Sunday, October 18, 2026

About Venice AI: Tokennomics for Privacy Nerds

Even before I ever subscribed to an AI app, I heard an ad for Venice AI on a podcast commercial over a year ago so I downloaded it to my phone. As I have been tokenmaxxing on my subscriptions as of late (not on purpose) I will be using Venice more. With the debut of Meta's Muse and it's large token allowance, I have thought more about privacy and just what am I giving to AI companies in exchange for using their products? With a free Muse account, Meta is compiling a dossier on it's users. Even "free" has a price. And even a paid account doesn't automatically mean you get to bypass the data brokers. Grok, for example, opts everyone in. OpenAI does too on free, Plus, and Pro accounts. I subscribe to ChatGPT Plus, their $20 a month plan. In researching "training data", I learned that even if you have a ChatGPT paid account like Plus or Pro, you are automatically opted in to having what you upload be used as "training data". So I opted myself out. Caveat -  even opting out does not opt you out if you provide feedback:

"Even if you have opted out of training, you can still choose to provide feedback to us about your interactions with our products (for instance, by selecting thumbs up or thumbs down on a model response). If you choose to provide feedback, the entire conversation associated with that feedback may be used to train our models."

So I decided to ask Venice AI what it has to offer for genealogy and what are the pros and cons of the model:  

Brickwall Research Plan by Venice AI on John Sisty

First, the actual numbers:


Venice publishes its tier limits directly, and they're stricter than most reviews claim. From Venice's own help documentation:

| Tier | Text prompts/day | Character prompts/day | Image requests/day |
|---|---|---|---|
| No account (anonymous) | 5 | 5 | 10 |
| Free account (email/wallet) | 10 | 5 | 16 |
| Pro | Unlimited | Unlimited | 1,000 |

Two footnotes matter enormously for genealogy: image prompt consumption varies by use case, and the Upscale & Enhance features can consume up to 20 requests per operation. Limits reset daily at 12:01 AM UTC.

Note the discrepancy: several third-party reviews cite "25 text + 15 image" for free. Venice's own page says 10 text / 16 images. Trust Venice's page. [Venice FAQ] 

What one unit of genealogy work actually costs

Genealogy is unusually expensive in prompts because it's verification-heavy — you rarely accept a first pass. Realistic costs on a free account:

| Task | Prompts |
|---|---|
| Transcribe one handwritten census page (vision) | 1, realistically 2–3 if the hand is bad |
| Translate one German/French/Spanish parish register entry | 1–2 |
| Extract structured fields (name, date, place, parents) from one record | 1 |
| Write an EE-style source citation | 1 |
| Draft a research plan for one brick wall | 1–2 |
| Cluster a DNA match list you paste in | 2–3 |
| OCR cleanup of a 5-page will (chunked) | 3–5 |
| Upscale one damaged ancestor photo | **up to 20 image requests** |
 
Three worked sessions

Session A — "One record, done properly." Free account, 10 text prompts.

1. Upload the 1880 census page → verbatim transcription
2. Second pass: flag every uncertain letter and why
3. Structured field extraction into a table
4. EE-format source citation
5. Cross-check the household against an index you paste in
6. Draft a one-paragraph research summary

That's 6. You have 4 left for corrections. Result: one record family taken to a defensible standard per day. Not a family line — one record.
 
Session B — "Batch transcription day." Free account, 10 prompts, 1 per page, zero correction budget. You'll realistically get 6–7 pages because you will need re-reads. A 30-page census district takes four to five days. This is the single biggest practical constraint on free-tier genealogy.

Session C — "Photo regeneration day." Free account, 16 image requests. Because a single Upscale & Enhance can burn up to 20 requests, one upscale can exhaust your entire daily image allowance and then some. Realistic output: two or three basic regenerations, or exactly one upscale if it runs long.

Session D — Anonymous. 5 text prompts. Enough for one transcription plus one citation. Nothing more.

Timezone hack worth knowing: the reset is 12:01 AM UTC. In US Eastern that lands at 8:01 PM EDT / 7:01 PM EST — so an evening session straddles the reset and you effectively double your daily allotment. Europeans (1:01 AM CET) get no such luck without staying up.

Give the Venice AI free account a test drive and comment if you have any successes. (Note: using the hyperlink will give us both credits for any Pro sign ups.)

