ChatGPT

Claude vs ChatGPT for Astronomy

OpenAI and Anthropic document different file limits, plan prices, and context allowances for astronomy work, while both warn that generated answers can be inaccurate.

Sources checked 2 Oct 2026

For Claude vs ChatGPT in astronomy, [OpenAI documents file uploads], [Anthropic documents supported files and images], and their [ChatGPT pricing] and [Claude pricing] pages set different plan, context, and usage rules. Neither documentation set establishes comparative astronomy accuracy, and [Chat Picker has not tested either assistant for astronomy]. The comparison below separates published constraints from checks you can run on your own material.

What the vendors document

The vendor figures below were read on October 1, 2026.

[OpenAI’s File Uploads FAQ] says uploads are available on Free and paid plans, subject to account and plan limits. It sets a 512 MB hard limit per chat file, a 2M-token cap for each text or document file, approximately 50 MB for a spreadsheet, and 20 MB per image; Free accounts have three uploads per day.

[Anthropic’s upload-files help page] lists PDF and common document formats plus JPEG, PNG, GIF, and WebP images. It sets 500 MB per chat upload and 30 MB per project file. Claude analyzes text and visual elements in PDFs of 100 pages or fewer; from 101 to 1,000 pages, it processes text only, and it cannot interpret embedded images in non-PDF documents.

The [OpenAI upload FAQ] and [Anthropic upload page] do not state whether FITS files are supported or promise validated JWST photometry.

On the same read date, [OpenAI’s pricing page] lists ChatGPT Plus at $20 per month. [Anthropic’s pricing page] lists Claude Pro at $20 monthly or $17 per month with annual billing, with $200 paid up front. Both offer free access: Anthropic lists web search, file creation, code execution, and memory on Free, while OpenAI lists limited uploads, images, voice, and deep research. Their pricing pages describe usage qualitatively rather than publishing exact message counts. OpenAI lists context allowances by plan and model family; Anthropic says context can reach 1M on every plan and varies by model.

For data handling, [OpenAI’s pricing page] says an opt-out from training on chats is available on Free, Go, Plus, and Pro. [Anthropic’s pricing page] says an opt-out is available on Free, Pro, and Max, while Team is not trained on by default.

[OpenAI’s accuracy note] says ChatGPT may be incorrect or misleading and can sound confident when wrong; it also notes a knowledge cutoff unless tools are used. [Anthropic’s note] says Claude can hallucinate, should not be a sole source of truth, and that cited sources and original pages need review. Those cautions apply directly to astronomy references, observations, and image interpretations.

What the documentation cannot tell you

The cited pages do not document how either assistant handles a particular spectrum, FITS cube, catalog, target list, or telescope setup, and they supply no astronomy-specific test. A controlled trial can show whether an upload is accepted, a table is read as intended, citations remain visible, controls are understandable, and the limits shown to your account fit the task.

The [Chat Picker method] supplies no quality, speed, accuracy, reliability, or benchmark results. This page also replaces an older version that used statistics and test results without sources.

How to check it yourself

Stellar evolution and nucleosynthesis. Give both assistants this prompt: “Compare the evolutionary paths of a low-mass main-sequence star and an intermediate-mass main-sequence star. Separate core and shell nucleosynthesis, mass loss, and remnant outcomes. Flag assumptions and cite a source for every quantitative statement.” Check whether the distinctions remain consistent and whether the citations lead to relevant sources. Record unsupported claims, missing assumptions, and citation problems.
Observation planning. Give both: “I am a beginner using a manual telescope, a printed star atlas, and a laptop. Ask me for my location, date, sky brightness, aperture, and eyepiece constraints before proposing a shortlist of targets. For each target, explain its visibility, seasonal limits, and suitability for binocular or telescope observation.” Look for relevant clarification instead of invented details. Write down any unsupported visibility claim or impractical recommendation.
JWST image interpretation. With a JWST image attached, give both: “List only claims supported by this image. Separate visual description from astrophysical inference, name the metadata needed to verify filters, wavelengths, scale, and exposure, and do not assign physical values that are not shown.” Record upload failures, unsupported identifications, and missing requests for instrument metadata.
Tables and PDFs. Give both a CSV with columns for object name, filter, magnitude, and uncertainty, then ask: “Identify one pattern, show every calculation, state the units, and do not infer missing values.” Look for transparent calculations and clear separation between supplied data and assumptions. Record invented values, unit errors, and misleading rounding.
Interface, usage, and cost. Repeat the image and table tasks with identical files and prompts in the interface and plan you currently use. Look for upload errors, source controls, data-setting controls, and visible usage warnings. Record each interruption and limit message, then check the vendor’s current price before subscribing. Choose by fit for your workflow, not by confident wording alone.

Which rows of the comparison matter

In the [Claude vs ChatGPT comparison matrix], focus on Free plan, Low-cost tier, Main paid plan, Heavy-use plans, Context window, How usage limits are described, and Training on your chats. The plan rows help define cost and access; the context and usage rows affect recurring work; the training row matters when material is unpublished.

Every figure in the matrix carries its vendor source and read date. Values that could not be confirmed are marked “Not verified” and left blank, so the matrix can narrow your plan choice without turning undocumented differences into a quality ranking.