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Fully Aggressive variant Uncensored MoE model that won’t refuse red team or pentesting tasks & coding. - 35B parameters, 3B active (MoE) - 0 refusals (Aggressive variant) - Excellent agentic coding + multimodal Powerful uncensored coding model 73.4% on SWE-bench Verified & fully uncensored, It dangerous (in a good...

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28,103 görüntüleme • 7 gün önce •via X (Twitter)

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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.
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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.

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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 ↓

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Hy3, the new 295B MoE model from Tencent Hy, is now free in Nous Portal for the next two weeks! It is focused on cost-effective agentic use, and particularly strong on coding, tool-calling reliability, reasoning, and 256K long-context tasks.
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Hy3, the new 295B MoE model from Tencent Hy, is now free in Nous Portal for the next two weeks! It is focused on cost-effective agentic use, and particularly strong on coding, tool-calling reliability, reasoning, and 256K long-context tasks.

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Introducing 0GM-1.0-35B-A3B. Our first proprietary AI model. Mixture of Experts (MoE), 35B parameters, 3B active per token. Trained on our own decentralized GPU network. Open source under Apache 2.0.
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Introducing 0GM-1.0-35B-A3B. Our first proprietary AI model. Mixture of Experts (MoE), 35B parameters, 3B active per token. Trained on our own decentralized GPU network. Open source under Apache 2.0.

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Qwen3.5-35B with only 3B active parameters This MoE model runs FASTER than most 7B dense models. Tested on 3 generations of NVIDIA: - 5090: 137 tok/s - 4090: 112 tok/s - 3090: 78 tok/s The surprise? The 4090 <> 5090 gap is only 22%. With a 3B active MoE, even old GPUs fly.
0:30

Qwen3.5-35B with only 3B active parameters This MoE model runs FASTER than most 7B dense models. Tested on 3 generations of NVIDIA: - 5090: 137 tok/s - 4090: 112 tok/s - 3090: 78 tok/s The surprise? The 4090 <> 5090 gap is only 22%. With a 3B active MoE, even old GPUs fly.

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Composer is a frontier coding model that completes tasks in under 30 seconds.
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Composer is a frontier coding model that completes tasks in under 30 seconds.

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1. using Warp / Warp didn’t just code. It cooked. ✅ Agentic development environment ✅ Built-in coding agents with guardrails ✅ Multithreaded tasks & knowledge base One of the smartest coding tools I’ve tested. Rating: 10/10
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1. using Warp / Warp didn’t just code. It cooked. ✅ Agentic development environment ✅ Built-in coding agents with guardrails ✅ Multithreaded tasks & knowledge base One of the smartest coding tools I’ve tested. Rating: 10/10

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Today we’re taking a big step on the path toward AGI and releasing Gemini 3— our most intelligent model yet. With Gemini 3, you can bring any idea to life. It is state-of-the-art in reasoning, the best model in the world for multimodal understanding, and our best agentic and vibe coding model.
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Today we’re taking a big step on the path toward AGI and releasing Gemini 3— our most intelligent model yet. With Gemini 3, you can bring any idea to life. It is state-of-the-art in reasoning, the best model in the world for multimodal understanding, and our best agentic and vibe coding model.

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1/4Introducing Qwen3-Coder-Next: Our latest open-weights model designed specifically to power the next generation of autonomous Coding Agents. Built on Qwen3-Next, this model is engineered to handle complex, long-horizon programming tasks with unprecedented efficiency. High-performance agentic intelligence is now in your hands.
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1/4Introducing Qwen3-Coder-Next: Our latest open-weights model designed specifically to power the next generation of autonomous Coding Agents. Built on Qwen3-Next, this model is engineered to handle complex, long-horizon programming tasks with unprecedented efficiency. High-performance agentic intelligence is now in your hands.

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MiniMax M2.1 is officially live🚀 Built for real-world coding and AI-native organizations — from vibe builds to serious workflows. A SOTA 10B-activated OSS coding & agent model, scoring 72.5% on SWE-multilingual and 88.6% on our newly open-sourced VIBE-bench, exceeding leading closed-source models like Gemini 3 Pro and Claude 4.5 Sonnet. The most powerful OSS model for the agentic era is here.
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MiniMax M2.1 is officially live🚀 Built for real-world coding and AI-native organizations — from vibe builds to serious workflows. A SOTA 10B-activated OSS coding & agent model, scoring 72.5% on SWE-multilingual and 88.6% on our newly open-sourced VIBE-bench, exceeding leading closed-source models like Gemini 3 Pro and Claude 4.5 Sonnet. The most powerful OSS model for the agentic era is here.

