DeepSeek V4 Pro 0813 - API Pricing & Providers
Service

DeepSeek V4 Pro 0813 - API Pricing & Providers

deepseek
2026.08.12
·Web·by Mineru
#API#DeepSeek#LLM#OpenRouter#Pricing

Key Points

  • 1DeepSeek V4 Pro 0813 is a large-scale Mixture-of-Experts model featuring 1.6 trillion total parameters and 49 billion activated parameters, optimized for advanced reasoning and coding tasks.
  • 2It supports a massive 1-million-token context window and utilizes a hybrid attention system to enhance efficiency during long-horizon agent workflows and complex codebase analysis.
  • 3Available through OpenRouter, the model offers a cost-effective solution for high-performance inference, with pricing structures designed for competitive accessibility across diverse production workloads.

DeepSeek V4 Pro 0813, released on August 12, 2026, is a large-scale Mixture-of-Experts (MoE) model representing the General Availability (GA) iteration of the DeepSeek V4 Pro series. Architecturally, the model utilizes a total of 1.6T parameters, with 49B parameters activated per forward pass, facilitating a balance between massive knowledge capacity and computational efficiency. A defining technical feature of this iteration is the integration of a hybrid attention system, designed specifically to optimize performance across its 1M-token context window.

The model is engineered for high-complexity tasks, including full-codebase analysis, multi-step automation, and large-scale information synthesis. Its technical infrastructure supports advanced reasoning through configurable effort levels (high and xhigh), where the xhigh setting maps to the maximum available reasoning compute. OpenRouter provides access to the model’s internal reasoning process via the reasoning_details array, allowing developers to observe step-by-step chain-of-thought outputs.

From an operational perspective, the model is highly optimized for production environments, featuring a weighted average input cost of 0.04999permilliontokensandanoutputcostof0.04999 per million tokens and an output cost of0.8698 per million tokens. The inference framework is compatible with both OpenAI and Anthropic API standards, supporting features such as tool calling, structured outputs, and streaming responses. Performance is maintained through continuous monitoring of uptime, which is reported at 100% over the observed 30-day window, and its deployment in professional-grade frontends such as SillyTavern and the Velocity CLI suggests strong utility in agentic and interactive workflows. The model's architecture is rooted in the same lineage as the V4 Flash series, though it distinguishes itself through increased parameter scaling and enhanced long-context handling capabilities.