For more on privacy in genealogy and AI, see the Coalition of Responsible AI in Genealogy craigen.org


 

Wednesday, October 14, 2026

ChatGPT for Genealogists: Models, Plans, Maps, and Privacy

(Graphic generated by Luna 6 Medium)

Two days ago, I hit my ChatGPT usage limit (aka "tokenmaxxing") while using Astra on Max. I had generated three maps and asked three follow-up questions when I hit the limit, so learned my lesson the hard way to toggle the model to save tokens. ChatGPT uses varying verbiage for usage; it does use the term "tokens"...sometimes...but weirdly, not most of the time.

The map I was generating was a map of where my ancestors lived in 18th century Westmoreland County, Virginia. I will eventually do a post about how to generate such a map, but ChatGPT still struggles to get the modern roads correct; so it is not quite there yet with accuracy. One of my cousins was generating a map using the free ChatGPT account and hit the usage limit which made me wonder about the differences between a free vs. paid account. My account is the $20 Plus plan. So I prompted ChatGPT to compile the following information about the different plans and suggested uses for genealogists. Lastly, I turned off the setting which allows what I enter to be used for "training data". Not that I am entering anything on living persons, etc. But just to be on the safe side. Note too how the setting is called, "Improve the model for everyone" - lol! Passive-aggressive guilt trip much, OpenAI?

Information checked October 14, 2026. Prices are in US dollars. Features, limits, and model access can change.

ChatGPT can help genealogists organize research, transcribe records, compare evidence, draft biographies, and create maps showing where ancestors lived. The model, the subscription plan, and the tools you can use are related, but they are not the same thing.

A model processes your request. Your plan affects which models and features are available and how much you can use them. Tools such as file uploads, data analysis, and image input help you work with source material.

Chat is suited to questions and discussion. ChatGPT Work is designed for larger tasks and reviewable results, such as a report made from uploaded records. Codex is intended for programming and other technical work. Most genealogists will begin with Chat or Work.

ChatGPT models made simple

Model names and availability can change. As of this review, GPT-6 is rolling out in Chat to eligible paid users. Free and Go users receive GPT-5.6 Luna as the default model. In GPT-6, the Instant, Medium, High, and Extra High thinking levels use GPT-6 Sol. The Pro thinking option uses GPT-6 Pro, powered by Astra. GPT-6.1 Sol is a separate option in Work and Codex, rather than ordinary Chat. Model access depends on your plan, account, workspace, and rollout status.

Model or optionWhat it is intended forPossible genealogy task
GPT-5.6 LunaEveryday questions and focused workOrganize notes or summarize a short transcription
GPT-6 InstantFast answers to everyday questionsAsk what a historical term in a record means
GPT-6 Medium or HighMore involved analysisCompare several records and identify unanswered questions
GPT-6 Extra HighThe highest GPT-6 Sol thinking levelReview a complicated timeline for contradictions
GPT-6 Pro, powered by AstraDifficult problems and longer tasksCompare competing identity hypotheses using multiple records
GPT-6.1 Sol in Work or CodexComplex work with attention to usagePrepare a chronology or sourced biography from supplied documents

These are suggested applications, not a guarantee that one model will produce accurate genealogical conclusions. Check the current model menu in your account.

Free and paid plans

Here are the main plans and listed prices relevant to individual genealogists and small groups:

PlanListed priceWhat may matter to genealogists
Free$0Everyday text chat; file uploads, data analysis, image creation, and other tools have separate limits
Go$8 per monthHigher limits than Free for eligible features such as file uploads, image generation, and data analysis
Plus$20 per monthAccess to additional models and Work; usage allowances still apply
Pro 100$100 per monthPro models, file uploads, deep research, and a larger included usage allowance
Pro 200$200 per monthMore included usage than Pro 100
Pro 500$500 per monthHighest Pro allowance; includes eligible Ultrafast access
Business$20 per user monthly with annual billing, or $25 monthlyFor at least two users; includes shared workspace and administrative features

Prices and features are subject to change. Pro 100 and Pro 200 do not include Ultrafast. Pro 500 does.

Free users can continue everyday text chats, subject to safeguards, but tools such as uploads and data analysis have separate limits. Paid plans provide higher limits for eligible features. Pro offers larger allowances, but it is not unlimited access to every model or tool.

A genealogist who asks occasional questions may find Free sufficient. Go or Plus may suit someone who regularly works with uploaded documents or spreadsheets. Pro may be useful for frequent, demanding projects, but the higher price makes sense only if the additional capacity meets a real need.

