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🚨 Open-source AI just got serious. Alibaba just released Qwen 3.5-Plus 🤯 397B parameters. Only 17B active per inference. Performance comparable to Gemini 3 Pro — at just $0.8 per million tokens (1/18 the cost). But here’s what makes it different 👇 This isn’t just another benchmark drop. In...

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Toha Khan

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123,375 görüntüleme • 4 ay önce •via X (Twitter)

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🚨 ALIBABA JUST OPEN-SOURCED THE MOST POWERFUL MODEL IN THE WORLD - Qwen3.5 plus And it changes the AI race forever. This is not another “bigger model” release. This is a complete architectural reset. 397B parameters → only 17B active at inference, Qwen3.5 plus delivers performance on par with GPT-5.2 and Gemini-3-Pro. A new Hybrid Sparse MoE + Linear Attention architecture + Multi-Token Prediction = near-instant long-context responses and massive speed gains. Built as a true native multimodal model, it doesn’t just chat it builds. With a single prompt: “Use the React framework to create a visually impressive Mapbox demo featuring locations in Beijing and Shanghai” it generates a live interactive 3D map UI, structured components, real layouts, and production-ready frontend logic. This is real agentic, multimodal coding not a static code block. MMLU-Pro: 87.8 GPQA: 88.4 IFBench: 76.5 ⚡ up to 8× faster inference And it’s fully open-sourced under Apache-2.0. No locked APIs. No restricted tiers. 201 languages supported bringing frontier AI to developers, startups, and researchers worldwide. The race is no longer about the biggest model. It’s about the most usable intelligence. Open source just entered the top tier.
1:50

🚨 ALIBABA JUST OPEN-SOURCED THE MOST POWERFUL MODEL IN THE WORLD - Qwen3.5 plus And it changes the AI race forever. This is not another “bigger model” release. This is a complete architectural reset. 397B parameters → only 17B active at inference, Qwen3.5 plus delivers performance on par with GPT-5.2 and Gemini-3-Pro. A new Hybrid Sparse MoE + Linear Attention architecture + Multi-Token Prediction = near-instant long-context responses and massive speed gains. Built as a true native multimodal model, it doesn’t just chat it builds. With a single prompt: “Use the React framework to create a visually impressive Mapbox demo featuring locations in Beijing and Shanghai” it generates a live interactive 3D map UI, structured components, real layouts, and production-ready frontend logic. This is real agentic, multimodal coding not a static code block. MMLU-Pro: 87.8 GPQA: 88.4 IFBench: 76.5 ⚡ up to 8× faster inference And it’s fully open-sourced under Apache-2.0. No locked APIs. No restricted tiers. 201 languages supported bringing frontier AI to developers, startups, and researchers worldwide. The race is no longer about the biggest model. It’s about the most usable intelligence. Open source just entered the top tier.

RAVI KUMAR SAHU

379,590 görüntüleme • 4 ay önce

Alibaba just open-sourced Qwen 3.6-35B A3B 35B MoE model (only ~3B active), multimodal, agentic coding, Apache 2.0. This isn’t just efficient—it’s built for real workflows. Open models are catching up fast.
1:49

Alibaba just open-sourced Qwen 3.6-35B A3B 35B MoE model (only ~3B active), multimodal, agentic coding, Apache 2.0. This isn’t just efficient—it’s built for real workflows. Open models are catching up fast.

Mervin Praison

13,063 görüntüleme • 2 ay önce

Qwen 3.6 Plus Preview just dropped on OpenRouter for Free. > 1M token context. > $0 input. $0 output. Meanwhile: - Claude Opus 4.6 → $5 / $25 per 1M - GPT-5.4 → charges for 1M context Qwen just nuked the pricing model. Open source isn’t slowing down. It’s taking over.
0:44

Qwen 3.6 Plus Preview just dropped on OpenRouter for Free. > 1M token context. > $0 input. $0 output. Meanwhile: - Claude Opus 4.6 → $5 / $25 per 1M - GPT-5.4 → charges for 1M context Qwen just nuked the pricing model. Open source isn’t slowing down. It’s taking over.

