Gemini 3.5 Flash vs Unstructured
The cheapest raw model against a parsing layer, five points apart. Gemini 3.5 Flash fills in fields and is excellent on a single page. Unstructured returns elements for something else to fill fields from, and with that step applied it came last. Both collapse on long documents. Gemini is the better extractor. Unstructured is the better ingestion layer, with cleaner data terms.
Gemini here is Google's fast general model with a file and a field list. Unstructured splits documents up for retrieval systems. To rank it we ran the same field-filling step over its output that every system got. They came sixth and eighth, and they share more than most pairs on this site.
Both were good on clean single pages, with Gemini second only to DocuPipe there, and both were terrible on long registers, Gemini with the lowest long-document average in the test and runs that failed outright, Unstructured with row structure lost in the parse. Gemini led clearly on single-page documents, photographed pages, multi-page statements, and non-English documents generally. Unstructured was slightly ahead on Hebrew and Arabic text direction and on long registers, in the sense of losing less. Chinese and Japanese scans went clearly to Gemini.
On resilience Gemini's failure is predictable and total on length. Unstructured's is a matter of category. It can't finish the job alone, and on hard layouts the structure the next step needs is gone before it runs.
On price both are as cheap as it gets. Gemini is well under a cent per page with a free tier for development. Unstructured is a cent and a half a page after 10,000 free pages, no card, for parsing only, with a model step, possibly Gemini itself, on top.
On product Unstructured is the more complete for its own purpose: a hosted platform with connectors, partitioning, chunking, and enrichment, a Python SDK, REST API, MCP server, and the open-source library, zero data retention on every plan, and SOC 2 Type 2, HIPAA, and GDPR stated. Gemini offers a good general API with the largest PDF page limit of the raw models, a Files API and structured output, and no document product, with a data policy that differs between its free and paid tiers.
For extracting fields from short documents, Gemini. For ingesting ordinary English documents into a search index with clean compliance terms, Unstructured, with a model behind it. For long documents, neither.
Structured extraction from single-page documents and scans, with your own pipeline, where cost decides.
Search and retrieval pipelines over ordinary English documents where you want cheap parsing, connectors, and zero-retention terms on every plan.
How it scores, area by area
The accuracy score comes from the benchmark. Every other score is ours, with the reason written next to it. We use the same weights on every review and comparison.
| Area | Gemini 3.5 Flash | Unstructured |
|---|---|---|
| Accuracy35% of total | 7.3Ranked 6th of 8 systems on the benchmark. | 6.8Ranked 8th of 8 systems on the benchmark. |
| Resilience15% of total | 3.0Several runs failed outright and the long-document average was the lowest in the test; excellent one day and empty the next depending on page count. | 4.0Needs your own extraction step to produce fields at all, and on long or tabular documents the structure is lost before that step runs. |
| Price15% of total | 10.0$1.50 and $9 per million tokens plus a free tier; well under a cent per page. | 8.0$0.015 per page for parsing, but you add your own model cost to get structured fields. |
| Getting started10% of total | 4.0No document product, though the free tier makes trying it trivial. | 6.0Hosted platform and open-source library, 10,000 free pages, no card; not an extraction product. |
| API and integration10% of total | 5.0Strong general SDKs, the largest PDF page limit of the direct models, a Files API and structured output; no document jobs or webhooks. | 6.0Python SDK, MCP server and a full workflow API with connectors, but built around partitioning rather than schema extraction, and webhooks are not marketed. |
| Data control7.5% of total | 4.0Platform policy only, and it differs between the free and paid tiers. | 8.0Zero data retention stated on every plan. |
| Compliance7.5% of total | 6.0Platform certifications apply to the API; your pipeline is your responsibility. | 8.0SOC 2 Type 2, HIPAA and GDPR; dedicated instance and VPC on Business. |
| Overallweighted | 6.2weighted score out of 10 | 6.6weighted score out of 10 |
How each area is scored
- Accuracy (35%). The benchmark result, on a 0 to 10 scale.
- Resilience (15%). Does it just work? Fewer modes to choose, no tuning to reach the ranked result, no runs that fail outright, and no documents that come back quietly empty. Informed by the benchmark, judged by us.