Creating an ancestral migration map

Both Free and Pro users can ask ChatGPT to help create a map, though their access to file uploads, data analysis, and other tools differs. Think of the examples below as sample project sizes, not promised plan limits.

Free examplePro example
Provide a short list of five verified locations for one ancestorUpload a spreadsheet with locations for several generations
Ask for labeled points and arrows showing the order of documented residencesAsk for separate colors for family branches, labels, dates, and a legend
Review the map and make a small number of revisions as your available usage permitsWork through multiple revisions or request separate versions for printing and presentation
If you reach a tool limit, wait for the reset shown in your accountCheck your usage before starting a large project; Pro still has an allowance

A clear prompt might say:

Create a migration map from the attached table. Label each ancestor, location, and year. Use verified coordinates and a geographic base map. Put uncertain locations in a separate list. Do not invent a route between documented residences.

A plotted map based on verified coordinates is different from an AI-generated picture that merely looks like a map. Check every place name and location against your sources. Treat generated historical images as illustrations, not evidence, and label them accordingly.

Tokens and usage limits

OpenAI uses the word tokens for small pieces of information that ChatGPT reads and writes. Your prompt, files, conversation history, tool results, and answer all contribute to token use. However, OpenAI does not publish one fixed token total for Free users or a single fixed token total for Pro users. So there is no reliable number to give for “Free tokens versus Pro tokens.”

OpenAI also describes subscription use with terms such as usage allowance, model allowance, and usage limits. In simple terms, an allowance is the amount of work included with your plan. You may have limits for a particular model, a time period, or a tool such as file upload or data analysis.

TermPlain meaningGenealogy example
TokensPieces of information the model processesA long probate file takes more processing than a short question
Usage allowanceThe work included with your planComparing a set of records and drafting a biography uses some of your included access
Model allowanceA limit for using a particular modelAstra may become unavailable after you have used its allowance
Tool limitA separate limit for a featureYou might still be able to chat after reaching a file upload limit
Reset timeWhen access becomes available againChatGPT may show when you can use the affected model or tool again

The same number of messages can use different amounts of allowance. A short request to compare several deeds, tax lists, and probate records may require more work than a longer request to alphabetize names. OpenAI says usage depends on the model, context, reasoning settings, and tools used.

OpenAI publishes estimates for local Work and Codex messages on Plus, within a five-hour window. These are estimates, not guaranteed counts, and they do not apply as Free or Pro message limits.

ModelEstimated Plus messages in five hours
GPT-6 Astra5 to 45
GPT-6.1 Sol15 to 160
GPT-6 Sol15 to 150
GPT-6 Luna350 to 3,000

Weekly limits may also apply. Pro has no five-hour usage limit in Work and Codex, but it still has an included allowance. GPT-6 Pro in Chat has separate limits. Your actual available use depends on your plan, model, task, and settings. Check Settings → Usage for your allowance and reset times.

For example, asking Astra to read a group of deeds, resolve uncertain place names, compare conflicting evidence, and prepare a sourced explanation can consume more allowance than asking it to summarize one document. Your experience of reaching an Astra limit is consistent with OpenAI’s guidance: Pro users can reach model limits too. Depending on the feature and account, you may need to wait for a reset, switch to another available model, or use eligible credits. Switching models does not replenish a shared Work and Codex allowance.

To make usage go further, upload only the relevant records, state the exact question, and request the format you need. You might first ask for a transcription with uncertain readings marked, then ask for a comparison of the transcribed documents. Higher reasoning effort can use more allowance and does not always improve the result.

Privacy and uploaded family records

Yes, OpenAI may use content from personal Free and Pro accounts to improve its models when the relevant setting is on. This can include content from conversations and eligible uploads. The setting can be turned off on either plan.

To opt out, open Settings → Data Controls and turn off Improve the model for everyone. New conversations will not be used for model training after you opt out. Your chats can remain in your history. Turning this setting off does not delete saved conversations or files. If you submit feedback on a response, OpenAI says the conversation associated with that feedback may still be used to improve models.

CRAIGEN, the Coalition for Responsible AI in Genealogy, states its Privacy Principle this way: genealogists should take reasonable measures to safeguard private information when using AI. For family history work, consider removing names, exact birth dates, addresses, and other identifying details about living people when they are not needed. Take particular care with adoption records, health information, and DNA match lists. CRAIGEN’s privacy principle and practical privacy guidance offer further advice.

