Moe Model

Summary: DeepSeek V4.1 Flash in 30 Seconds DeepSeek-V4.1-Flash shipped on September 10, 2026. License is MIT, weights are on Hugging Face. 552B backbone parameters, but only 8B active while reading input and 16B while generating output. That asymmetry is the whole point of the model. New architecture: Causal Encoder-Decoder (CED). 40 layers, 20 causal encoder plus 20 decoder. The decoder’s global KV cache is projected from the encoder’s final hidden states instead of from each decoder layer’s own. Result: a global KV cache of 890 bytes per token. One quarter of V4-Flash, and 1/437 of DeepSeek-V1. Natively multimodal: images go through DeepSeek-ViT, a vision encoder trained from scratch, from the very start of language-model pre-training. Pre-training corpus is 45T tokens. Beats Claude Opus 5 on several agentic benchmarks: 90.6 vs 89.1 on Terminal-Bench 2.1, 74.2 vs 74.0 on DeepSWE v1.1, 54.8 vs 50.3 on AutomationBench. Reasoning effort is a continuous 1-100 dial, not an on/off thinking toggle. API pricing is $0.15 in / $0.60 out per million tokens off-peak, double that at peak. Roughly one twentieth of Claude Opus 5’s output price. DeepSeek is retiring V4 Pro: from September 14, 2026, deepseek-v4-pro requests get routed to V4.1 Flash and billed at Flash rates. Everyone in the open-weight race this year is chasing the same two numbers: active parameters and KV cache. The first decides what each token costs, the second decides how much memory a long context eats. GLM-5.3-Flash answered with hybrid attention, Qwen3.8-Flash-Next with 6B active parameters. ...

Summary: DeepSeek V4 Pro in 30 Seconds DeepSeek V4 Pro 0813 went generally available on August 13, 2026. No press release, no blog post, just one line in a changelog. 1.7 trillion parameters, mixture-of-experts architecture, 1M token context, 384K token output ceiling. The weights are on Hugging Face under the MIT license. You can download them, modify them and ship them in a commercial product. Official scores are bold: 87.9 on Terminal Bench 2.1, 62.7 on DeepSWE. Independent testing is more restrained: 53 on the Artificial Analysis Intelligence Index. Pricing is $0.435 in and $0.87 out per million tokens. From August 16 the off-peak rate is half of that. The catch: its smaller sibling V4 Flash scores 52 on the same index at one third of the price. You are paying triple for one point. Model launches have settled into a ritual: a teaser video, a wall of benchmark charts, an excited founder post. DeepSeek skipped all of it. DeepSeek V4 Pro 0813 went generally available on August 13, 2026 with no announcement at all. One line landed in the API changelog and the weights appeared on Hugging Face. ...

Hello everyone! 😁 Today we’re diving into a very exciting topic. Google DeepMind just dropped a massive bomb in the open source AI world: Gemma 4 models are officially released! 🚀 You know how people keep saying “open source models are nice but they can’t even compete with closed source ones”… With Gemma 4, you might want to rethink that claim. This model family delivers the most impressive intelligence-per-parameter we’ve ever seen. ...