Gemma 4 vs Claude Fable 5.1
Compare Gemma 4 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
Gemma 4 vs Claude Fable 5.1 Overview
Everything you need to know about these AI models, including capabilities, performance, pricing, and technical details.
Google / Gemma 4
proDescription
Google's open model family, and the one you can run on your own hardware. Gemma 4 handles text, images, and video, parses documents and handwriting, and was trained across more than 140 languages. Its image understanding is unusually detailed, covering OCR, charts, and screen layouts. Weights are open, so it can be self-hosted or run offline entirely, which no closed frontier model allows.
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 Gemma 4 and Claude Fable 5.1?
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Google / Gemma 4
proCoding That Runs Offline
Google positions Gemma 4 as a code-generation, completion, and correction tool and says it can turn a workstation into a local-first coding assistant. Function calling is native, so it can drive tools.
Configurable Thinking Modes
Google describes every model in the family as a capable reasoner with configurable thinking modes, so you can trade depth against speed on a task-by-task basis rather than being locked to one setting.
Room for Repositories and Long Documents
A 256,000-token context window on the larger sizes. Google says this is enough to pass whole repositories or long documents in a single prompt without chunking them into separate requests.
Writing in Many Languages
Trained natively on more than 140 languages, with out-of-the-box support for over 35. The broadest multilingual coverage of any model here, and the reason it suits non-English writing.
Analysis Without Live Search
Reads and analyses whatever you give it, including PDFs, charts, and tables. It has no native web search, so anything current has to be supplied or fetched through a tool you connect.
Images, Video, and Handwriting
Google lists object detection, document and PDF parsing, screen and UI understanding, chart comprehension, multilingual OCR, and handwriting recognition. Video is analyzed as a sequence of frames. Text and images can be interleaved freely.
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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