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title: DeepSeek’s smaller model just outperformed its own flagship
description: DeepSeek has released DeepSeek-V4-Flash-0731, a smaller model (284B total / 13B activated parameters) that outperforms the earlier V4-Pro preview on several...
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og:description: DeepSeek has released DeepSeek-V4-Flash-0731, a smaller model (284B total / 13B activated parameters) that outperforms the earlier V4-Pro preview on several...
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# DeepSeek’s smaller model just outperformed its own flagship

**[The New Stack](https://daily.dev/sources/newstack)** · 4 min read · 0 upvotes · 0 comments

## Summary

DeepSeek has released DeepSeek-V4-Flash-0731, a smaller model (284B total / 13B activated parameters) that outperforms the earlier V4-Pro preview on several agent-focused benchmarks including Terminal-Bench 2.1 (82.7), DeepSWE (54.4), and Toolathlon-Verified (70.3). The gains come from additional post-training rather than architectural changes, demonstrating that scaling up isn't the only path to better performance. The weights are published on Hugging Face under the MIT license, giving organizations full control to self-host and customize. The model supports OpenAI-compatible APIs and Responses API for agentic workflows, lowering switching costs for teams already using OpenAI-style tooling. Independent testing by Artificial Analysis found slightly lower scores than DeepSeek's reported numbers, so some benchmark claims remain unverified.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://thenewstack.io/deepseek-v4-flash-open-weights>

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#deepseek](https://daily.dev/tags/deepseek), [#llm](https://daily.dev/tags/llm), [#open-source](https://daily.dev/tags/open-source)

[View this post on daily.dev](https://daily.dev/posts/deepseek-s-smaller-model-just-outperformed-its-own-flagship-x7y9ab7jh)

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