qwen3-max
阿里巴巴 · Qwen阿里巴巴通义千问发布的超万亿参数级大语言模型，在推理、编程和多语言任务上定位为对标 GPT-5 级别的旗舰模型。
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查看详情 ↗DISCOVER & COMPARE
探索 AI 模型 84883
qwen3-max-2025-09-23
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗qwen3-max-2026-01-23
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗qwen3-max-preview
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗Qwen3 Next 80B A3B Instruct
阿里巴巴 · QwenQwen3-Next-80B-A3B-Instruct 是 Qwen3-Next 系列中的一款指令微调聊天模型，经过优化，可在不留下“思考”痕迹的情况下实现快速、稳定的响应。它面向推理、代码生成、知识问答以及多语言等复杂任务……
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$0.09 / M 输入 TokenOpenRouter · qwen/qwen3-next-80b-a3b-instruct
查看详情 ↗qwen3-next-80b-a3b-thinking
阿里巴巴 · QwenOver the past few months, we have observed increasingly clear trends toward scaling both total parameters and context lengths in the pursuit of more powerful and agentic artificial intelligence (AI). We are excited to share our latest advancements in addressing these demands, centered on improving scaling efficiency through innovative model architecture. We call this next-generation foundation models **Qwen3-Next**. **Qwen3-Next-80B-A3B** is the first installment in the Qwen3-Next series and features the following key enchancements: - **Hybrid Attention**: Replaces standard attention with the combination of **Gated DeltaNet** and **Gated Attention**, enabling efficient context modeling for ultra-long context length. - **High-Sparsity Mixture-of-Experts (MoE)**: Achieves an extreme low activation ratio in MoE layers, drastically reducing FLOPs per token while preserving model capacity. - **Stability Optimizations**: Includes techniques such as **zero-centered and weight-decayed layernorm**, and other stabilizing enhancements for robust pre-training and post-training. - **Multi-Token Prediction (MTP)**: Boosts pretraining model performance and accelerates inference. We are seeing strong performance in terms of both parameter efficiency and inference speed for Qwen3-Next-80B-A3B: - Qwen3-Next-80B-A3B-Base outperforms Qwen3-32B-Base on downstream tasks with 10% of the total training cost and with 10 times inference throughput for context over 32K tokens. - Leveraging GSPO, we have addressed the stability and efficiency challenges posed by the hybrid attention mechanism combined with a high-sparsity MoE architecture in RL training. Qwen3-Next-80B-A3B-Thinking demonstrates outstanding performance on complex reasoning tasks, not only **surpassing Qwen3-30B-A3B-Thinking-2507 and Qwen3-32B-Thinking**, but also **outperforming the proprietary model Gemini-2.5-Flash-Thinking** across multiple benchmarks.
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$0.15 / M 输入 TokenOpenRouter · qwen/qwen3-next-80b-a3b-thinking
查看详情 ↗qwen3-reranker-0.6b
阿里巴巴 · QwenThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining. **Exceptional Versatility**: The embedding model has achieved state-of-the-art performance across a wide range of downstream application evaluations. The 8B size embedding model ranks No.1 in the MTEB multilingual leaderboard (as of June 5, 2025, score 70.58), while the reranking model excels in various text retrieval scenarios. **Comprehensive Flexibility**: The Qwen3 Embedding series offers a full spectrum of sizes (from 0.6B to 8B) for both embedding and reranking models, catering to diverse use cases that prioritize efficiency and effectiveness. Developers can seamlessly combine these two modules. Additionally, the embedding model allows for flexible vector definitions across all dimensions, and both embedding and reranking models support user-defined instructions to enhance performance for specific tasks, languages, or scenarios.
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查看详情 ↗qwen3-reranker-4b
阿里巴巴 · QwenThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining. **Exceptional Versatility**: The embedding model has achieved state-of-the-art performance across a wide range of downstream application evaluations. The 8B size embedding model ranks No.1 in the MTEB multilingual leaderboard (as of June 5, 2025, score 70.58), while the reranking model excels in various text retrieval scenarios. **Comprehensive Flexibility**: The Qwen3 Embedding series offers a full spectrum of sizes (from 0.6B to 8B) for both embedding and reranking models, catering to diverse use cases that prioritize efficiency and effectiveness. Developers can seamlessly combine these two modules. Additionally, the embedding model allows for flexible vector definitions across all dimensions, and both embedding and reranking models support user-defined instructions to enhance performance for specific tasks, languages, or scenarios.
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查看详情 ↗qwen3-reranker-8b
阿里巴巴 · QwenThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining. **Exceptional Versatility**: The embedding model has achieved state-of-the-art performance across a wide range of downstream application evaluations. The 8B size embedding model ranks No.1 in the MTEB multilingual leaderboard (as of June 5, 2025, score 70.58), while the reranking model excels in various text retrieval scenarios. **Comprehensive Flexibility**: The Qwen3 Embedding series offers a full spectrum of sizes (from 0.6B to 8B) for both embedding and reranking models, catering to diverse use cases that prioritize efficiency and effectiveness. Developers can seamlessly combine these two modules. Additionally, the embedding model allows for flexible vector definitions across all dimensions, and both embedding and reranking models support user-defined instructions to enhance performance for specific tasks, languages, or scenarios.
