Google: Gemini 3 Pro

Claude Opus 5 is a large language model with multimodal vision capabilities developed by Anthropic, released on July 24, 2026 as the fourth model in the Claude 5 family. It sits in the Opus tier of Anthropic's lineup, positioned below the Mythos-class Fable 5 and Mythos 5 models, and is framed by Anthropic as the go-to model for most knowledge work and automation tasks. The model approaches Fable 5's capabilities at roughly half the cost, priced at $5 per million input tokens and $25 per million output tokens. It becomes the default model on Claude Max and the strongest model available on Claude Pro. The model ships with a 1 million token context window and an adjustable "effort" parameter that allows users to trade reasoning depth for speed and token savings. Early enterprise customers reported that Opus 5 achieved comparable performance to Opus 4.8's maximum-reasoning mode while generating significantly fewer tokens on average, and demonstrated higher accuracy on financial modeling tasks with fewer tool calls and less time.Claude Opus 5 supports multimodal inputs including images and text, and is designed for agentic workflows, coding, scientific research, and complex enterprise tasks. Anthropic reports the model scores 10.2 percentage points higher than Opus 4.8 on an internal chemistry benchmark, making it the most capable generally available model for scientific research in the Claude lineup. Cyber classifiers on Opus 5 are designed to intervene approximately 85 percent less often than those on Fable 5, with fallback to Opus 4.8 when a classifier triggers. The model does not retain user data for 30 days, unlike Fable 5. It is available across Anthropic's platforms including Claude Code and Claude Cowork, as well as cloud partners.

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, which also includes Terra (a balanced everyday-work tier) and Luna (a fast, cost-efficient tier). Sol is designed for demanding reasoning, long-horizon agentic workflows, software engineering, computer use, scientific research, and cybersecurity tasks. It introduces two new capability modes: a "max" reasoning effort setting that allocates additional compute time for difficult problems, and an "ultra" mode that coordinates multiple subagents in parallel to accelerate complex, multi-step work. The model supports native multimodal input, allowing it to process screenshots, diagrams, charts, documents, and photographs alongside text. A reported context window of approximately 1.5 million tokens enables processing of large codebases, lengthy research documents, and extended agentic sessions.GPT-5.6 Sol was announced on June 26, 2026, initially in a limited preview for trusted partners, and reached general availability on July 9, 2026. On the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields, Sol scores 53.6. On Terminal-Bench 2.1, which tests command-line agentic coding workflows, Sol Ultra achieves 91.9%. The model also demonstrates gains in life sciences evaluations, including long-horizon genomics and quantitative biology analyses. OpenAI paired the release with its most extensive safety evaluation to date, combining human red teaming with large-scale automated testing, and classified Sol as High capability in both cybersecurity and biological risk under its Preparedness Framework, though it does not cross the Critical threshold in either category.

Llama 4 Maverick, introduced on April 5, 2025, is one of the first models in Meta’s Llama 4 family, designed as a natively multimodal model supporting text + image inputs with text outputs. It employs a Mixture-of-Experts (MoE) architecture with 128 experts, activating ~17B parameters per token out of a pool of ~400B total parameters. This design improves scalability, efficiency, and reasoning capacity. Maverick has a 1M-token context window, enabling it to handle large documents, extended conversations, and multimodal reasoning. Its knowledge cutoff is August 2024.The model is released under the Llama 4 Community License and comes in both base and instruction-tuned (“Instruct”) versions. Maverick is widely deployed via Hugging Face, Google Vertex AI, Amazon Bedrock, and Oracle Cloud, making it one of the most accessible large open-weight models. However, it outputs text only (no image/audio generation) and, while input capacity is huge, output limits are typically much smaller. The MoE design also raises hardware demands, as maintaining 128 experts requires significant compute resources, and Meta’s license introduces restrictions around commercial-scale use.

Qwen3 VL 235B A22B Instruct is a flagship multimodal vision-language model developed by Qwen (Alibaba Cloud), designed for instruction-following tasks that combine advanced text generation with visual understanding. It serves as a high-end open-weight model for developers and researchers building multimodal AI systems that require strong reasoning, perception, and long-context capabilities.The model supports interleaved text and image inputs, very long context windows (up to roughly 256K tokens), and efficient inference through a mixture-of-experts architecture with about 22B active parameters out of 235B total. In today’s landscape, it competes with top-tier proprietary vision-language models while offering the advantages of open weights and flexible deployment. Typical applications include multimodal assistants, document and image analysis, visual reasoning, and large-context instruction-based workflows.