- Price (15%). Published cost per page for parse plus extraction, cheapest scoring highest. Unpublished pricing is marked down.
- Getting started (10%). How far you get without a sales call: a dashboard, a free tier with no card, help authoring schemas, a test environment.
- API and integration (10%). Webhooks and which tier they are on, SDKs, no-code connectors, whether the API is built around document jobs at all.
- Data control (7.5%). Deletion controls, scheduled retention, zero-retention availability and on which tier, choice of region.
- Compliance (7.5%). Certifications stated on public pages: SOC 2, ISO 27001, HIPAA with a BAA, GDPR, private deployment options.
By document type
Average accuracy on each group of benchmark documents, both systems on the same files. Every document and score is on the evidence page.
| Document type | Gemini 3.5 Flash | Unstructured |
|---|---|---|
| Scans and photosimages, not PDFs · 7 documents | 95.5% Strong | 86.5% Good |
| Short forms, invoices, receiptsone page · 30 documents | 94.1% Good | 80.2% Good |
| Statements, filings, reports2 to 5 pages · 21 documents | 87.5% Good | 84.9% Good |
| Non-English documents12 languages · 25 documents | 68.9% Mixed | 62.2% Mixed |
| Long registers, catalogs, directories6 pages and up · 21 documents | 28.3% Weak | 32.5% Weak |
Price, product, and policies
Full reviews: Gemini 3.5 Flash, Unstructured.
| Gemini 3.5 Flash | Unstructured | |
|---|---|---|
| Pricing model | Per token through the Gemini API. No document-specific product or plan. | Per page, parse only. You supply the extraction step yourself. |
| Entry price | $1.50 per million input tokens, $9 per million output tokens on the paid tier. | 10,000 free pages, no card. Then $0.015 per page pay-as-you-go. Business plan on request. |
| Cost per page | Depends on page size and output length; typically well under a cent to a couple of cents per page, the cheapest of the direct models. | $0.015 per page for parsing. Add the cost of whatever model you run on the output to get structured fields. |
| Free tier | Yes. A rate-limited free tier for development. | Yes. 10,000 pages, no credit card. |
| Pay as you go | Yes. Pure usage billing. | Yes. |
| Dashboard | No document product. AI Studio for trying prompts; upload, review and results tooling is yours to build. | Hosted platform for building workflows from source connectors (files, storage, databases) through partitioning and chunking to destination connectors, plus a widely used open-source library. |
| Webhooks | None for document jobs. You run the pipeline. | Workflow and job notifications through the API; not marketed as webhooks on the pricing page. |
| API and SDKs | Official SDKs in Python, JavaScript, Go and others. PDF input up to 1,000 pages or 50 MB, a Files API with 48-hour storage, structured output. | Python SDK, REST endpoints, an MCP server, and workflow and job management APIs. |
| Data retention | Governed by Google's API data policies, which differ between the free and paid tiers. Nothing document-specific. | Zero data retention stated across all plans. |
| Compliance | Google's platform certifications apply to the API; your pipeline around it is your responsibility. | SOC 2 Type 2, HIPAA, GDPR. Dedicated instance and VPC options on Business. |
We checked these against the vendors' own pricing and documentation pages on 2026-09-11. Sources: Gemini 3.5 Flash: ai.google.dev; Unstructured: unstructured.io, docs.unstructured.io. Prices change, so confirm before you budget.
Frequently asked
Is Gemini better than Unstructured for extraction?
Yes, 72.98% to 67.67% in our benchmark. Unstructured is a parsing layer rather than an extraction product. With the same field-filling step applied it held up on clean English text and little else. Both collapse on long documents.
Can I use Unstructured with Gemini?
That's a common pattern. Unstructured parses and chunks, and a model fills the fields. Our benchmark scored Unstructured's parse with a fixed extraction step applied, which is what that pattern measures.
Scores are macro-average field accuracy from the DocuBench 0.2.0, 72-document run. Every document, answer key, and raw extraction is open in the explorer; the scoring rules are on the methodology page, and the replication kit re-runs the scorer. A document a system could not process scores zero rather than being dropped.