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查看详情 ↗qwen3-vl-235b-a22b
阿里巴巴 · QwenQwen3-VL-235B-A22B 是通义千问推出的超大规模视觉-语言 MoE 模型（激活参数约 220 亿），支持长上下文和多模态输入。 它能做图像理解、OCR、多模态推理、视频/多帧分析，并结合文本生成、界面交互和代码生成等功能。
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查看详情 ↗Qwen3 VL 235B A22B Instruct
阿里巴巴 · QwenQwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
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$0.21 / M 输入 TokenOpenRouter · qwen/qwen3-vl-235b-a22b-instruct
查看详情 ↗qwen3-vl-235b-a22b-thinking
阿里巴巴 · QwenMeet Qwen3-VL — the most powerful vision-language model in the Qwen series to date. This generation delivers comprehensive upgrades across the board: superior text understanding & generation, deeper visual perception & reasoning, extended context length, enhanced spatial and video dynamics comprehension, and stronger agent interaction capabilities. Available in Dense and MoE architectures that scale from edge to cloud, with Instruct and reasoning‑enhanced Thinking editions for flexible, on‑demand deployment.
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查看详情 ↗Qwen3 VL 30B A3B Instruct
阿里巴巴 · QwenQwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception...
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$0.15 / M 输入 TokenOpenRouter · qwen/qwen3-vl-30b-a3b-instruct
查看详情 ↗Qwen3 VL 30B A3B Thinking
阿里巴巴 · QwenQwen3-VL-30B-A3B-Thinking 是一款多模态模型，将强大的文本生成能力与图像和视频的视觉理解能力融为一体。其 Thinking 变体在 STEM、数学以及复杂任务中的推理能力方面得到了显著提升。它擅长……
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$0.29 / M 输入 TokenOpenRouter · qwen/qwen3-vl-30b-a3b-thinking
查看详情 ↗qwen3-vl-32b-instruct
阿里巴巴 · QwenMeet Qwen3-VL — the most powerful vision-language model in the Qwen series to date. This generation delivers comprehensive upgrades across the board: superior text understanding & generation, deeper visual perception & reasoning, extended context length, enhanced spatial and video dynamics comprehension, and stronger agent interaction capabilities. Available in Dense and MoE architectures that scale from edge to cloud, with Instruct and reasoning‑enhanced Thinking editions for flexible, on‑demand deployment.
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查看详情 ↗qwen3-vl-32b-thinking
阿里巴巴 · QwenThis generation delivers comprehensive upgrades across the board: superior text understanding & generation, deeper visual perception & reasoning, extended context length, enhanced spatial and video dynamics comprehension, and stronger agent interaction capabilities. Available in Dense and MoE architectures that scale from edge to cloud, with Instruct and reasoning‑enhanced Thinking editions for flexible, on‑demand deployment. 1. **Interleaved-MRoPE**: Full‑frequency allocation over time, width, and height via robust positional embeddings, enhancing long‑horizon video reasoning.
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查看详情 ↗Qwen3 VL 8B Instruct
阿里巴巴 · QwenQwen3-VL-8B-Instruct 是 Qwen3-VL 系列中的一款多模态视觉语言模型，专为在文本、图像和视频之间实现高保真理解与推理而打造。它采用 Interleaved-MRoPE 技术，实现了更优的多模态融合，适用于长时序场景……
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$0.25 / M 输入 TokenOpenRouter · qwen/qwen3-vl-8b-instruct
查看详情 ↗qwen3-vl-8b-thinking
阿里巴巴 · QwenMeet Qwen3-VL — the most powerful vision-language model in the Qwen series to date. This generation delivers comprehensive upgrades across the board: superior text understanding & generation, deeper visual perception & reasoning, extended context length, enhanced spatial and video dynamics comprehension, and stronger agent interaction capabilities. Available in Dense and MoE architectures that scale from edge to cloud, with Instruct and reasoning‑enhanced Thinking editions for flexible, on‑demand deployment.
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查看详情 ↗qwen3-vl-flash
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗qwen3-vl-flash-2025-10-15
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗qwen3-vl-flash-2026-01-22
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗qwen3-vl-plus
阿里巴巴 · QwenQwen3-VL-Plus 是 Qwen-VL 系列中的增强视觉-语言模型版本，具有更强的细节识别和文本识别能力，支持超高像素分辨率和极端宽高比的图像输入。 它在视觉理解（物体识别、OCR、空间分析等）与文本生成 / 模型推理等多模态任务中都有显著性能提升。
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查看详情 ↗qwen3-vl-plus-2025-09-23
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗qwen3-vl-plus-2025-12-19
阿里巴巴 · Qwen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗暂未找到匹配模型
可以调整厂商、分类或输入输出条件；新模型正持续收录。
COST EXPLORER
好模型，也要算好成本。
调整月度 Token 用量，直观比较不同模型的预估 API 开支。
1 M = 100 万 Token · 美元计价
仅比较同一渠道的基础文本 Token 报价
仅比较同一渠道的基础文本 Token 报价
使用已采集且单位可比的 USD / 百万 Token 渠道报价。报价为采集时快照；不计缓存优惠、阶梯价、推理额外输出与税费，请以来源的当前报价为准。
MODEL HANDBOOK
读懂模型，再做选择
API 价格应该怎么比较？+
先区分输入、输出和缓存价格，再使用同一任务和用量估算总费用。图像、音频和视频可能按张、时长或分辨率计费，不能直接与 Token 单价比较。
开放权重，就代表可以免费商用吗？+
不一定。必须逐一核对具体模型版本的许可证、商用限制及使用政策。自己部署还需要考虑显存、推理资源和运维费用。
排行榜第一，就是最适合我的模型吗？+
榜单取决于测试任务、版本与评测方法。建议用实际业务样本比较准确性、时延、稳定性和成本，再选择模型。