DeepSeek-V2 vs. DeepSeek-V4-Pro Comparison


DeepSeek-V2 DeepSeek	DeepSeek-V4-Pro DeepSeek	+	+
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About DeepSeek-V2 is a state-of-the-art Mixture-of-Experts (MoE) language model introduced by DeepSeek-AI, characterized by its economical training and efficient inference capabilities. With a total of 236 billion parameters, of which only 21 billion are active per token, it supports a context length of up to 128K tokens. DeepSeek-V2 employs innovative architectures like Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache and DeepSeekMoE for cost-effective training through sparse computation. This model significantly outperforms its predecessor, DeepSeek 67B, by saving 42.5% in training costs, reducing the KV cache by 93.3%, and enhancing generation throughput by 5.76 times. Pretrained on an 8.1 trillion token corpus, DeepSeek-V2 excels in language understanding, coding, and reasoning tasks, making it a top-tier performer among open-source models.	About DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience AI researchers, developers, and tech enthusiasts seeking a high-performance, cost-efficient open-source language model for advanced natural language processing, coding, and reasoning tasks	Audience AI researchers, developers, and enterprises seeking a powerful open-source language model for large-scale reasoning, coding, and long-context AI applications
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Not Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Not Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Open source Free Version Supported Free Trial Not Supported	Pricing $0.435 per 1M tokens (input) $0.435 per 1 million input tokens (cache miss), $0.003625 per 1 million input tokens (cache hit), and $0.87 per 1 million output tokens Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 5.0 / 5 Read all reviews
	Pros & Cons from Real Users Pros DeepSeek-V4-Pro is one of those models I keep coming back to because it handles serious work without feeling ridiculously expensive. For coding, repo analysis, long debugging threads, and agent-style workflows, the 1M-token context window is a huge advantage. I also like that it feels strong across both reasoning and implementation. I can use it to think through architecture, explain a messy bug, generate a fix, write tests, and then sanity-check the tradeoffs without constantly switching models. The Pro-Max reasoning mode is especially useful when I need it to slow down and really work through something. It is not the mode I would use for every quick answer, but for hard technical problems, it gives the model a lot more room to reason. The open-weight angle is a big plus too. As someone who uses it heavily, I like having more flexibility than a purely closed API model gives me. Cons It is still not something I would run on autopilot. For production code, I always review diffs, run tests, and check edge cases because even strong models can make confident mistakes. It can also be overkill for simple tasks. If I just need a quick explanation, small script, or lightweight edit, DeepSeek-V4-Flash may be the better fit. The size is another consideration. Open weights are great, but self-hosting a 1.6T-parameter MoE model is not casual infrastructure.
Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information DeepSeek Founded: 2023 China deepseek.com	Company Information DeepSeek Founded: 2023 China deepseek.com
Alternatives DeepSeek-V4 DeepSeek	Alternatives Gemini 4 Argon Google
DeepSeek-V4-Pro DeepSeek	Claude Sonnet 5.5 Anthropic
DeepSeek-V4.1-Flash-1017 DeepSeek	Claude Fable 5.1 Anthropic
DeepSeek-V4-Flash DeepSeek	DeepSeek-V4 DeepSeek
DeepSeek R1 DeepSeek View All	DeepSeek-V4-Flash DeepSeek View All
Categories AI Coding Models Supported AI Models Supported Large Language Models Supported Open-Weight AI Models Supported	Categories AI Coding Models Supported AI Models Supported Large Language Models Supported Open-Weight AI Models Supported

Integrations .NET Not Supported C Not Supported C# Not Supported Cheaper Inference Not Supported ClinePass Not Supported Dart Not Supported DeepSeek Harness Not Supported Go Not Supported Java Not Supported Kotlin Not Supported Lua Not Supported Objective-C Not Supported OfoxAI Not Supported OpenClaw Not Supported Oxlo.ai Not Supported PHP Not Supported Reasonix Not Supported Together AI Not Supported Vercel AI Gateway Not Supported XML Not Supported Show More Integrations View All 1 Integration	Integrations .NET Supported C Supported C# Supported Cheaper Inference Supported ClinePass Supported Dart Supported DeepSeek Harness Supported Go Supported Java Supported Kotlin Supported Lua Supported Objective-C Supported OfoxAI Supported OpenClaw Supported Oxlo.ai Supported PHP Supported Reasonix Supported Together AI Supported Vercel AI Gateway Supported XML Supported Show More Integrations View All 44 Integrations
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