DeepSeek 2026: el modelo IA que asusta a OpenAI

DeepSeek R1 cuesta 27 veces menos que o1 de OpenAI. ¿Vale la pena migrar? Especificaciones reales de V4, benchmarks y guía de acceso gratis en español.

https://blog.donweb.com/deepseek-modelo-ia-que-es-como-funciona-2026/

#deepseek #modelosia #llmcódigoabierto #deepseekv4 #deepseekr1

DeepSeek Unveils V4 Models, Sparking Debate on Open-Source Frontiers

DeepSeek AI released V4-Pro and V4-Flash open-source models. They claim better coding and math skills. See how they compare to other AI.

#DeepSeekV4, #OpenSourceAI, #LLM, #AICoding, #AIMath

https://newsletter.tf/deepseek-v4-models-open-source-ai-coding-math/

DeepSeek AI has launched V4-Pro and V4-Flash, new open-source AI models. They claim these models are the best for coding and math among open-source options.

#DeepSeekV4, #OpenSourceAI, #LLM, #AICoding, #AIMath
https://newsletter.tf/deepseek-v4-models-open-source-ai-coding-math/

GPT-5.5 vs DeepSeek V4: The April 2026 Developer Comparison

OpenAI dropped GPT-5.5 and DeepSeek released V4-Pro within eight hours of each other on April 24, 2026. Here is the head-to-head benchmark, pricing, and architecture breakdown e...

https://wowhow.cloud/blogs/gpt-5-5-vs-deepseek-v4-developer-comparison-april-2026

#wowhow #gpt55 #deepseekv4 #aimodelcomparison

nanowhale은 DeepSeek‑V4 아키텍처로 처음부터 학습한 약 110M 파라미터 언어모델입니다. 레포에 모델 코드·설정·토크나이저와 사전학습(5K steps on FineWeb‑Edu)·SFT(3K steps on SmolTalk) 스크립트 및 성능 결과가 포함돼 있습니다. MLA, MoE, Hyper‑Connections 등 설계 특징과 bf16 NaN, from_pretrained 재초기화 같은 알려진 이슈도 명시하며 MIT 라이선스로 공개되었습니다.

https://github.com/huggingface/nanowhale

#nanowhale #deepseekv4 #languagemodel #moe #huggingface

I'm now 100% weened off of #Anthropic #Claude. My Max subscription has lapsed and I'm not planning to renew.

I've found I can do everything I want to do with #OpenCode + #HermesAgent as harnesses. I'm using #OpenCodeGo for inference and fail over to #OpenCodeZen when my Go subscription hits a limit.

But with #DeepseekV4 Flash I'm finding it hard to hit that limit. I'm actually getting better outcomes without Claude now.

DEEPSEEK’S V4 CONTINUES CHINA’S OPEN-SOURCE AI ASSERTION

DeepSeek's new V4 AI model uses Huawei chips, not Nvidia. It aims to improve open-source AI in China and globally. Learn how it affects AI development.

#DeepSeekV4, #OpenSourceAI, #ChineseAI, #HuaweiChips, #AICapabilities

https://newsletter.tf/deepseek-v4-ai-china-chips-open-source/

DeepSeek's new V4 AI model is now using Chinese chips from Huawei, a change from Nvidia. This shows China's growing power in AI.

#DeepSeekV4, #OpenSourceAI, #ChineseAI, #HuaweiChips, #AICapabilities
https://newsletter.tf/deepseek-v4-ai-china-chips-open-source/

RT @TeksEdge: TRANSLASION: 🚀 vLLM v0.20.0 ist da! Ich freue mich auf TurboQuant! • 752 Commits von 320 Mitwirkenden (123 neue) 🎉 • TurboQuant 2-Bit KV-Cache → 4× Kapazität + FA3/FA4 Prefill 🗜️⚡ • FA4 wieder als Standard-MLA-Prefill aktiviert (SM90+ GPUs) • vLLM-IR-Grundlage + rmsnorm (zukünftige Kernel-Basis) 🧱 • 2,1 % E2E-Latenzgewinn durch fused RMS norm 📈 Neue Baselines: CUDA 13, PyTorch 2.11, Python 3.14, Transformers v5 Hardware/Modelle • DeepSeek V4 (MegaMoE auf Blackwell) + Hunyuan v3 Preview 🔥 • Jetson Thor, AMD ROCm-Upgrades, Intel XPU-Unterstützung • Einfachere GB200/Grace-Blackwell-Einrichtung Großes Update! vLLM (@vllmproject) vLLM v0.20.0 ist da! 752 Commits von 320 Mitwirkenden (123 neue). 🎉 Highlights: DeepSeek V4, Hunyuan v3 Preview-Unterstützung, CUDA 13 / PyTorch 2.11 / Transformers v5 als Baseline, FA4 als Standard-MLA-Prefill, TurboQuant 2-Bit KV (4× Kapazität), vLLM-IR-Grundlage. Thread 👇 — https://nitter.net/vllmproject/status/2048918629144805619#m

mehr auf Arint.info

#AIInfrastructure #DeepSeekV4 #LLM #MachineLearning #TurboQuant #vLLM #arint_info

https://x.com/TeksEdge/status/2048983564801450315#m