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Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.
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Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.

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This is Gemini 3: our most intelligent model that helps you learn, build and plan anything. It comes with state-of-the-art reasoning capabilities, world-leading multimodal understanding, and enables new agentic coding experiences. 🧵
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This is Gemini 3: our most intelligent model that helps you learn, build and plan anything. It comes with state-of-the-art reasoning capabilities, world-leading multimodal understanding, and enables new agentic coding experiences. 🧵

Google DeepMind

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Introducing Warp 2.0: the Agentic Development Environment 1️⃣ Top overall coding agent: #1 on Terminal-Bench, 71% on SWE-bench Verified 2️⃣ Agent multi-threading: build features, debug, and ship all at once 3️⃣ The first all-in-one platform for agentic development 🧵 Learn more
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Introducing Warp 2.0: the Agentic Development Environment 1️⃣ Top overall coding agent: #1 on Terminal-Bench, 71% on SWE-bench Verified 2️⃣ Agent multi-threading: build features, debug, and ship all at once 3️⃣ The first all-in-one platform for agentic development 🧵 Learn more

Warp

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Starting today, Gemini 3 is now available for developers. Built to accelerate software development, it can help you bring your ideas to life no matter your level of experience. Our first model in the series, Gemini 3 Pro, is incredibly strong at: ✨ Agentic coding ✨ Vibe coding and web dev ✨ Multimodal understanding
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Starting today, Gemini 3 is now available for developers. Built to accelerate software development, it can help you bring your ideas to life no matter your level of experience. Our first model in the series, Gemini 3 Pro, is incredibly strong at: ✨ Agentic coding ✨ Vibe coding and web dev ✨ Multimodal understanding

Google

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OpenAI took the best Coding model in the world GPT-5.3 Codex And turned it into a powerful coding app It's called Codex, but most people have no idea what you can build with it.
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OpenAI took the best Coding model in the world GPT-5.3 Codex And turned it into a powerful coding app It's called Codex, but most people have no idea what you can build with it.

David Ondrej

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i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2
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i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

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Introducing Arena Mode in Windsurf: One prompt. Two models. Your vote. Benchmarks don't reflect real-world coding quality. The best model for you depends on your codebase and stack. So we made real-world coding the benchmark. Free for the next week. May the best model win.
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Introducing Arena Mode in Windsurf: One prompt. Two models. Your vote. Benchmarks don't reflect real-world coding quality. The best model for you depends on your codebase and stack. So we made real-world coding the benchmark. Free for the next week. May the best model win.

Devin Desktop

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$HOME is in the terminal. Now your new coding bestie is available in whatever terminal emulator you use. Crush is a high performance, agentic coding tool built with Charm libraries and the quirky, playful aesthetic that you know and love. This is just the beginning, too.
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$HOME is in the terminal. Now your new coding bestie is available in whatever terminal emulator you use. Crush is a high performance, agentic coding tool built with Charm libraries and the quirky, playful aesthetic that you know and love. This is just the beginning, too.

Charm

231,583 görüntüleme • 11 ay önce

Start building with Gemini 3 Pro, our most intelligent model with state-of-the-art reasoning and complex multimodal understanding, as well as powerful agentic and vibe coding capabilities. See more below:
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Start building with Gemini 3 Pro, our most intelligent model with state-of-the-art reasoning and complex multimodal understanding, as well as powerful agentic and vibe coding capabilities. See more below:

Google AI Developers

104,898 görüntüleme • 7 ay önce

⚡️OPENAI: GPT-5.6 SOL IS 54% MORE TOKEN EFFICIENT ON AGENTIC CODING Sam Altman says the new GPT-5.6 Sol model is 54% more token efficient on agentic coding tasks and is “as good or better” than competing models. He also said OpenAI aims to offer better value with “every enterprise now is thinking about spend and the value they’re getting in exchange for AI.”
2:22

⚡️OPENAI: GPT-5.6 SOL IS 54% MORE TOKEN EFFICIENT ON AGENTIC CODING Sam Altman says the new GPT-5.6 Sol model is 54% more token efficient on agentic coding tasks and is “as good or better” than competing models. He also said OpenAI aims to offer better value with “every enterprise now is thinking about spend and the value they’re getting in exchange for AI.”

Coin Bureau

33,775 görüntüleme • 3 gün önce