arXiv:2610.19758v1 Announce Type: new Abstract: We present Lumen, The open-source model is available at, our submission to the WMT 2026 General Machine Translation Shared Task. We focus on instruction-specialized translation, where systems must produce accurate translations while satisfying fine-gra
Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction
arXiv:2609.25176v2 Announce Type: replace-cross Abstract: Real-time voice assistants must reason over evolving requests, execute actions, and follow conversational rules. Qwen-Audio-3.1-Realtime brings these requirements together through Think, Act, and Speak and Coordinate. Think combines Core-Cock
Qwen-Planner-Agent: A Closed-Loop AI-for-AI Framework for Real-World Mobile Planner Agents
arXiv:2609.29892v1 Announce Type: new Abstract: The rapid progression of large language models is extending AI from passive content generation into the active workflows of engineering and scientific discovery. This shift raises a compelling question: can AI be both the object of development and an a
Qwen-Image-Flash: Rethinking the Training Recipe for Few-Step Distillation
arXiv:2606.03746v3 Announce Type: replace-cross Abstract: Few-step distillation has emerged as a critical component in the development of advanced visual generative foundation models, substantially reducing inference overhead while enabling real-time generation and cost-efficient deployment across a