WorldofAI

146,277 görüntüleme • 2 ay önce

Alibaba just dropped an AI that doesn’t just write code. It runs it. Tests it. Fixes it. Until it actually works. Here’s what makes Qwen 3 Coder Next different: → Executes code, not just autocomplete → Runs tests automatically → Iterates until all tests pass → Handles multi-file repositories → Works fully offline This is a real coding agent, not a text generator. Save this video, you’ll rethink how coding gets done. Want the SOP? DM me. 💬
8:15

Alibaba just dropped an AI that doesn’t just write code. It runs it. Tests it. Fixes it. Until it actually works. Here’s what makes Qwen 3 Coder Next different: → Executes code, not just autocomplete → Runs tests automatically → Iterates until all tests pass → Handles multi-file repositories → Works fully offline This is a real coding agent, not a text generator. Save this video, you’ll rethink how coding gets done. Want the SOP? DM me. 💬

Julian Goldie SEO

20,956 görüntüleme • 4 ay önce

Numbers in! Target: 150 tok/s browser-native Qwen 3.5 inference Achieved: 180 tok/s — Qwen 3.5 INT4, WebGPU, browser-only. No cloud, APIs, servers, just Pure WebGPU + WGSL optimizations, HF SafeTensors, single browser tab. Open AI, for real.
0:57

Numbers in! Target: 150 tok/s browser-native Qwen 3.5 inference Achieved: 180 tok/s — Qwen 3.5 INT4, WebGPU, browser-only. No cloud, APIs, servers, just Pure WebGPU + WGSL optimizations, HF SafeTensors, single browser tab. Open AI, for real.

Eric

256,622 görüntüleme • 3 ay önce

x Alibaba Cloud: 60% less flickering in AI video! ·Integrates Wan, Qwen-Image & Qwen-VL ·40-60% cost reduction via flexible deployment ·180+ languages translated in minutes Commercial AI video at scale.
0:40

x Alibaba Cloud: 60% less flickering in AI video! ·Integrates Wan, Qwen-Image & Qwen-VL ·40-60% cost reduction via flexible deployment ·180+ languages translated in minutes Commercial AI video at scale.

Alibaba Cloud

1,583,157 görüntüleme • 1 ay önce

Google just killed every paid coding tool. Their new AI Studio destroys Cursor completely. Here's how to build React apps instantly: → Open Google AI Studio Build Mode → Type what you want to build → Watch it code everything automatically → Deploy to GitHub with one click → Share working apps instantly Features that crush the competition: • Angular + React support ✔ • GitHub integration ✔ • Real-time code preview ✔ • Gemini API built-in ✔ • Enterprise AI for $0 ✔ Save this thread, you'll build faster apps. Want the SOP? DM me. 💬
9:50

Google just killed every paid coding tool. Their new AI Studio destroys Cursor completely. Here's how to build React apps instantly: → Open Google AI Studio Build Mode → Type what you want to build → Watch it code everything automatically → Deploy to GitHub with one click → Share working apps instantly Features that crush the competition: • Angular + React support ✔ • GitHub integration ✔ • Real-time code preview ✔ • Gemini API built-in ✔ • Enterprise AI for $0 ✔ Save this thread, you'll build faster apps. Want the SOP? DM me. 💬

Julian Goldie SEO

188,249 görüntüleme • 9 ay önce

Crusoe Managed Inference is now available. Run model inference faster, easier, and more cost-effectively. Large-context AI solutions demand fast outputs, massive throughput, and resilient scaling. Crusoe Managed Inference delivers breakthrough speed & reduced input-token spend.
1:21

Crusoe Managed Inference is now available. Run model inference faster, easier, and more cost-effectively. Large-context AI solutions demand fast outputs, massive throughput, and resilient scaling. Crusoe Managed Inference delivers breakthrough speed & reduced input-token spend.

Crusoe

12,096,815 görüntüleme • 7 ay önce

Qwen3-Next (thinking & non-thinking) are now live in BF16 at Hyperbolic! Qwen3-Next is a huge efficiency leap: - 80B MoE with just 3B active params - 10x cheaper to train vs Qwen3-32B - 10x inference throughput for >32K tokens Proud to be a launch partner with Qwen - kudos to this amazing team for keeping pushing open-source AI forward. We’re the first to serve Qwen3-Next on Hugging Face. Give it a try!
0:23

Qwen3-Next (thinking & non-thinking) are now live in BF16 at Hyperbolic! Qwen3-Next is a huge efficiency leap: - 80B MoE with just 3B active params - 10x cheaper to train vs Qwen3-32B - 10x inference throughput for >32K tokens Proud to be a launch partner with Qwen - kudos to this amazing team for keeping pushing open-source AI forward. We’re the first to serve Qwen3-Next on Hugging Face. Give it a try!

