DeepSeek V4 vs ChatGPT-5 vs Claude 4

What You Will Learn

• The official specifications for DeepSeek V4-Pro and V4-Flash, including parameter counts and context limits
• How DeepSeek V4 API pricing compares across input and output tokens
• The reasoning effort modes available in the DeepSeek API
• How OpenAI describes GPT-5.5 capabilities for coding and multi-step tool use

DeepSeek V4 official release specifications

DeepSeek released the preview version of its DeepSeek V4 series on April 24, 2026. The release includes two Mixture-of-Experts models: DeepSeek-V4-Pro and DeepSeek-V4-Flash. Both models support a context length of one million tokens and are available through the official API, which supports both OpenAI ChatCompletions and Anthropic API formats.

DeepSeek-V4-Pro is a 1.6-trillion parameter model with 49 billion activated parameters. DeepSeek-V4-Flash is a smaller variant with 284 billion total parameters and 13 billion activated parameters. The official documentation states that the 1M-token context is the default standard across official DeepSeek services, enabled by an architectural change combining Compressed Sparse Attention and Heavily Compressed Attention.

The models and their weights are licensed under the MIT License, which allows for free commercial use and self-hosting. DeepSeek notes that the legacy deepseek-chat and deepseek-reasoner endpoints will be retired in July 2026, requiring developers to migrate to the deepseek-v4-pro or deepseek-v4-flash endpoints.

DeepSeek V4 reasoning effort modes

Both DeepSeek V4 models support three reasoning effort modes that control how the model processes a prompt before outputting the final answer. These modes are accessed via the API using the reasoning_effort parameter, and they replace traditional sampling controls. The official documentation states that temperature, top_p, presence_penalty, and frequency_penalty parameters have no effect when thinking mode is enabled.

The Non-think mode is designed for fast, intuitive responses and routine daily tasks. The Think High mode applies conscious logical analysis and is recommended for complex problem-solving and planning. The Think Max mode pushes the model's reasoning to its fullest extent, which DeepSeek recommends pairing with a context window of at least 384K tokens.

When using thinking mode in multi-turn conversations or tool calls, the API returns the chain-of-thought reasoning in a reasoning_content parameter alongside the final content. Developers must properly pass this reasoning content back to the API during tool calls to maintain the reasoning context.

How reasoning effort changes model selection

Reasoning effort is a practical way to match the model to the task. Non-think is appropriate when speed matters more than extended analysis, while Think High and Think Max are better suited to complex coding, planning, and tool-driven work. The best choice depends on the required accuracy, response time, and token budget.

DeepSeek V4 vs ChatGPT-5 vs Claude 4 official benchmarks

Comparing DeepSeek V4 vs ChatGPT-5 vs Claude 4 requires examining the official benchmarks published by each vendor. DeepSeek reports that V4-Pro Max achieves an 80.6 percent resolved score on SWE-bench Verified and a Codeforces rating of 3206. These figures represent the model's maximum reasoning effort mode on specific coding and algorithmic evaluations.

OpenAI introduced GPT-5.5 on April 23, 2026, describing it as a model built for complex professional work, including writing code, researching online, and operating software across multiple tools. OpenAI's published evaluations report GPT-5.5 scoring 82.7 percent on Terminal-Bench 2.0, 78.7 percent on OSWorld-Verified, and 84.4 percent on BrowseComp. In the same evaluation table, OpenAI listed Claude Opus 4.7 at 69.4 percent on Terminal-Bench 2.0 and 78.0 percent on OSWorld-Verified.

Anthropic introduced Claude Opus 4 and Claude Sonnet 4 in May 2025. The official announcement described Claude Opus 4 as the world's best coding model with sustained performance on long-running tasks. Anthropic reported Opus 4 achieving 72.5 percent on SWE-bench Verified under its specific test conditions. Because each vendor uses different evaluation setups, sampling methods, and tool environments, no single benchmark score definitively ranks the models across all workloads.

For broader background on the model landscape, consult the list of large language models on Wikipedia.

DeepSeek API pricing comparison

DeepSeek bills its API usage based on the total number of input and output tokens, measured per one million tokens. The official pricing documentation specifies that the V4-Flash model is the economical choice, while the V4-Pro model is priced for its larger parameter scale and advanced capabilities.

The API pricing structure includes peak and off-peak rates. Off-peak rates apply during specific UTC hours and are half the cost of peak rates. This structure encourages developers to shift non-urgent batch processing or bulk evaluations to off-peak windows to reduce costs.

Because the official pricing table is subject to change, developers should check the DeepSeek API documentation for the exact current rates before calculating a production budget. The cost difference between V4-Flash and V4-Pro is substantial, with V4-Flash designed to handle standard tasks and simple agent workflows at a much lower cost per token.

Conclusion: choosing between the models for production workloads

The choice between DeepSeek V4, GPT-5.5, and Claude 4 depends on the specific workload, budget, and deployment requirements. DeepSeek V4-Pro offers high-level coding and reasoning performance with the option for self-hosting via its MIT license, making it suitable for teams with data privacy constraints or existing on-premises GPU clusters.

GPT-5.5 is positioned by OpenAI for complex, multi-step tasks that require navigating through ambiguity and using tools. Its performance on agentic benchmarks suggests it is designed for workloads that require the model to plan, execute, and verify its own work across different software environments.

Claude Opus 4.7 remains a strong option for enterprise environments that prioritize reliability and sustained performance on long-running tasks. Teams must weigh the API costs, required context windows, and ecosystem integrations when selecting the primary model for their application.