- General Users & Chat Enthusiasts: Engage in natural dialogue across multiple formats—text, images, voice, and video.
- Content Creators & Designers: Generate visuals, analyze documents, interpret images, or extract information from media.
- Developers & Enterprises: Build multimodal assistants with capabilities like agent behavior, tool integration, and reasoning.
- Analysts & Researchers: Perform document Q&A, chart interpretation, code debugging, or audio transcription.
- Language & Audio Users: Translate, transcribe, and analyze language, speech, and music with Qwen-Audio support.
How to Use Qwen Chat?
- Choose a Model Variant: Options include Qwen-7B-Chat, Qwen1.5-7B-Chat, Qwen2.5-Max, Qwen-VL, Qwen-Audio, and Qwen2.5-Omni, based on needed modalities.
- Access via Interface: Use the web chat platform or call via API (OpenAI-compatible) through Alibaba Cloud Model Studio.
- Provide Mixed Inputs: Send text, images, audio, or video interleaved in one conversation.
- Activate Tools & Agents: Enable reasoning ("thinking" mode), use functions or agent tools for tasks like data retrieval or translation.
- Receive Rich Outputs: Get text responses, generated images, document analysis, transcripts, or code—all in chat.
- Multimodal Mastery: Supports text, image, audio, and video in a single assistant.
- Unified Chat Experience: Conduct all modalities via one interface—no separate tools needed.
- High-End Reasoning & Tool Use: Qwen3 introduces a “thinking” mode and reasoning budget control for depth.
- Open-Source Backing: Most Qwen models are released under Apache 2.0 or similar permissive licenses.
- High Performance: Qwen2.5-Max and QwQ-32B rival top open and closed models in benchmarks for reasoning, coding, math.
- Truly multimodal—text, image, audio, and video all in one assistant
- “Thinking” mode for deeper chain-of-thought reasoning
- Open-source, widely accessible with flexible deployment
- Enterprise-ready via Alibaba Cloud API and Model Studio
- Strong performance in benchmarks for reasoning and coding
- Full multimodal capability limited by user’s chosen variant and resource access
- Some models may require high compute or cloud usage costs
- Advanced features may need Alibaba Cloud account or premium setup
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DeepSeek V3 is the latest flagship Mixture‑of‑Experts (MoE) open‑source AI model from DeepSeek. It features 671 billion total parameters (with ~37 billion activated per token), supports up to 128K context length, and excels across reasoning, code generation, language, and multimodal tasks. On standard benchmarks, it rivals or exceeds proprietary models—including GPT‑4o and Claude 3.5—as a high-performance, cost-efficient alternative.
DeepSeek-V3
DeepSeek V3 is the latest flagship Mixture‑of‑Experts (MoE) open‑source AI model from DeepSeek. It features 671 billion total parameters (with ~37 billion activated per token), supports up to 128K context length, and excels across reasoning, code generation, language, and multimodal tasks. On standard benchmarks, it rivals or exceeds proprietary models—including GPT‑4o and Claude 3.5—as a high-performance, cost-efficient alternative.
DeepSeek-V3-0324
DeepSeek V3 (0324) is the latest open-source Mixture-of-Experts (MoE) language model from DeepSeek, featuring 671B parameters (37B active per token). Released in March 2025 under the MIT license, it builds on DeepSeek V3 with major enhancements in reasoning, coding, front-end generation, and Chinese proficiency. It maintains cost-efficiency and function-calling support.
DeepSeek-V3-0324
DeepSeek V3 (0324) is the latest open-source Mixture-of-Experts (MoE) language model from DeepSeek, featuring 671B parameters (37B active per token). Released in March 2025 under the MIT license, it builds on DeepSeek V3 with major enhancements in reasoning, coding, front-end generation, and Chinese proficiency. It maintains cost-efficiency and function-calling support.
DeepSeek-V3-0324
DeepSeek V3 (0324) is the latest open-source Mixture-of-Experts (MoE) language model from DeepSeek, featuring 671B parameters (37B active per token). Released in March 2025 under the MIT license, it builds on DeepSeek V3 with major enhancements in reasoning, coding, front-end generation, and Chinese proficiency. It maintains cost-efficiency and function-calling support.
grok-3-fast-latest
Grok 3 Fast is xAI’s speed-optimized variant of their flagship Grok 3 model, offering identical output quality with lower latency. It leverages the same underlying architecture—including multimodal input, chain-of-thought reasoning, and large context—but serves through optimized infrastructure for real-time responsiveness. It supports up to 131,072 tokens of context.
grok-3-fast-latest
Grok 3 Fast is xAI’s speed-optimized variant of their flagship Grok 3 model, offering identical output quality with lower latency. It leverages the same underlying architecture—including multimodal input, chain-of-thought reasoning, and large context—but serves through optimized infrastructure for real-time responsiveness. It supports up to 131,072 tokens of context.
grok-3-fast-latest
Grok 3 Fast is xAI’s speed-optimized variant of their flagship Grok 3 model, offering identical output quality with lower latency. It leverages the same underlying architecture—including multimodal input, chain-of-thought reasoning, and large context—but serves through optimized infrastructure for real-time responsiveness. It supports up to 131,072 tokens of context.
