In 2025 and early 2026, significant advancements in Llama AI technology have been marked by the maturation of open-source Vision-Language Models (VLMs), which are anticipated to be widely productized by 2026. Mixture of Experts (MoE) models have gained popularity, with users now operating models with 100-120 billion parameters, a significant increase from the previous year's 30 billion. Z.ai has emerged as a key player with models optimized for inference, while OpenAI's GPT-OSS has been lauded for its tool-calling capabilities. Additionally, Alibaba has expanded its offerings with a variety of models, and coding agents have demonstrated the undeniable potential of generative AI. This matters because these advancements reflect the rapid evolution and diversification of AI technologies, influencing a wide range of applications and industries.
The IQuest-Coder-V1-40B-Instruct model has shown disappointing results in recent benchmarking tests, achieving only a 52% success rate. This performance is notably lower compared to other models like Opus 4.5 and Devstral 2, which solve similar tasks with 100% success. The benchmarks assess the model's ability to perform coding tasks using basic tools such as Read, Edit, Write, and Search. Understanding the limitations of AI models in practical applications is crucial for developers and users relying on these technologies for efficient coding solutions.