Whatever plan you use, check transcriptions against the original images, follow cited links to the underlying records, and verify names, dates, relationships, and map locations. CRAIGEN’s Accuracy Principle calls for checking AI-generated information against other records and acknowledging credible sources.

Sources

  1. OpenAI, Use ChatGPT.

  2. OpenAI, GPT-6 and other models in ChatGPT.

  3. OpenAI, Model selection.

  4. OpenAI, Pricing, tokens, and usage allowances.

  5. OpenAI, Managing usage with GPT-6 Astra in Work and Codex.

  6. OpenAI, About ChatGPT Pro tiers.

  7. OpenAI, ChatGPT Free Tier FAQ.

  8. OpenAI, Data controls in ChatGPT.

  9. OpenAI, How your data is used to improve model performance.

  10. OpenAI, Data analysis with ChatGPT.

  11. Coalition for Responsible AI in Genealogy, Guiding Principles.

  12. Coalition for Responsible AI in Genealogy, Key Action Points for Protecting Privacy.

Disclaimer: This post was compiled by Katherine Borges and ChatGPT. Katherine Borges has no paid affiliation with OpenAI. This post is for informational purposes only.


Tuesday, October 13, 2026

OpenAI DevDay 2026: What Dots, Spaces, and the New Tools Could Mean for Genealogists

OpenAI's DevDay keynote on September 29 included more than 20 announcements. Most were aimed at developers and businesses, but several of them line up well with the daily work of genealogists: long research projects, piles of records to transcribe, shared family trees, and sensitive DNA data. The Neuron podcast hosts reacted live, and I watched the replay with a genealogist's eye.

Dots: an assistant that keeps working

The headline announcement was Dots, an always-on personal agent built into ChatGPT. Dots has its own cloud computer and browser, connects to more than 4,000 apps through ChatGPT plugins, and keeps working in the background. OpenAI's demos showed Dots reviewing overnight messages, rebuilding a slide deck, rescheduling a conflict, and fixing software bugs. Dots is included in the plan and does not count against usage. It is available now to Pro, Business Premium, and Enterprise users.

Steve Little introduced me to Dots last week and showed me how to use it like an assistant, and that framing is the key. Think of a research assistant who drafts the correspondence, organizes the research log, summarizes what came in overnight, and reminds you what is waiting for your review. For a genealogist juggling several projects, that is a very different tool from a chatbot you have to prompt from scratch every time.

One personal observation: Dot's speech pattern sounds to me very "Silicon Valley Californian". In the keynote demo, Dots was upbeat and casual, even handing out wedding advice. Dots is like having an Astra-level smart Alexa or Google Nest that you can converse with; so you could talk through a brick wall problem on the drive home from the courthouse or archive and have Dots pick up the thread when you sit back down at your desk.

Spaces: a shared workspace for research teams

ChatGPT Spaces gives teammates and Dots a shared place to work on pages, files, and data. Someone can tag Dots in a comment and it gets to work. For genealogists, the obvious fits are family history societies, project volunteers, and cousins collaborating on a shared line. A space could hold a research log, a source list, and a draft write-up, with Dots keeping the log current while the humans make the judgment calls. OpenAI also said a collaborative presentation feature is coming, which could help with society talks.

Codex in the cloud: long jobs without babysitting

Codex now runs fully in the cloud, so a task started on a phone keeps running after the laptop closes. For genealogists who build their own scripts, this suits the long, tedious jobs: batch processing record images, cleaning and merging spreadsheets of census extractions, or analyzing large sets of DNA matches. You hand off the task and check on it later.

Speed and cost: Sol, Ultra fast, and cheap cached input

GPT-6.1 Sol is described as delivering close to Astra-level intelligence at about a fifth of the price, and cached input is discounted by 95 percent. Caching matters for genealogy because research is full of repeated context. When you work through a long run of court records or a family file, the same background material gets reread again and again, and cached input makes that far less expensive. Ultra fast mode runs about eight times faster at six times the price, which most genealogists will not need but may enjoy for large transcription batches.

The new Decisions API answers from a fixed set of options in a fraction of a second. It is built for routing and classification, which could suit sorting a pile of unlabeled images into record types, such as deeds, wills, or probate inventories.

