What are Open Source Chat Models?
Open source chat models are specialized large language models designed for conversational AI and dialogue applications. Using advanced deep learning architectures like Mixture-of-Experts (MoE) and transformer designs, they excel at understanding context, maintaining coherent conversations, and providing helpful responses across diverse topics. These models democratize access to powerful conversational AI, enabling developers to build chatbots, virtual assistants, and interactive applications. They foster collaboration, accelerate innovation in dialogue systems, and provide transparent alternatives to closed-source solutions for both research and commercial applications.
DeepSeek-V3
DeepSeek-V3-0324 utilizes the same base model as the previous DeepSeek-V3-1226, with improvements made only to the post-training methods. The new V3 model incorporates reinforcement learning techniques from the training process of the DeepSeek-R1 model, significantly enhancing its performance on reasoning tasks. It has achieved scores surpassing GPT-4.5 on evaluation sets related to mathematics and coding. Additionally, the model has seen notable improvements in tool invocation, role-playing, and casual conversation capabilities.
DeepSeek-V3: Advanced Conversational AI with Enhanced Reasoning
DeepSeek-V3-0324 represents the cutting edge of open source conversational AI, featuring a massive 671B parameter Mixture-of-Experts architecture. This model incorporates advanced reinforcement learning techniques that significantly enhance performance on reasoning tasks, mathematics, and coding discussions. With its 131K context length, DeepSeek-V3 excels in extended conversations while maintaining coherence and relevance. The model demonstrates notable improvements in tool invocation, role-playing scenarios, and casual conversation capabilities, making it ideal for sophisticated chat applications that require both depth and versatility.
Pros
- Massive 671B parameter MoE architecture for superior performance.
- Enhanced reasoning capabilities through reinforcement learning.
- Excellent performance in mathematics and coding conversations.
Cons
- Higher computational requirements due to large parameter count.
- More expensive inference costs for high-volume applications.
Why We Love It
- It combines massive scale with advanced training techniques to deliver exceptional conversational AI capabilities across technical and casual dialogue scenarios.
Qwen3-235B-A22B
Qwen3-235B-A22B is the latest large language model in the Qwen series, featuring a Mixture-of-Experts (MoE) architecture with 235B total parameters and 22B activated parameters. This model uniquely supports seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue). It demonstrates significantly enhanced reasoning capabilities, superior human preference alignment in creative writing, role-playing, and multi-turn dialogues.
Qwen3-235B-A22B: Versatile Chat Model with Dual-Mode Intelligence
Qwen3-235B-A22B stands out as a revolutionary conversational AI model that seamlessly switches between thinking and non-thinking modes. With 235B total parameters and 22B activated through its efficient MoE architecture, this model delivers exceptional performance in both complex reasoning tasks and everyday dialogue. The model excels in creative writing, role-playing scenarios, and multi-turn conversations while supporting over 100 languages and dialects. Its superior human preference alignment makes it particularly effective for applications requiring natural, engaging interactions with precise tool integration capabilities.
Pros
- Dual-mode operation for both complex reasoning and casual chat.
- Efficient MoE design with 22B activated parameters.
- Superior human preference alignment and multilingual support.
Cons
- Complex architecture may require specialized deployment knowledge.
- Higher pricing tier for premium conversational features.
Why We Love It
- It offers the perfect balance of efficiency and capability with its unique dual-mode system, making it ideal for diverse conversational AI applications.
OpenAI gpt-oss-120b
gpt-oss-120b is OpenAI's open-weight large language model with ~117B parameters (5.1B active), using a Mixture-of-Experts (MoE) design and MXFP4 quantization to run on a single 80 GB GPU. It delivers o4-mini-level or better performance in reasoning, coding, health, and math benchmarks, with full Chain-of-Thought (CoT), tool use, and Apache 2.0-licensed commercial deployment support.
OpenAI gpt-oss-120b: Efficient Open-Weight Chat Model
OpenAI's gpt-oss-120b represents a breakthrough in accessible high-performance chat models, featuring an efficient MoE architecture with 117B total parameters and only 5.1B active parameters. Designed with MXFP4 quantization, this model can run on a single 80 GB GPU while delivering performance comparable to much larger models. With full Chain-of-Thought reasoning capabilities, comprehensive tool use support, and Apache 2.0 licensing, it's perfect for commercial chat applications. The model excels in reasoning, coding assistance, health-related conversations, and mathematical problem-solving within dialogue contexts.
Pros
- Highly efficient with only 5.1B active parameters.
- Can run on a single 80 GB GPU with MXFP4 quantization.
- Apache 2.0 license for commercial deployment.
Cons
- Smaller active parameter count may limit performance on very complex tasks.
- Newer model with less community adoption compared to established alternatives.
Why We Love It
- It democratizes access to high-quality conversational AI with its efficient architecture and commercial-friendly licensing, perfect for deployment at scale.
Chat Model Comparison
In this table, we compare 2025's leading open source chat models, each with unique strengths for conversational AI applications. DeepSeek-V3 offers maximum capability with its massive parameter count, Qwen3-235B-A22B provides versatile dual-mode intelligence, while OpenAI's gpt-oss-120b delivers efficient performance with commercial-friendly licensing. This side-by-side comparison helps you choose the right conversational AI model for your specific chat application needs.
| Number | Model | Developer | Architecture | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | DeepSeek-V3 | deepseek-ai | MoE (671B) | $1.13/M (out) $0.27/M (in) | Maximum reasoning capability |
| 2 | Qwen3-235B-A22B | Qwen3 | MoE (235B/22B) | $1.42/M (out) $0.35/M (in) | Dual-mode intelligence |
| 3 | OpenAI gpt-oss-120b | OpenAI | MoE (120B/5.1B) | $0.45/M (out) $0.09/M (in) | Efficient & commercial-ready |
Frequently Asked Questions
Our top three picks for 2025 are DeepSeek-V3, Qwen3-235B-A22B, and OpenAI gpt-oss-120b. Each of these models stood out for their exceptional conversational abilities, innovative architectures, and unique approaches to solving challenges in open source chat AI applications.
Our analysis shows different leaders for various needs. DeepSeek-V3 is ideal for applications requiring maximum reasoning capability and complex conversations. Qwen3-235B-A22B excels in versatile scenarios with its dual-mode operation and multilingual support. OpenAI gpt-oss-120b is perfect for cost-effective deployment with commercial licensing requirements.