Gemini 3.5 Flash vs Claude Fable 5.1
Compare Gemini 3.5 Flash and Claude Fable 5.1 side-by-side. See comparisons of price, response speed, accuracy, and file support to choose the best model for your task.
Overview
Gemini 3.5 Flash vs Claude Fable 5.1 Overview
Everything you need to know about these AI models, including capabilities, performance, pricing, and technical details.
Google / Gemini 3.5 Flash
proDescription
Google's newest Flash-tier model, and an unusual one. Google describes it as delivering near-Pro intelligence at Flash cost and speed, with Pro-level coding proficiency and parallel agentic execution. It reads text, images, audio, video, and PDFs across a one-million-token context window. Fast, cheap, and strong on tool use. Still a preview release, with the same modest output ceiling as the rest of the Gemini 3 line.
Anthropic / Claude Fable 5.1
maxDescription
Anthropic's most capable generally available model, sitting above the Opus line. Fable 5.1 is built for long, unsupervised work: multi-day coding, agentic research, and tasks that run across dozens of tool calls. It reads text and images, maintains a very large context, and reasons before every answer at an adjustable depth. Its knowledge is the most recent of any Claude model. Anthropic positions Opus 5 as the starting point for most work, and Fable 5.1 for teams whose evaluations demand a higher ceiling.
About
About
Capabilities
Capabilities
Comparison
Why Use Gemini 3.5 Flash and Claude Fable 5.1?
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Google / Gemini 3.5 Flash
proCoding at Flash Speed
Google claims Pro-level coding proficiency at Flash-tier cost, and lists agentic coding among its core strengths. Built for parallel agent execution, where several tasks run at once rather than one after another.
Adjustable Thinking
Thinking runs at minimal, low, medium, or high, defaulting to medium rather than high. That makes it cheaper and faster out of the box, with room to push harder when a problem needs it.
Handle full Codebases Context
A one-million-token context window, the same as Google's Pro tier. Load a full repository, a long document set, or hours of media, and work across all of it in a single session.
A Modest Output Ceiling
Writes up to 64,000 tokens in a single response, well short of what most frontier models produce. Enough for reports and documentation, but long-form generation has to be split into parts.
Search, Maps, and URL Grounding
Supports Google Search, Grounding with Google Maps, File Search, URL Context, and code execution, and can combine them in one request. Its knowledge cutoff is January 2025, so grounding matters.
Reads Video, Audio, and PDFs
Text, images, video, audio, and PDFs, all handled natively. Output is text only. Very few models accept video or audio input at all, which makes this range genuinely uncommon.
Anthropic / Claude Fable 5.1
maxLong-Running Coding
Anthropic's strongest model for multi-day coding sessions and codebase research. Built to sustain complex software engineering across many steps and tool calls without a human checking in at each one.
Adaptive Thinking Always On
Reasoning is always on, with adjustable effort rather than an on-off switch. Steer depth up for the hardest problems or down for lighter work, without restructuring the prompt each time.
Room For Whole Projects
A very large context window, among the largest available. Load an entire codebase, a long research corpus, or a large document set and work across all of it in a single session.
Document-Heavy Analysis
Built for document-heavy analysis and multi-step automation alongside coding. Suited to work that reads across large, mixed source material and produces structured, reviewable output.
Long-Horizon Agent Work
Its defining strength. Retains context, uses tools, evaluates results, and works on a task through many steps. Built for agents who run for a long time with little supervision.
Text And Image Input
Reads text and images in the same prompt, so you can send screenshots, diagrams, or scanned pages alongside your question. Output is text only. Audio and video are not accepted.
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