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.
Articles Tagged "Open Source"
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.
An AI Agent Just Pwned Trivy's 32K-Star Repo via GitHub Actions
An autonomous agent powered by Claude Opus 4.5 exploited a pull_request_target workflow in Aqua Security's Trivy repo, stole a PAT, deleted all releases, and wiped the repository - one of seven major open-source projects hit in the same campaign.
Tenstorrent Blackhole p150a - RISC-V AI Card
Complete specs, benchmarks, and analysis of the Tenstorrent Blackhole p150a - the $1,399 PCIe AI accelerator with 120 Tensix cores, 768 RISC-V processors, 32GB GDDR6, and fully open-source software.
China's GLM-5 Rivals GPT-5.2 on Zero Nvidia Silicon
Zhipu AI's 744B open-source model GLM-5 was trained entirely on Huawei Ascend chips and now competes with GPT-5.2 and Claude Opus on major benchmarks.
DeepSeek V4 vs Claude Opus 4.6 - Open Weight Meets Proprietary
A pre-release comparison of DeepSeek V4 and Claude Opus 4.6 - the open-weight challenger that could match Opus on coding at potentially 89x lower output cost.
DeepSeek V4 vs Kimi K2.5 - China's Trillion-Parameter MoE Duel
Two Chinese open-weight trillion-parameter MoE models with ~32B active parameters each - DeepSeek V4 bets on cost and context, Kimi K2.5 bets on Agent Swarm and verified benchmarks.
DeepSeek V3.2 vs V4 - What Changes With a Trillion Parameters
A pre-release comparison of DeepSeek V3.2 and V4 - examining the generational leap from 671B text-only to a trillion-parameter natively multimodal model with 1M context.
DeepSeek V4 Drops Next Week - 1 Trillion Parameters on Chinese Chips
DeepSeek will release V4, a natively multimodal trillion-parameter model with a 1M token context window, in the first week of March - optimized for Huawei Ascend chips, not Nvidia.
The Creator of MLX Just Left Apple - And He's Not the First
Awni Hannun, the Stanford-trained researcher who co-created Apple's MLX machine learning framework, announced his departure from Apple. His exit is the latest in a devastating exodus of AI talent that has hollowed out Apple's ML research bench over the past year.
