---
title: "DeepSeek's new V4.1-Flash model cuts memory needs for AI agents"
url: https://www.parallelquant.com/posts/deepseek-s-new-v4-1-flash-model-cuts-memory-needs-for-ai-agents-85f0bc
source_name: "The Decoder"
source_url: https://the-decoder.com/new-deepseek-model-v4-1-flash-cuts-memory-needs-for-ai-agents/
published: 2026-09-10T12:40:51.000Z
topics: ["open source"]
publisher: "Parallel Quant"
---

# DeepSeek's new V4.1-Flash model cuts memory needs for AI agents

*2026-09-10 · Source: [The Decoder](https://the-decoder.com/new-deepseek-model-v4-1-flash-cuts-memory-needs-for-ai-agents/)*

DeepSeek released V4.1-Flash, a 552-billion-parameter multimodal model that activates only 16 billion parameters per token and cuts key-value cache memory to a quarter of its predecessor. On the DeepSWE coding benchmark it narrowly beats Opus 5 and GPT-5.6 Sol, and it ships under the MIT license.

**Why it matters:** Lower KV-cache memory directly cuts the cost of running long-context agents, which is often the real deployment bottleneck rather than raw model quality. An MIT-licensed model beating closed frontier models on a coding benchmark keeps pricing and licensing pressure on Western labs.

**Topics:** open source

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Read the original: https://the-decoder.com/new-deepseek-model-v4-1-flash-cuts-memory-needs-for-ai-agents/
Canonical: https://www.parallelquant.com/posts/deepseek-s-new-v4-1-flash-model-cuts-memory-needs-for-ai-agents-85f0bc
Published by Parallel Quant — https://www.parallelquant.com