Privacy: the item genealogists should watch most closely

OpenAI previewed Private Intelligence, which pairs zero data retention with private safety processing, with private inference coming this fall. Genealogists handle sensitive material, including DNA results, living relatives' details, and unpublished family stories. The hosts called this the most significant item for enterprises and predicted every provider will offer something similar by January 1. If it works as described, it could ease one of the biggest concerns about putting genetic and family data into AI tools. Genealogists should still read the fine print on what is retained, who can access it, and what counts as an approved safety purpose.

Tools for the people who build genealogy software

Sign in with ChatGPT lets users spend their own plan's tokens inside third-party apps. For the small developers behind genealogy tools, that removes the burden of paying for every user's AI costs. Plugin extensions let developers build full applications inside ChatGPT, and the new OpenAI Marketplace gives them a way to reach customers. It is easy to imagine tree builders, record indexes, and DNA analysis tools showing up in that ecosystem.

Cautions

Dots and most of the new products are not yet available in the EU or UK, which leaves many genealogists waiting. The hosts also urged viewers to treat vendor-published benchmarks as marketing, since each lab picks the comparisons that flatter it.

That brings up a term worth knowing: benchmaxxing. It means tuning a model, or the way its results are presented, to score as high as possible on public benchmark tests rather than to be better at real work. A model can post impressive numbers on a coding or math test and still stumble when asked to read a faded deed or untangle two men of the same name. Test any new tool on your own records and your own research questions before trusting it. Whatever an assistant produces, a genealogist's standards do not change. Cite the source, check the original, and keep the human in charge of the conclusions.

The takeaway

Most of what OpenAI shared is about making AI easier to use and easier to fold into daily work. For genealogists, the promise is an assistant that handles the tedious parts of research while you handle the evidence. The new privacy options and cheaper cached input make that more realistic, and the shared Spaces make it easier to work as a team.

Compiled by Katherine and Claude (Sonnet 5.5 Medium). Source: The Neuron's OpenAI DevDay 2026 live watch party on YouTube.


Monday, October 12, 2026

Match the Model to the Task: A Genealogist’s Guide to Saving Time and Tokens


Match the Model to the Task: A Genealogist's Guide to Saving Time and Tokens

I tokenmaxxed today. I was working with frontier model ChatGPT's Astra on Max level to create a map. The third generation of the map was what I wanted. I asked Astra two more questions and hit my token limit. The questions were simple ones so I should have dropped to a lower model and strength to preserve tokens. Live and learn. The point is that waste comes from paying frontier prices for simple work; or from redoing cheap work that failed. So Claude's Fable 5.1 Medium compiled this article with this human's input and review to help genealogists figure out how to conserve tokens.

Every major AI company now sells a ladder of models. At the top are frontier models such as Claude Fable 5.1 and GPT-6 Astra. At the bottom are small, fast models such as Claude Haiku 5.5 and GPT-6 Luna. The top of the ladder costs up to 100 times more per token than the bottom. The bottom makes more mistakes. Knowing which rung fits which genealogical task saves both money and hours of rework.

The current ladder

Prices are per million tokens, input and output, as of October 12, 2026.

TierModelInputOutput
FrontierClaude Fable 5.1$10.00$50.00
FrontierGPT-6 Astra$10.00$50.00
Upper middleClaude Opus 5.5$4.00$20.00
MiddleClaude Sonnet 5.5$2.00$10.00
MiddleGPT-6.1 Sol$2.00$10.00
MiddleGemini 3.1 Pro$2.00$12.00
MiddleGemini 3.8 Flash$0.75$3.75
EconomyClaude Haiku 5.5$0.10$0.50
EconomyGPT-6 Luna$0.10$0.50

Sources for the table are the three companies' price lists. [1][2][3] The Gemini 3.8 Flash price is promotional and doubles on January 1, 2027. [3] Google announced Gemini 4 Argon on September 30 at an introductory $2 and $10, but it was limited to testers and top-tier subscribers at announcement and is not yet on Google's public price list. [3][4]

Where the tokens go

Most genealogists pay a flat subscription, so tokens show up as usage limits instead of a bill. Either way, three things drain them.

The first is price. A frontier model burns through an allowance far faster than a middle model doing the same job.

