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DeepSeek-V4-Flash-0731

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LLMs#16AI Models & LLMsOpen source · Web

DeepSeek-V4-Flash-0731 is an advanced language model that enhances agentic capabilities. It outperforms previous versions and is competitive with top proprietary models, offering improved performance across various benchmarks.

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DeepSeek-V4-Flash-0731 screenshot
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Description

DeepSeek-V4-Flash-0731 is the latest release in the DeepSeek series, designed to enhance agentic capabilities significantly. This model supersedes the preview version, DeepSeek-V4-Flash, by incorporating a speculative decoding module similar to DeepSeek-V4-Flash-DSpark. Despite having a smaller activated parameter count, DeepSeek-V4-Flash-0731 outperforms its predecessor, DeepSeek-V4-Pro (Preview), across multiple benchmarks.

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The model excels in various benchmarks, including Terminal Bench 2.1, NL2Repo, Cybergym, and DeepSWE, demonstrating its competitiveness with leading proprietary models. For instance, it scores 82.7 on Terminal Bench 2.1, surpassing the preview version's 61.8 and DeepSeek-V4-Pro's 72.1. It also shows strong performance in NL2Repo and Cybergym, with scores of 54.2 and 76.7, respectively.

DeepSeek-V4-Flash-0731 supports three levels of reasoning effort—low, high, and max—allowing users to control the deliberation the model undertakes before providing answers. The model is designed for easy deployment with vLLM and SGLang, offering detailed instructions for local deployment and model weight conversion.

The model is licensed under the MIT License, ensuring open access to its capabilities. Users can explore its functionalities through a dedicated encoding folder that provides Python scripts and test cases for encoding messages in an OpenAI-compatible format. This release does not include a Jinja-format chat template but offers comprehensive documentation for message encoding and output parsing.

  • CategoryAI Models & LLMs
  • Pricing ModelOpen source
  • DeploymentCloud, Self-hosted
  • PlatformsWeb

DeepSeek-V4-Flash-0731 Highlights

  • Enhanced agentic capabilities

  • Speculative decoding module

  • Competitive benchmark performance

  • Three reasoning effort levels

  • OpenAI-compatible encoding

  • MIT License

  • Local deployment support

  • Detailed documentation

Getting Started with DeepSeek-V4-Flash-0731

  1. Access model page: Visit the Hugging Face model page

  2. Authenticate: Log in to your Hugging Face account

  3. Configure: Set reasoning effort and decoding parameters

  4. Send prompts: Use the model with configured settings

  5. Fine-tune: Adjust parameters for specific tasks

DeepSeek-V4-Flash-0731's Use Cases

  • Advanced Text Analysis
  • Benchmark Testing
  • Agentic Scenarios
  • Open Source Projects
  • Research and Development

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