Yuchen Jin

84,342 görüntüleme • 9 ay önce

Qwen just published the 'Thinking' variant of this model 🔥 So you can run a model EVEN MORE powerful than GPT-4o locally! - Still only 3B active parameters - Open source license - 256k context window extendable to 1M - Strong in math, science and coding Details below ↓
0:45

Qwen just published the 'Thinking' variant of this model 🔥 So you can run a model EVEN MORE powerful than GPT-4o locally! - Still only 3B active parameters - Open source license - 256k context window extendable to 1M - Strong in math, science and coding Details below ↓

Paul Couvert

106,261 görüntüleme • 11 ay önce

The future of AI infrastructure isn’t just being built. It’s being powered. $IFR - the token at the core of Inferium. ⚡ Fuel for inference 🛠️ Incentives for nodes 🌐 Backbone of a decentralized AI economy What can you do with $IFR? ✅ Stake to power decentralized inference ✅ Fuel AI-driven transactions & services ✅ Govern the AI economy ✅ Reward developers & model testers Real utility. Real demand. Real upside. $IFR 🔜
0:47

The future of AI infrastructure isn’t just being built. It’s being powered. $IFR - the token at the core of Inferium. ⚡ Fuel for inference 🛠️ Incentives for nodes 🌐 Backbone of a decentralized AI economy What can you do with $IFR? ✅ Stake to power decentralized inference ✅ Fuel AI-driven transactions & services ✅ Govern the AI economy ✅ Reward developers & model testers Real utility. Real demand. Real upside. $IFR 🔜

Inferium

62,967 görüntüleme • 1 yıl önce

Qwen just quietly dropped the most dangerous open model of 2026 Qwen3.6-Plus. native 1M context. agentic workflows. multimodal. half the size of competitors. and it's free on OpenRouter right now. you're not ready for this breakdown 🧵
0:35

Qwen just quietly dropped the most dangerous open model of 2026 Qwen3.6-Plus. native 1M context. agentic workflows. multimodal. half the size of competitors. and it's free on OpenRouter right now. you're not ready for this breakdown 🧵

Farhan

53,820 görüntüleme • 2 ay önce

Eigent × Qwen 3.5 Plus We upload a Spring Festival Gala robot performance video and ask our open source Cowork, powered by Qwen 3.5 Plus, to turn it into a complete single-file 3D interactive Three.js game. Recreates the characters, movements, and festive stage. Full Eigent breakdown in the video.👇 Now live with BYOK, bring your own Qwen 3.5 Plus key and run it directly in Eigent.
2:52

Eigent × Qwen 3.5 Plus We upload a Spring Festival Gala robot performance video and ask our open source Cowork, powered by Qwen 3.5 Plus, to turn it into a complete single-file 3D interactive Three.js game. Recreates the characters, movements, and festive stage. Full Eigent breakdown in the video.👇 Now live with BYOK, bring your own Qwen 3.5 Plus key and run it directly in Eigent.

Eigent AI

29,748 görüntüleme • 4 ay önce

Alibaba just dropped Qwen3.5-397B-A17B and there's a lot to unpack. 397B params, 17B active per forward pass. Sparse MoE done right. But the real story isn't the size—it's the architecture choices. The MoE Design Most MoE models feel like bolt-ons. Qwen 3.5's sparse activation is native—only 4.3% of parameters fire per token. That's how you get trillion-parameter-class performance without trillion-parameter inference costs. The 0.8 RMB/million tokens pricing isn't subsidized; it's structurally earned. Native Multimodal, Not Glued-On This is a vision-language model from the ground up. Heterogeneous architecture—separate processing pipelines for text, image, video that fuse early. Not a vision encoder slapped onto an LLM. The result: 90.8 on OmniDocBench, 79.0 on MMMU-Pro. Document understanding and visual reasoning without the usual brittleness. The Context Window Reality Qwen3.5-Plus (the hosted version) ships with 1M tokens by default. That's not a marketing number—they're actually positioning it for long-document workflows. With built-in adaptive tool use, it's clearly aimed at agentic automation, not just chat. What Actually Impressed Me • FP8 native pipeline: ~50% activation memory reduction • Async RL framework for continuous refinement—training and inference workloads separated • 201 languages (up from 119), 250k vocab for better low-resource encoding • Apache 2.0 license. Full weights on HuggingFace and ModelScope. The Benchmark Context 76.4 on SWE-bench Verified puts it in the range where it can handle real debugging workflows. 72.9 on BFCL v4 for agentic tool use. 88.4 on GPQA Diamond. These aren't SOTA in isolation, but the breadth is unusual—strong across reasoning, coding, multimodal, and agentic tasks. The Honest Caveat I haven't stress-tested the 1M context for needle-in-haystack retrieval yet. And "native multimodal" claims need real-world torture testing—PDFs with tables, charts, mixed layouts. Benchmarks are benchmarks. Bottom Line This isn't just another model release. It's a bet on efficient scale: big model capabilities, small active compute, open weights. At 1/18th the cost of Gemini 3 Pro, it's going to force pricing conversations across the board.
1:03

