Private datasets
Latest stories covering Private datasets, with summaries and links to related coverage.
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1 story · 1 report in the last 7 days
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Models in this coverage
Up to six tracked models linked to this topic’s reports in the last 30 days. Counts measure coverage on Themata, not usage.
- Claude Haiku 5.5
Anthropic
· Closed
A small, fast Claude model for high-volume tasks. Suited to summarization, browser use, and supporting agents where speed and cost matter.
1 story · 1 report on this topic
- Claude Opus 5.5
Anthropic
· Closed
Anthropic’s model for complex reasoning and longer agent tasks. Built for work such as large codebase changes, code review, and multi-step problem solving.
1 story · 1 report on this topic
- Claude Sonnet 5.5
Anthropic
· Closed
Anthropic’s everyday model for coding, writing, and well-scoped tasks. Designed for feature development, bug fixes, and practical agent workflows.
1 story · 1 report on this topic
- DeepSeek V4.1 Flash
DeepSeek
· Open weights
An open-weight mixture-of-experts model that reads text and images. Its architecture focuses on efficient long-context and agent workloads, with support for up to one million tokens.
1 story · 1 report on this topic
- Gemini 4 Argon
Google
· Closed
Google’s reasoning model for software engineering, mathematical and scientific problems, and multi-step agents. Designed to maintain context across longer tasks.
1 story · 1 report on this topic
- GPT-6.1 Sol
OpenAI
· Closed
A general-purpose OpenAI model for coding, tool use, and document-heavy work. Supports multi-step workflows and computer use.
1 story · 1 report on this topic
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Latest stories
Artificial Analysis Intelligence Index v5
research
7 min read
Artificial Analysis released Intelligence Index v5 on October 27, 2026, adding two benchmarks and revising three others so that 60% of the composite model-capability score now relies on private test sets or held-out answers. The index measures knowledge work, coding, science and general capabilities at 25% each. New evaluations include Cognition’s 132-task FrontierCode 2.0 coding benchmark and Terminal-Bench-Science, which contains 70 terminal-based scientific research tasks. Claude Opus 5.5 at maximum effort leads the overall index with 58, followed by GPT-6 Astra at 57 and GPT-6.1 Sol at 55; Gemini 4 Argon scores 50. Claude Opus 5.5 leads FrontierCode 2.0 at 46% and HLE-Diamond at 68%, while GPT-6 Astra leads Terminal-Bench-Science at 63% and the CritPt v2 hard subset at 72%. No model led all nine evaluations. Kimi K3.1 Pro, whose weights have not yet been released, is the highest-scoring open-weights model at 46, 12 points behind Claude Opus 5.5. Among models with released weights, DeepSeek V4.1 Flash 1017 and GLM-5.3 lead at 32. Artificial Analysis also launched Progress Index v1, a continuous capability scale covering language models released since November 2022.