The second is thinking. Reasoning tokens are billed but never shown. First Page Sage found they made up 22.4% of billed tokens across its 14-task study and were the largest hidden cost. [7] Effort settings matter here: at maximum effort, Claude Opus 5.5 used about 119,000 output tokens per benchmark task, Fable 5.1 about 78,000, and GPT-6 Astra about 27,000. [5]

The third is failure. Cheap models are not always frugal. GPT-6 Luna used about 51,000 output tokens per task against 31,000 for the larger GPT-6 Sol. [6] In the First Page Sage content test, the two cheapest models had 45% and 48% of their drafts thrown away, against 9% for the best model. [7] A discarded answer costs tokens and your time.

Transcribing English handwriting: middle tier, thinking turned down

This is the best-tested genealogy task, and the evidence says not to pay for the top rung. Mark Humphries measured Gemini 3 Pro at a 1.67% character error rate on 18th and 19th century English documents, with the best results at the lowest thinking setting and a cost of about one cent per page. [8] Nicole Elder Dyer found Gemini 3 Flash slightly better than Pro, and on one North Carolina deed it scored 1.22% against 5.61% for Transkribus. She advises turning extended thinking off, because reasoning modes tend to "correct" old spellings. [10] A Dutch test found that limiting the Flash model's reasoning budget raised its score from 47% to 67%. [11]

For transcription, then, extra thinking costs more and can make the result worse. Using Humphries's token counts, my rough estimate is a third of a cent per page at Gemini 3.8 Flash prices and about four cents at frontier prices, before any reasoning tokens. One caution: these tests used earlier Gemini versions, and I found no published handwriting test of Gemini 3.8 Flash. Claude Opus 5.5 can no longer run with thinking switched off, so set its effort to low instead. [19]

Checking a transcription: a second middle model

Spend the savings on verification. Humphries had two other models compare their readings with the first. They flagged 374 disagreements, 106 of them real errors, and a human had to review only about 4% of the text. [9] Names, dates, and places remain the weakest spots, so check each one against the image. [10][14]

Difficult hands and other languages: step up, and still verify

On the University of Basel's benchmark, updated October 6, the top scores for 15th century German manuscripts were Claude Fable 5 at 88.4 and GPT-6 Astra at 87.1. Claude Sonnet 5.5, at one fifth the price, scored 85.9. [12] A 29-language benchmark found the best models still had handwritten character error rates near 30%. [13] Start in the middle, move to a frontier model for pages that defeat it, and use a specialized tool such as Transkribus alongside. [10]

Tables, registers, and index cards: middle tier

Extraction from structured records does not reward the most expensive models. On the Basel benchmark, Gemini 3.8 Flash led on meeting minutes at 95.5, and Claude Sonnet 5.5 led on library cards at 91.4. [12] In the Dutch test, Gemini read a 23-column register in one pass. [11] Dyer notes that censuses and tax lists are still harder than prose. [10]

Economy tier: text in, text out

Use the cheapest models for reformatting a clean transcription, sorting a list, or summarizing typed text. Do not use them to read images. Claude Haiku 4.5 scored 19% in the Dutch handwriting test, against 75% for the best model. [11] Haiku 5.5 and GPT-6 Luna have no published handwriting results.

Writing: middle to upper middle

The First Page Sage data covers the previous generation, but the pattern is useful: Claude Opus 5 and Sonnet 5 needed the fewest revisions, and Sonnet 5 finished cheaper than a model with a lower first-draft price. [7] Denyse Allen reports the same preference for Claude in family narratives. [16] Their successors, Opus 5.5 and Sonnet 5.5, are the reasonable picks.

Evidence analysis and proof arguments: where frontier models earn their price

Correlating conflicting records across a large file is the task where a wrong answer costs the most. Opus 5.5 currently holds the highest Artificial Analysis Intelligence Index score at 58, and Fable 5.1 and Astra sit in the same class. [5] No published benchmark tests genealogical reasoning, so this recommendation rests on general measures. A sensible rule from developer practice applies: start with the cheapest model likely to succeed, and when its answer fails your check, move up a tier instead of retrying. [15]

Finding records: not a chatbot task

Chat models do not search archives. FamilySearch Full-Text Search covers nearly 2 billion records in English, Spanish, and Portuguese. [17]

Quick reference

TaskTier to useEffort setting
English handwritingMiddle (Gemini Flash or Pro)Low or off
Checking a transcriptionSecond middle modelLow
Hard hands, other languagesMiddle, then frontierMedium
Tables and registersMiddleLow to medium
Reformatting clean textEconomyLow
Narrative writingMiddle to upper middleMedium
Evidence analysisFrontierHigh

