SubQ 1.1 Small vs. Claude Fable 5.1

SubQ 1.1 Small is a long-context enterprise AI model developed by Subquadratic to address the limitations of traditional models that struggle with large artifacts. It is built for tasks where the full context matters, including analyzing entire codebases, reviewing lengthy contracts, comparing financial filings, and reasoning across document collections. The model uses Subquadratic Sparse Attention, which replaces dense attention with a learned sparse approach that scales more efficiently as context length grows. This allows SubQ 1.1 Small to process extremely large context windows while sharply reducing attention compute requirements. In benchmark testing, the model achieved near-perfect needle-in-a-haystack retrieval at 1M, 2M, 6M, and 12M tokens. It also scored 99.12% on the RULER 128K benchmark, demonstrating strength on tasks involving multi-hop reasoning, variable tracing, aggregation, and long-context understanding. Beyond retrieval, SubQ 1.1 Small maintains competitive performance in general knowledge, coding, and enterprise agent benchmarks such as GPQA Diamond, LiveCodeBench, and AutomationBench Finance. Its efficiency is a major advantage, requiring 64.5x less compute than dense attention and running 56x faster than FlashAttention-2 at 1M tokens on a single attention layer. The model was trained through staged context extension and continued pretraining on long-form artifacts such as books, documents, and repository-scale code. SubQ 1.1 Small is suited for financial analysis, legal work, software engineering, due diligence, long-horizon coding tasks, and enterprise workflows that depend on relationships spread across large bodies of information. It gives organizations a way to reason over complete artifacts more directly instead of relying only on retrieval pipelines, chunking strategies, and agentic scaffolding.

Claude Fable 5.1 is an advanced general-purpose AI model from Anthropic focused on coding, scientific research, knowledge work, business processes, and long-horizon agentic reasoning. It is the generally available counterpart to Claude Mythos 5.1, which uses the same underlying model but is offered with different safeguards for vetted cybersecurity and life sciences users. Compared with Claude Fable 5, Fable 5.1 shows stronger performance across agentic coding, research, computer use, multidisciplinary reasoning, business workflow automation, and other complex benchmarks. The model is designed to remain effective during long-running tasks that involve planning, tool use, repeated verification, code modification, research, and multi-step decision making. In software engineering scenarios, it can investigate difficult bugs, trace problems across large codebases, perform code review, and work through complex implementation tasks with less supervision. Anthropic also positions Fable 5.1 as a stronger research model, with demonstrated capabilities in scientific analysis, computational modeling, and other technically demanding workflows. Improvements to cache-read pricing reduce the cost of reusing previously processed context, making the model more economical for workflows that involve long conversations, large codebases, or repeated tool calls. Fable 5.1 introduces updated enterprise privacy and security options, including Enterprise Frontier Safeguards and zero-data-retention access for eligible customers during the rollout period. Its cybersecurity protections are designed to permit more benign defensive security work, including vulnerability discovery, while continuing to restrict higher-risk activities such as exploit development and certain penetration-testing tasks. The model is available through Claude.ai, Claude Code, Claude Cowork, the Claude API, Amazon Web Services, Google Cloud, and Microsoft Azure under the claude-fable-5-1 model identifier for API users.