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DeepSeek V4

Model ● Covered in 10 stories + Follow

DeepSeek V4 is an open-weight AI model that has been covered as an efficiency- and scale-focused release, including reports that it supports 1M-token context windows and incorporates architectural techniques aimed at reducing memory and compute costs for long-context processing. Recent coverage also describes DeepSeek V4’s deployment in the inference stack ecosystem, including reported token-cost reductions on NVIDIA’s Blackwell platform, as well as its availability through Hugging Face’s supported inference providers via DeepInfra. Other coverage places DeepSeek V4 in a broader discussion of open models’ lower per-token costs and ongoing evaluation of how open releases compare to frontier and proprietary alternatives.

Updated 17 September 2026

Specifications

No specifications recorded yet.

Latest developments

The Sequence Learning Loop - Issue #921: Learn About DeepSeek New Model, the Env Harness Paper and the Amazing Etched TheSequence · 3 weeks ago · 15
📈 Data to start your week Exponential View · 1 month ago · 23
Agentic Misalignment in Summer 2026 Anthropic · 2 months ago · 12
How NVIDIA’s Inference Software Stack Powers the Lowest Token Cost NVIDIA · 2 months ago · 36 The Unbearable Cheapness of Open Weight Models jamesoclaire.com · 2 months ago · 12
Frontier post-training recipe review with Finbarr Timbers Interconnects · 3 months ago · 40
Latest open artifacts (#21): Open model bonanza! Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, GLM-5.1 & others. On CAISI's V4 assessment. Interconnects · 4 months ago · 34
Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention Ahead of AI · 4 months ago · 36

Timeline

Month Quarter Year

August 2026

July 2026

Moonshot AI releases Kimi K3, a 2.8 trillion parameter open-weight model achieving frontier-class performance Open source release

June 2026

Multiple AI companies release open-source models as pricing competition intensifies Open source release

May 2026

Amazon researchers present framework for optimizing LLM architecture to improve inference speed without sacrificing accuracy Research publication

April 2026

Relationships

Products & technology

  • DeepSeek develops this model · 5 sources
  • NVIDIA integrated with this model · 1 source
  • Hugging Face deploys this model · 1 source

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