**********DeepSeek V4 MoE HF Launches Pro-Base/Collections & Distillation Tease****** [developing]
Key Questions
What is DeepSeek V4?
DeepSeek V4 includes models like Flash/Pro/Pro-Base, which are 1.6T/862B parameter MIT open Mixture-of-Experts (MoE) models supporting 1M context length with Hybrid Attention. They excel in SOTA coding and agents. Fresh Hugging Face collections and Unsloth quants are now available.
What are the performance highlights of DeepSeek V4?
South China Morning Post reports impressive gains, ranking it 2nd among open-source models behind Kimi K2.6. However, it has high 94% hallucinations and lags behind US closed models. It shows strengths in efficiency, KV cache, and Ascend hardware.
Where can I access DeepSeek V4 models?
The models are available in fresh HF collections with Unsloth quants. They support cheap vLLM/HF indie wrappers for B2C/B2B SaaS amid the Chinese OSS surge versus Kimi/Qwen.
What are the key capabilities of DeepSeek V4?
DeepSeek V4 launches with enhanced long-context inference capabilities. It features advanced AI advancements as per DeepSeek AI News and shocks the world with its performance, as noted in related videos.
Is DeepSeek V4 considered underwhelming or underrated?
According to South China Morning Post, DeepSeek V4 shows 'impressive' gains on benchmarks despite some criticisms. It reinforces efficiency for indie SaaS applications.
DeepSeek V4 Flash/Pro/Pro-Base (1.6T/862B MIT open MoE 1M ctx Hybrid Attention SOTA coding/agents) fresh HF collections/Unsloth quants; SCMP reports impressive gains (2nd open-source behind Kimi K2.6) but high 94% hallucinations/lags US closed, efficiency/KV cache/Ascend reinforces cheap vLLM/HF indie B2C/B2B SaaS wrappers amid Chinese OSS surge vs Kimi/Qwen.