Comparing AI Assistants for Energy Analysis

Vendor pages document energy-analysis file, research, plan, and accuracy controls, but they do not establish which assistant performs best.

Sources checked 2 Oct 2026

Vendor pages establish what ChatGPT, Claude, and Gemini document about energy-data files, research, plan limits, and accuracy cautions; they do not establish which analyzes energy data best. Chat Picker has not tested the assistants for this use or produced its own quality scores. Compare documented fit, then run the same controlled tasks on the plans and tools you expect to use.

What the vendors document

Files and visual evidence. OpenAI says ChatGPT can inspect uploaded data, create tables or charts, and review code-backed analysis; it recommends clear column names and one record per row (OpenAI’s data analysis guide, as read on October 1, 2026). Anthropic says Claude accepts CSV and XLSX, but XLSX requires code execution and file creation; its upload guide also distinguishes visual PDF analysis from text-only processing (Anthropic’s file-upload guide, as read on October 1, 2026). Google says Gemini Apps supports most file types and up to 10 supported files per prompt, subject to availability (Google’s Gemini file-upload guide, as read on October 1, 2026).

Research and sources. OpenAI says Deep Research can combine uploaded files, searches of the public web or specific sites, and enabled apps; it produces a reviewable research plan and a report with citations, while usage varies by plan (OpenAI’s Deep Research guide). Claude says Research is available to paid Pro, Max, Team, and Enterprise users, requires web search, and can use connected internal context as well as the web (Anthropic’s Research guide). Gemini says Deep Research includes Google Search by default and can use uploaded files, NotebookLM notebooks, and connected Gmail or Drive sources (Google’s Deep Research guide).

Plans, context, and usage. Free plans are listed on OpenAI’s pricing page, Anthropic’s pricing page, and Google’s US AI plans page. As read on October 1, 2026, ChatGPT Plus is $20 per month, Claude Pro is $20 per month, and Google AI Pro is $19.99 per month. Confirm current regional prices before subscribing.

As read on October 1, 2026, OpenAI’s pricing page lists a 27K Instant context window on Free and 54K on Plus. Anthropic’s pricing page says Claude offers up to 1M context on every plan, varying by model. The Google AI plans page does not state an app token figure. OpenAI and Anthropic do not publish exact message counts on their pricing pages, while Google describes compute-based limits with a weekly ceiling.

Data and accuracy. OpenAI lists a chat-training opt-out for Free, Go, Plus, and Pro; Anthropic lists one for Free, Pro, and Max and says Team is not trained on by default (OpenAI pricing; Anthropic pricing). The Google plans page does not state a chat-training setting. Check the controls on your exact account before uploading confidential load, tariff, or customer data.

OpenAI says ChatGPT can produce incorrect or misleading answers and may sound confident when wrong (OpenAI’s accuracy guidance). Anthropic says Claude can also be incorrect or misleading and should not be your only source of truth; it recommends checking original sources for missing context (Anthropic’s incorrect-response guidance). Google says Gemini Apps sometimes display related sources (Google’s source-viewing guide). Gemini’s policy says it should not generate factually inaccurate outputs that could cause significant real-world harm, including erroneous disaster alerts; that policy is not evidence that a particular answer is correct (Google’s safety guidelines).

What the documentation cannot tell you

Vendor pages cannot show how an assistant will handle your energy data. They do not establish whether it will misread timestamps, omit missing intervals, apply a tariff rule incorrectly, confuse correlation with causation, express uncertainty properly, or reproduce a chart without errors. File and context ceilings describe capacity, not correctness. Likewise, a citation only shows that a source is presented unless you inspect the original material.

Use a representative, sanitized dataset. Repeat the same task, and keep the plan, model or mode, tools, and prompt stable where the interface allows.

How to check it yourself

Use nonconfidential or sanitized data and define your pass-or-fail checks before starting.

Task design and scoring. Attach a CSV with timestamp, region, demand_mw, temperature_c, and tariff_period. Prompt: “Using the attached CSV, calculate total energy in MWh, peak demand in MW, and mean temperature in Celsius. Show the row count, formula for each metric, missing-value rule, and every anomaly you cannot explain.” Check units, time-zone handling, missing intervals, and unsupported claims. Record the formulas, assumptions, and discrepancies against your source.
Calculation audit. Attach a demand file and a tariff table. Prompt: “Calculate the energy charge and demand charge for each billing period. Show every joined column, unit conversion, tariff category, and formula. Do not infer a missing tariff rule.” Look for duplicate intervals, inconsistent units, unexplained exclusions, and arithmetic that cannot be reproduced. Write down each discrepancy.
Research traceability. On the plan you expect to use, enable web research if available. Prompt: “Identify current primary-source rules for measuring and verifying a demand-response event in the United States. Link each source, quote the relevant passage, state its publication date, and separate quoted requirements from your interpretation.” Inspect whether each source supports the associated claim. Record missing links, unsupported statements, and interpretations not present in the source.
PDF and chart extraction. Attach a report containing a chart labeled “Monthly demand profile.” Prompt: “Transcribe the chart’s axes, units, legend, and plotted values into a table. Cite the PDF page label and mark anything illegible instead of guessing.” Compare the table with the visible chart. Record altered labels, missing series, unsupported values, and incorrect page references.
Repeatability and version controls. Repeat the tariff prompt in a fresh chat without the earlier answer. Prompt: “Recalculate the billing-period totals from the attached files. List every assumption, show the calculation, and identify any missing or ambiguous input before giving a result.” Record the plan, tools, research toggles, and exact model or mode label if shown. Note changes in calculations, assumptions, source coverage, or stated uncertainty.

Which rows of the comparison matter

In Chat Picker’s three-way comparison matrix, start with Free plan, Main paid plan, Context window in the app, How usage limits are described, and Training on your chats. Add Heavy-use plans for repeated batch analysis and Ads if your organization has an advertising restriction.

Check the linked vendor source and read date for every figure. Treat “Not verified” as an unknown, not as zero or as evidence that a feature is absent. The matrix can help you shortlist plans, but file handling, research access, and analytical performance still need to be checked against current vendor pages and your own test.