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Llama 4 Maverick is Meta’s powerful mid-sized model in the Llama 4 series, released April 5, 2025. Built with a mixture-of-experts (MoE) architecture featuring 17 B active parameters (out of 400 B total) and 128 experts, it supports a 1 million-token context window and native multimodality for text and image inputs. It ranks near the top of competitive benchmarks—surpassing GPT‑4o and Gemini 2.0 Flash in reasoning, coding, and visual tasks.
Llama 4 Maverick is Meta’s powerful mid-sized model in the Llama 4 series, released April 5, 2025. Built with a mixture-of-experts (MoE) architecture featuring 17 B active parameters (out of 400 B total) and 128 experts, it supports a 1 million-token context window and native multimodality for text and image inputs. It ranks near the top of competitive benchmarks—surpassing GPT‑4o and Gemini 2.0 Flash in reasoning, coding, and visual tasks.
Llama 4 Behemoth is Meta’s ultimate “teacher” model within the Llama 4 series, currently in preview and training. Featuring an enormous 2 trillion total parameters with 288 billion active in a Mixture-of-Experts architecture (16 experts), it's designed to push the limits of multimodal reasoning, STEM, and long-context tasks. Initially slated for April 2025, its release has been postponed to fall 2025 or later due to internal performance and alignment concerns.
Llama 4 Behemoth is Meta’s ultimate “teacher” model within the Llama 4 series, currently in preview and training. Featuring an enormous 2 trillion total parameters with 288 billion active in a Mixture-of-Experts architecture (16 experts), it's designed to push the limits of multimodal reasoning, STEM, and long-context tasks. Initially slated for April 2025, its release has been postponed to fall 2025 or later due to internal performance and alignment concerns.
Llama 4 Behemoth is Meta’s ultimate “teacher” model within the Llama 4 series, currently in preview and training. Featuring an enormous 2 trillion total parameters with 288 billion active in a Mixture-of-Experts architecture (16 experts), it's designed to push the limits of multimodal reasoning, STEM, and long-context tasks. Initially slated for April 2025, its release has been postponed to fall 2025 or later due to internal performance and alignment concerns.
DeepSeek R1 Distill Qwen‑32B is a 32-billion-parameter dense reasoning model released in early 2025. Distilled from the flagship DeepSeek R1 using Qwen 2.5‑32B as a base, it delivers state-of-the-art performance among dense LLMs—outperforming OpenAI’s o1‑mini on benchmarks like AIME, MATH‑500, GPQA Diamond, LiveCodeBench, and CodeForces rating.
DeepSeek R1 Distill Qwen‑32B is a 32-billion-parameter dense reasoning model released in early 2025. Distilled from the flagship DeepSeek R1 using Qwen 2.5‑32B as a base, it delivers state-of-the-art performance among dense LLMs—outperforming OpenAI’s o1‑mini on benchmarks like AIME, MATH‑500, GPQA Diamond, LiveCodeBench, and CodeForces rating.
DeepSeek R1 Distill Qwen‑32B is a 32-billion-parameter dense reasoning model released in early 2025. Distilled from the flagship DeepSeek R1 using Qwen 2.5‑32B as a base, it delivers state-of-the-art performance among dense LLMs—outperforming OpenAI’s o1‑mini on benchmarks like AIME, MATH‑500, GPQA Diamond, LiveCodeBench, and CodeForces rating.
DeepSeek-R1-0528
DeepSeek R1 0528 is the May 28, 2025 update to DeepSeek’s flagship reasoning model. It brings significantly enhanced benchmark performance, deeper chain-of-thought reasoning (now using ~23K tokens per problem), reduced hallucinations, and support for JSON output, function calling, multi-round chat, and context caching.
DeepSeek-R1-0528
DeepSeek R1 0528 is the May 28, 2025 update to DeepSeek’s flagship reasoning model. It brings significantly enhanced benchmark performance, deeper chain-of-thought reasoning (now using ~23K tokens per problem), reduced hallucinations, and support for JSON output, function calling, multi-round chat, and context caching.
DeepSeek-R1-0528
DeepSeek R1 0528 is the May 28, 2025 update to DeepSeek’s flagship reasoning model. It brings significantly enhanced benchmark performance, deeper chain-of-thought reasoning (now using ~23K tokens per problem), reduced hallucinations, and support for JSON output, function calling, multi-round chat, and context caching.
Editorial Note
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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