Alibaba just dropped Qwen3.5-397B-A17B and there's a lot to unpack. 397B params, 17B active per forward pass. Sparse MoE done right. But the real story isn't the size—it's the architecture choices. The MoE Design Most MoE models feel like bolt-ons. Qwen 3.5's sparse activation is native—only 4.3% of parameters fire per token. That's how you get trillion-parameter-class performance without trillion-parameter inference costs. The 0.8 RMB/million tokens pricing isn't subsidized; it's structurally earned. Native Multimodal, Not Glued-On This is a vision-language model from the ground up. Heterogeneous architecture—separate processing pipelines for text, image, video that fuse early. Not a vision encoder slapped onto an LLM. The result: 90.8 on OmniDocBench, 79.0 on MMMU-Pro. Document understanding and visual reasoning without the usual brittleness. The Context Window Reality Qwen3.5-Plus (the hosted version) ships with 1M tokens by default. That's not a marketing number—they're actually positioning it for long-document workflows. With built-in adaptive tool use, it's clearly aimed at agentic automation, not just chat. What Actually Impressed Me • FP8 native pipeline: ~50% activation memory reduction • Async RL framework for continuous refinement—training and inference workloads separated • 201 languages (up from 119), 250k vocab for better low-resource encoding • Apache 2.0 license. Full weights on HuggingFace and ModelScope. The Benchmark Context 76.4 on SWE-bench Verified puts it in the range where it can handle real debugging workflows. 72.9 on BFCL v4 for agentic tool use. 88.4 on GPQA Diamond. These aren't SOTA in isolation, but the breadth is unusual—strong across reasoning, coding, multimodal, and agentic tasks. The Honest Caveat I haven't stress-tested the 1M context for needle-in-haystack retrieval yet. And "native multimodal" claims need real-world torture testing—PDFs with tables, charts, mixed layouts. Benchmarks are benchmarks. Bottom Line This isn't just another model release. It's a bet on efficient scale: big model capabilities, small active compute, open weights. At 1/18th the cost of Gemini 3 Pro, it's going to force pricing conversations across the board.

Bo Wang

13,221 görüntüleme • 4 ay önce

Google is about to merge two massive AI tools. And this could kill your current coding workflow overnight. Here’s what’s happening with Anti-Gravity + Google AI Studio 👇 Right now: → AI Studio = prototyping playground → Anti-Gravity = autonomous coding agents → You manually move everything → You lose context → You lose time The leak? One-click prototype → production. Shared session tokens. Agents keep your context. No more copying code. No more broken workflows. And Anti-Gravity agents: ✔ Plan your build ✔ Write code ✔ Test in browser ✔ Debug automatically ✔ Deploy Prototype to live app in one flow. If this lands mid-February like insiders say… Coding changes forever. Save this video, you’ll want to prepare before it drops. Want the SOP? DM me. 💬
8:20

Google is about to merge two massive AI tools. And this could kill your current coding workflow overnight. Here’s what’s happening with Anti-Gravity + Google AI Studio 👇 Right now: → AI Studio = prototyping playground → Anti-Gravity = autonomous coding agents → You manually move everything → You lose context → You lose time The leak? One-click prototype → production. Shared session tokens. Agents keep your context. No more copying code. No more broken workflows. And Anti-Gravity agents: ✔ Plan your build ✔ Write code ✔ Test in browser ✔ Debug automatically ✔ Deploy Prototype to live app in one flow. If this lands mid-February like insiders say… Coding changes forever. Save this video, you’ll want to prepare before it drops. Want the SOP? DM me. 💬

Julian Goldie SEO

24,257 görüntüleme • 4 ay önce

OpenAI just leaked a model so powerful it triggered code red. And yes, it’s called Garlic. Here’s the 30-second breakdown so you actually understand why this matters → ✔ Google Gemini 3 crushed OpenAI in benchmarks ✔ ChatGPT usage dropped ✔ Sam Altman paused projects to build “Garlic” ✔ Garlic uses high-density pre-training (smarter + smaller) ✔ Internal memos show it beating Gemini 3 + Claude Opus 4.5 Why this is wild: → Faster than current models → Cheaper to run → Better at reasoning → Better at coding → Could run locally on your phone Save this video, you'll rethink what AI models can do. Want the SOP? DM me. 💬
9:17