Whatever the tier, the Coalition for Responsible AI in Genealogy asks us to verify AI output against the records and to disclose its use. [18]

Sources

  1. Anthropic, "Pricing," Claude Platform Docs, accessed October 12, 2026. https://platform.claude.com/docs/en/about-claude/pricing
  2. OpenAI, "Pricing," API documentation, accessed October 12, 2026. https://developers.openai.com/api/docs/pricing
  3. Google, "Gemini Developer API pricing," accessed October 12, 2026. https://ai.google.dev/gemini-api/docs/pricing
  4. "Google announces Gemini 4 Argon as its new frontier model," 9to5Google, September 30, 2026. https://9to5google.com/2026/09/30/gemini-4-argon-announcement/
  5. Artificial Analysis, analysis of Claude Opus 5.5, September 22, 2026. https://artificialanalysis.ai/articles/claude-opus-5-5
  6. Artificial Analysis, analysis of GPT-6 Sol and Luna, September 22, 2026. https://artificialanalysis.ai/articles/gpt-6-sol-and-luna-push-the-cost-efficiency-frontier
  7. Evan Bailyn, "AI Token Usage Cost by Model: OpenAI vs. Anthropic vs. Google," First Page Sage, September 9, 2026. https://firstpagesage.com/seo-blog/ai-token-usage-cost-by-model/
  8. Mark Humphries, "Gemini 3 Solves Handwriting Recognition and it's a Bitter Lesson," Generative History, November 25, 2025. https://generativehistory.substack.com/p/gemini-3-solves-handwriting-recognition
  9. Mark Humphries, "When Models Disagree...Transcription Accuracy Improves Significantly," Generative History, May 27, 2026. https://generativehistory.substack.com/p/when-models-disagree-transcription
  10. Nicole Elder Dyer, "AI-Powered Transcription of Handwritten Documents," RootsTech 2026 syllabus. https://cms-z-assets.familysearch.org/3e/69/1106b1c7ad61708fa9c63d714652/syllabus-for-ai-powered-transcription-of-handwritten-documents.pdf
  11. Lieuwe Jongsma, "Can a general LLM really just read handwriting?" Neerlandistiek, June 21, 2026. https://neerlandistiek.nl/2026/06/can-a-general-llm-really-just-read-handwriting/
  12. University of Basel, RISE Humanities Data Benchmark, version 0.6.1, updated October 6, 2026. https://rise-services.rise.unibas.ch/benchmarks/p/benchmark-results/
  13. Mélodie Boillet, Solène Tarride, and Christopher Kermorvant, "METATR: A Multilingual, Evolving Benchmark for Automatic Text Recognition," arXiv, May 26, 2026. https://arxiv.org/abs/2605.26712
  14. Steve Little, "When the Machine Finally Learned to Read: Gemini 3 and the Question of 'Good Enough,'" AI Genealogy Insights, December 16, 2025. https://aigenealogyinsights.com/2025/12/16/when-the-machine-finally-learned-to-read-gemini-3-and-the-question-of-good-enough/
  15. Satvik Paramkusam, "AI Model Routing in 2026: When to Use Fable, Astra, Gemini or Muse," Build Fast with AI, September 9, 2026. https://blog.buildfastwithai.com/ai-model-routing-2026-fable-astra-gemini-muse
  16. Denyse Allen, "My practical AI toolkit for family history for 2026," Chronicle Makers, December 3, 2025. https://denyseallen.substack.com/p/practical-ai-toolkit-genealogy-2026-chatgpt-claude-gemini-perplexity
  17. FamilySearch, "Full-Text Search: A Powerful Tool for Making Genealogy Discoveries," October 18, 2025. https://www.familysearch.org/en/blog/what-is-full-text-search
  18. Coalition for Responsible AI in Genealogy, "Guiding Principles for Responsible AI in Genealogy," adopted by the National Genealogical Society, May 2025. https://www.ngsgenealogy.org/wp-content/uploads/2026/01/Responsible-Use-of-AI.pdf
  19. Anthropic, "Claude Opus 5.5," September 22, 2026. https://www.anthropic.com/claude-opus-5-5

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Even before I ever subscribed to an AI app, I heard an ad for Venice AI on a podcast commercial over a year ago so I downloaded it to my ph...