This page compares two current models on one job: turning ordered slide screenshots into a written summary a stakeholder can read without opening the deck. It looks at numerical accuracy, cost and a fair way to test both on your own decks.
Sep 1, 2026 · 10 min read
Claude Fable 5 is the safer default when keeping the actual numbers straight is the deciding requirement. Gemini 3.6 Flash is the better economic choice for bulk extraction and acceptable first-pass quality.
That split rests on the closest public professional-document benchmark, where Fable 5 more than doubles Gemini 3.6 Flash's strict pass rate1, set against Gemini's published rate, which runs at a fraction of Fable's on both input and output5. Fable's own benchmark result still means most of that deliberately difficult test was not passed perfectly, so even the stronger model needs a validation step.
A practical two-stage workflow uses Gemini 3.6 Flash for inexpensive bulk extraction or triage, then Fable 5 to reconcile conflicting numbers and write the final stakeholder narrative. Even with Fable, do not publish without a number ledger and a source-slide check.
A wrong figure in front of investors is expensive. Fable 5's lead on the closest professional-document benchmark supports it as the safer default for numerical fidelity.
You summarize dozens of decks a week for internal updates. Gemini 3.6 Flash's low cost and chart-reading evidence suit a fast, economical first pass.
Some decks matter more than others. Let Gemini triage the bulk of the deck library, then route the decision-critical ones to Fable 5 for the final numbers-checked summary.
A dashboard screenshot feeds a real decision. Require a source-slide reference for every material number from either model before the summary goes out.
This page compares the two models through their API in one neutral setup, not one model inside a presentation tool against the other inside a document viewer.
The parts that matter for a slide-deck summary are reading small labels and footnotes, extracting values from charts and tables, keeping a repeated metric consistent across slides, distinguishing actuals from forecasts, and turning the facts into readable prose. Official docs come first, then independent professional-document and chart-reasoning benchmarks with a clear method.
We left presentation-software and file-conversion features out of the spec table on purpose. Whether a screenshot comes from a slide viewer, an export tool or a browser extension belongs to the app around the model, not to the model itself. Judging those here would compare tools, not which model keeps the numbers straight.
The model facts that actually affect a slide-deck summary. Presentation and file-conversion tools are left out, since they belong to the app around the model.
Figures from Anthropic and Google documentation, checked September 1, 2026. Gemini's rate is promotional through December 31, 2026, after which Google's published rate rises.
The answer changes by dimension, not by brand. This is the main analysis: which model has the edge on each part of turning slide screenshots into a summary, and what backs it up.
Better-choice calls map to dimensions the sources actually evaluated. Visual-token figures are not directly comparable across vendors, since they use different image encoders and token accounting.
A useful test feels boring. Same ordered screenshots, same prompt, same output limit. Then judge what your team actually pays for: every material number kept straight, and a summary that reads without the deck.
Include a dense KPI dashboard, a financial deck with actual, target and forecast columns, a chart-heavy strategy deck with small labels, a deck where the same metric repeats, and a deliberately low-resolution set.
Use the same ordered screenshots and output limit, and require a reasoning level appropriate to each model. Do not edit the results before scoring.
Build a gold-standard ledger of every material number: value, sign, currency, unit, percentage versus percentage points, period, scenario and source slide.
Check exact numerical matches, missing or invented numbers, correct attribution to actual, forecast or target, and readability for someone who never saw the deck. Blind the reviewers for commercial work.
No public benchmark exactly measures ordered slide-deck screenshots to a standalone summary. Here is what each source helps judge, and how much weight it can carry.
GDP.pdf's documented failure patterns include misaligned tables, misread charts, skipped exclusions and amendments overriding earlier text, all close analogues to a slide summary that quotes the right-looking number from the wrong series or period.
The best prompt is not the same for both. Fable 5 benefits from a precise deliverable and an explicit ban on inferring unreadable values. Gemini benefits from splitting extraction from prose with structured output.
For Claude Fable 5, give it a precise deliverable, require a fact ledger before synthesis, and explicitly request brevity. High effort is the documented starting point, moving to medium only after testing numerical accuracy.
For Gemini 3.6 Flash, use high media resolution for dense slides, consider high thinking, and split extraction from prose using structured output so the narrative pass cannot silently change a number the extraction pass already recorded.
A Claude Fable 5 prompt: a ledger before the narrative
Review the slides in order. First extract every material number
with its unit, period, series, and slide number. Reconcile
repeated metrics before writing.
Then produce a 500-word stakeholder summary. Never infer an
unreadable value, write "unreadable on slide N" instead.
Lead with the business outcome and use complete sentences.A Gemini 3.6 Flash prompt: structured extraction first
For each slide, return JSON fields: slide, claim, value, unit,
period, series, qualifier, confidence. Copy numbers exactly, do
not calculate or round. Use null when unreadable.
After completing all slides, compare repeated metrics and write a
concise stakeholder summary using only the extracted records.Neither model is a safe unsupervised summarizer. The useful question is where each one adds risk, and what to change in the prompt or the workflow.
One question first. Is a wrong number materially worse than paying more for inference? Then follow the branch that matches your deck volume and audience.
A starting point, not a rule. Test on your own decks before you commit.
If a wrong number is materially worse than paying more for inference, start with Claude Fable 5 for extraction, reconciliation and final writing. Use high-quality lossless images and high effort for dense charts or footnotes, and require human verification of the number ledger before it reaches an executive or investor1, 4.
If cost or volume dominates, start with Gemini 3.6 Flash. Use high media resolution only on complex slides, use structured output for the extraction phase, and upgrade the final pass to high thinking3, 5.
If there are thousands of slides but only some are decision-critical, use Gemini for triage and Fable 5 for the flagged slides and the final summary. If the deployment has not yet been built, test Gemini 3.7 Flash alongside these two, since 3.6 is already previous-generation6.
Claude Fable 5 is the safer default for turning slide screenshots into a stakeholder-ready summary when keeping the actual numbers straight is the deciding requirement. Gemini 3.6 Flash is the better economic choice and has credible chart and long-context capabilities.
No public benchmark exactly measures ordered slide-deck screenshots against a standalone executive summary. GDP.pdf is the best available proxy, but it uses PDFs, and reported Gemini scores differ between evaluation harnesses. Image preprocessing can also alter results, and Gemini's introductory price expires on December 31, 2026. Playgram is not the right buy for everyone either: a solo analyst who only ever needs one model is better served by a single vendor subscription.
The safest final step is to test the shape of your own decks, not a generic prompt from the internet. A fair test needs the same setup for both models: the same screenshots, the same prompt and the same place to run them, so the result reflects the models and not the tool around them. In practice that is harder than it sounds, since most teams end up running one model in one app and the other in a different one, on two separate subscriptions, which tilts the comparison before the first summary comes back. The cleaner the setup, the more the difference you see is really Claude Fable 5 vs Gemini 3.6 Flash, and not just which one happened to be easier to reach that day.
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