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Anthropic

Anthropic: Claude 3.7 Sonnet

This model is deprecated

Claude 3.7 Sonnet and can no longer be run here. Its evaluation results and details remain available for reference. Try Claude Sonnet 5 instead.

Claude 3.7 Sonnet Overview

Claude 3.7 Sonnet, released by Anthropic in February 2025, is the company’s first hybrid reasoning model, combining fast response generation with an optional “extended thinking mode” that reveals longer, step-by-step reasoning. Like its predecessors, it is multimodal, handling both text and images, but expands its usability with up to 200,000 input tokens and up to 128,000 output tokens (64K generally available, 128K in beta). This makes it well-suited for analyzing large documents, codebases, or multi-turn conversations.

Typical applications include software development, research workflows, extended reasoning tasks, and enterprise-scale knowledge work where a trade-off between speed and visible reasoning is valuable.

Claude 3.7 Sonnet Details & Performance

Details

Resources

Vision Tasks

CaptioningChart Question AnsweringClassificationDocument Question AnsweringImage TaggingMulti-Label ClassificationOCRObject DetectionVision LanguageVisual Question Answering

Features

Foundation VisionLLMs with Vision CapabilitiesMultimodal Vision

Usage

Past 30 Days

Not available

Not in Playground

Performance

Avg. Latency

Claude 3.7 Sonnet Vision Evals

Claude 3.7 Sonnet has been deprecated by its provider and can no longer be evaluated on the current benchmark. The legacy Vision Evals results below are preserved for reference. See the current Vision Evals

Visual Understanding

77 models · 67 tasks
HighestLowest
This model#46 of 7759.7% pass rate · better than 35%
Score59.7%pass rate across 67 tasks
Speed15.48savg response per task
Costpricing unavailable
Tokenstokens unavailable
Score key:≥75%40–74%<40%
CategoryPassedScore
Document Understanding8 / 9
88.9%
Defect Detection10 / 15
66.7%
Object Understanding9 / 14
64.3%
Spatial Understanding11 / 19
57.9%
Object Counting2 / 10
20%

Scores based on a single evaluation run · Methodology

View all legacy Vision Evals results →

Price vs. performance

Estimated cost per task vs. Visual Understanding score, for this model and others ranked near it. Upper-left is the sweet spot (high quality, low cost). Based on Vision Evals (legacy) results.

10 of 11 models plotted · 1 not yet evaluated

Alternatives to Claude 3.7 Sonnet

Other models worth comparing for similar use cases.

Google
Gemini 3 Flash
Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.
OpenAI
GPT-5 Mini
GPT-5 Mini, released by OpenAI on August 7, 2025, is a mid-tier variant of the GPT-5 family that balances cost, speed, and capability. It is multimodal, supporting both text and image inputs, and offers a substantial input context window of ~400,000 tokens with output lengths up to ~128,000 tokens. While less powerful than the full GPT-5, it inherits its safety tuning, instruction-following improvements, and multimodal reasoning, making it a practical choice for developers who need large context handling without the expense of premium models.GPT-5 Mini is optimized for affordability while retaining strong reasoning performance. Benchmarks show it outperforming earlier models such as GPT-4o on many multimodal and medical VQA tasks, though it lags behind GPT-5 on the most complex problems. Ideal use cases include prototyping, scalable content generation, document analysis, and mid-range reasoning tasks where efficiency and context capacity matter more than top-tier accuracy.
Qwen
Qwen3 VL 30B A3B Instruct
Qwen3 VL 30B A3B Instruct is an open-weight multimodal large language model developed by Alibaba as part of the Qwen family, built for instruction-following tasks that unify text generation with visual and video understanding. Released around October 2025 under the Apache-2.0 license, it targets efficient, high-fidelity vision-language reasoning across very long contexts.The model accepts text and image inputs and produces text outputs, with strong performance in OCR, spatial reasoning, long-video understanding, and agentic or GUI-centric visual tasks. It uses a Mixture-of-Experts (A3B) design with ~31.1B total parameters and ~3B active per token, paired with Qwen3-VL’s unified multimodal stack (including Interleaved-MRoPE and DeepStack fusion) to process text, images, and video in a single architecture. OCR support expands to 32 languages, enhancing document workflows. With a native ~262K token context window (extendable further), it stands out today for its balance of scale, efficiency, long-context support, and open accessibility in multimodal systems.

Other Anthropic Sonnet models

Other versions in the same family as Claude 3.7 Sonnet.

Claude 3.7 Sonnet License

Proprietary

Claude 3.7 Sonnet is proprietary: the weights are not distributed, and the Claude 3.7 Sonnet license is the vendor's commercial terms of service that you accept when you call the API.

Commercial use
Permitted under the vendor terms, typically metered per token or per request, with the vendor usage policy applying to your inputs and outputs.
Modification
Not available. Claude 3.7 Sonnet weights are closed, so you can configure prompts and use vendor-hosted fine-tuning where it is offered, but you cannot modify the model itself.
Redistribution
Not permitted. You cannot self-host or resell the model; you build on the hosted API instead.

Vendor terms govern data retention, whether your inputs can be trained on, rate limits, and regional availability, and they can change with notice. Review them if you handle regulated or customer data.

Do I need a commercial license for Claude 3.7 Sonnet?

Proprietary terms are set by the vendor rather than negotiated per project, and no open-source obligation attaches to your code. If you would rather deploy a model whose commercial license is included in your plan — on Roboflow Managed Cloud or a Self-Hosted Inference Server — Roboflow's licensing page lists the supported alternatives to Claude 3.7 Sonnet.

Do not hesitate to reach out with questions for your commercial project — our team will help you start solving business problems on the first call. See Roboflow commercial licensing for the models included in each plan.

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This model is proprietary. The author retains all rights, and use of the model is governed by their specific terms of service or license agreement.

Commercial use depends on the terms set by the model author. Most proprietary commercial models require a paid subscription, API key, or per-call billing. Check the provider’s pricing and terms-of-service for details.

License information is provided as a guide and is not legal advice.

Frequently Asked Questions About Claude 3.7 Sonnet Vision

Yes. Claude 3.7 Sonnet accepts image input, and on Roboflow's previous vision benchmark it passed 59.7% of visual understanding tasks (#46 of 77).

Claude 3.7 Sonnet has been deprecated by its provider and can no longer be run, so it is not part of Roboflow's current Vision Evals. Its results from the previous benchmark are preserved on this page for reference.