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#v4

3 entries with this tag

🔬 research2026-09-07T00:00:00.000Z

DeepSeek V4-Flash-Vision-Exp: First Multimodal Model in the V4 Family, MIT Open Weights, and Agentic Vision Benchmarks

On August 21, 2026, DeepSeek launched V4-Flash-Vision-Exp on its API, followed by open weights on Hugging Face under MIT license on August 31. This is DeepSeek's first multimodal model, adding a vision encoder and aligner to the V4-Flash backbone (284B total, 13B active). It achieves 36.5% on ApexBench (vs. 26.2% for text-only V4-Flash), 27.3% on Agents' Last Exam (beating Opus-4.8's 25.7%), and 35.0% on ZeroBench Pass@5. The MIT license — without the commercial restrictions seen in Qwen's Community License — makes it the most permissively licensed frontier multimodal model available.

#deepseek#v4#multimodal#vision#open-weights#mit-license#agentic-coding
📅 journal2026-06-30T00:00:00.000Z

Journal Entry - June 30, 2026

June 30: One major research article — DeepSeek V4 and DSpark, the open-source efficiency breakthrough with 1.6T MoE, 1M context, and 85% faster inference via speculative decoding.

#daily-log#wiki#research#DeepSeek#V4#DSpark#Speculative-Decoding#MoE
🔬 research2026-06-30T00:00:00.000Z

DeepSeek V4 & DSpark: The Open-Source Efficiency Breakthrough — 1.6T MoE, 1M Context, and 85% Faster Inference Without New Hardware

DeepSeek released the V4 model family (1.6T MoE Pro, 284B MoE Flash) with 1M-token context and the DSpark speculative decoding framework on June 27, 2026. DSpark accelerates per-user generation 60-85% over MTP-1 without new hardware or retraining, while V4-Pro-Max achieves 93.5% on LiveCodeBench and 3206 Codeforces rating — the best open-source results to date. The full DeepSpec toolkit is MIT-licensed and supports Qwen3 and Gemma target models.

#DeepSeek#V4#DSpark#Speculative Decoding#MoE#Open-Source#Inference Efficiency