OpenAI just leaked a model so powerful it triggered code red. And yes, it’s called Garlic. Here’s the 30-second breakdown so you actually understand why this matters → ✔ Google Gemini 3 crushed OpenAI in benchmarks ✔ ChatGPT usage dropped ✔ Sam Altman paused projects to build “Garlic” ✔ Garlic uses high-density pre-training (smarter + smaller) ✔ Internal memos show it beating Gemini 3 + Claude Opus 4.5 Why this is wild: → Faster than current models → Cheaper to run → Better at reasoning → Better at coding → Could run locally on your phone Save this video, you'll rethink what AI models can do. Want the SOP? DM me. 💬

Julian Goldie SEO

114,491 görüntüleme • 6 ay önce

Small models are so powerful! Alibaba Qwen released QwQ-32B, a reasoning model that beats DeepSeek-R1 (671B) and OpenAI o1-mini! We at Hyperbolic Labs now serve QwQ 32B in bf16! As an inference provider of Hugging Face, you can chat with it directly on the model's Hugging Face page!
0:57

Small models are so powerful! Alibaba Qwen released QwQ-32B, a reasoning model that beats DeepSeek-R1 (671B) and OpenAI o1-mini! We at Hyperbolic Labs now serve QwQ 32B in bf16! As an inference provider of Hugging Face, you can chat with it directly on the model's Hugging Face page!

Yuchen Jin

65,950 görüntüleme • 1 yıl önce

New AI just replaced N8N forever. And it’s completely free right now. Here’s how I built 3 workflows → ✔ Gmail → Slack → ClickUp (3 mins). ✔ YouTube → Blog → LinkedIn posts (auto). ✔ Competitor tracker → SEO briefs (instantly). No setup. No coding. Just talk to the AI and it builds everything. Save this video, you’ll rethink automation. DM “SOP” for the full workflow. 💬
14:49

New AI just replaced N8N forever. And it’s completely free right now. Here’s how I built 3 workflows → ✔ Gmail → Slack → ClickUp (3 mins). ✔ YouTube → Blog → LinkedIn posts (auto). ✔ Competitor tracker → SEO briefs (instantly). No setup. No coding. Just talk to the AI and it builds everything. Save this video, you’ll rethink automation. DM “SOP” for the full workflow. 💬

Julian Goldie SEO

69,572 görüntüleme • 8 ay önce

World models are moving beyond offline generation towards interactive, real-time experiences. Introducing ⚡FlashDreams⚡: an open-source high-performance inference and serving library built for autoregressive world models: 🔥 Up to 3.10× faster LingBot-World inference 🔥 Up to 2.12× faster Self-Forcing inference 🔥 Up to 1.40× faster Wan2.1 inference 🔥 8 integrated models 🔥 Multi-GPU, streaming, low-latency serving 🔥 Agentic skills that teach you how to use it FlashDreams is designed for a new generation of AI systems that continuously evolve over time while responding to user interactions. It powers applications across robotics, autonomous vehicle simulation, gaming, and virtual worlds. Github: Docs: Research page: Join the #flashdreams Discord channel at FlashDreams is also the runtime backbone behind NVIDIA OmniDreams ( 1/n #AI #WorldModels #FastInference #PhysicalAI #OpenSource #NVIDIA
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World models are moving beyond offline generation towards interactive, real-time experiences. Introducing ⚡FlashDreams⚡: an open-source high-performance inference and serving library built for autoregressive world models: 🔥 Up to 3.10× faster LingBot-World inference 🔥 Up to 2.12× faster Self-Forcing inference 🔥 Up to 1.40× faster Wan2.1 inference 🔥 8 integrated models 🔥 Multi-GPU, streaming, low-latency serving 🔥 Agentic skills that teach you how to use it FlashDreams is designed for a new generation of AI systems that continuously evolve over time while responding to user interactions. It powers applications across robotics, autonomous vehicle simulation, gaming, and virtual worlds. Github: Docs: Research page: Join the #flashdreams Discord channel at FlashDreams is also the runtime backbone behind NVIDIA OmniDreams ( 1/n #AI #WorldModels #FastInference #PhysicalAI #OpenSource #NVIDIA

Ruilong Li

88,901 görüntüleme • 24 gün önce