Mercury 2 Is 13x Faster Than Claude Haiku - Verified
Inception Labs' Mercury 2 hits 1,196 tokens per second in independent testing - a diffusion architecture that rewires how inference works.
Articles Tagged "Open Source"
Shannon AI Tool Masters Web App Pentesting With 96% Success
KeygraphHQ's open-source Shannon runs Claude-powered multi-agent attacks against real web apps, hitting 96.15% on the XBOW benchmark and finding 30+ flaws in OWASP Juice Shop.
GLM-5
Zhipu AI's GLM-5 is a 744B MoE model with 40B active parameters, trained on 100K Huawei Ascend chips, scoring 77.8% SWE-bench and 50 on Artificial Analysis Intelligence Index - MIT licensed.
Mistral's New Playbook - Send Engineers, Not Models
Europe's most-funded AI startup is embedding engineers inside banks and consulting giants, borrowing Palantir's forward-deploy playbook to survive the frontier race.
Qwen's Tech Lead Junyang Lin Steps Down From Alibaba
Junyang Lin, the 32-year-old architect behind Alibaba's Qwen open-source AI models, announces his departure in a brief tweet - the fourth major exit from Tongyi Lab in two years.
Mistral Vibe 2.0 Review - Europe's CLI Coding Agent
Mistral Vibe 2.0 pairs the open-weight Devstral 2 model with a terminal-native coding agent. We tested it head-to-head against Claude Code and Codex.
Someone Reverse-Engineered Apple's Neural Engine and Trained a Model on It
A developer cracked Apple's undocumented ANE private APIs, measured its real throughput at 19 TFLOPS FP16 (not the marketed 38 TOPS), and trained a 109M-parameter transformer on hardware Apple designed exclusively for inference.
Qwen 3.5 Small Series Ships Four Models From 0.8B to 9B
Alibaba completes the Qwen 3.5 lineup with four small models - 0.8B, 2B, 4B, and 9B - all natively multimodal, 262K context, Apache 2.0. The 9B outperforms last-gen Qwen3-30B and beats GPT-5-Nano on vision benchmarks.
Qwen3.5-0.8B
Qwen3.5-0.8B is the smallest natively multimodal model in the Qwen 3.5 family - 0.8B parameters handling text, images, and video with 262K context. MathVista 62.2, OCRBench 74.5. Apache 2.0.
Qwen3.5-2B
Qwen3.5-2B is a 2B dense multimodal model with 262K context, thinking mode, and native vision including video understanding. OCRBench 84.5, VideoMME 75.6. Apache 2.0 licensed.
Qwen3.5-4B
Qwen3.5-4B is a 4B dense multimodal model that matches Qwen3-30B on MMLU-Pro and beats GPT-5-Nano on vision benchmarks. Runs on 8GB VRAM, Apache 2.0 licensed, 262K-1M context.
Qwen3.5-9B
Qwen3.5-9B is a 9B dense model that outperforms Qwen3-30B on most benchmarks and beats GPT-5-Nano on vision tasks. Natively multimodal with 262K-1M context, Apache 2.0 licensed.
