# Interfaze vs Gemini URL: https://interfaze.ai/compare/gemini [ Interfaze ![logo](https://interfaze.ai/interfaze_icon.svg) ](https://interfaze.ai/)[ we're hiring ](https://interfaze.ai/careers) models[ pricing ](https://interfaze.ai/pricing)[ help ](https://interfaze.ai/help)[ docs ](https://interfaze.ai/docs)[ blog ](https://interfaze.ai/blog)[ sign in ](https://interfaze.ai/dashboard/playground) Backed by ![Y Combinator](https://interfaze.ai/yc_logo.svg) Combinator Every value, with where it is and how sure. One API call returns your JSON fields plus the OCR underneath, with a bounding box and a confidence score for every word. [Build now](https://interfaze.ai/dashboard/playground)Setup with agents Trusted by builders at ![NVIDIA](https://interfaze.ai/companies/nvidia.webp) ![IBM](https://interfaze.ai/companies/ibm.webp) ![Vercel](https://interfaze.ai/companies/vercel.webp) ![Supabase](https://interfaze.ai/companies/supabase.webp) ![Notion](https://interfaze.ai/companies/notion.webp) ![Zapier](https://interfaze.ai/companies/zapier.webp) ![Robinhood](https://interfaze.ai/companies/robinhood.webp) ![Airwallex](https://interfaze.ai/companies/airwallex.webp) ![Langflow](https://interfaze.ai/companies/langflow.webp) ![Smithery](https://interfaze.ai/companies/smithery.webp) ![Rho](https://interfaze.ai/companies/rho.webp) ![Pocket](https://interfaze.ai/companies/pocket.webp) ![101 GenAI](https://interfaze.ai/companies/101genai.webp) ![Aegis](https://interfaze.ai/companies/aegis-logo-text.webp) ![RMH](https://interfaze.ai/companies/rmh-logo.webp) ![INTH](https://interfaze.ai/companies/inth.webp) ![Andco](https://interfaze.ai/companies/andco.webp) ## Why teams choose Interfaze over Gemini Values you can check on the page, OCR and extraction in one call, and a lead on the public olmOCR benchmark. [ INVOICE NO. INV-20418 DATE 2026-09-03 1,200.00 3,620.50 TOTAL $4,820.50 total\_due 0.98 01 ### Know where every value is Every response comes with bounding boxes and a confidence score for each word, so you can check any value against the page. Gemini has no OCR layer or confidence scores. ](https://interfaze.ai/docs/precontext) [ .pdf .jpg .mp3 URL ![](https://interfaze.ai/interfaze_icon.svg) 02 ### OCR and extraction in one call One request returns your JSON fields with the OCR underneath. No second OCR service and no code to match values back to the page. ](https://interfaze.ai/docs/vision/ocr) [ LINE ITEMS ITEM QTY AMOUNT Valve, 2in 12 1,104.00 Gasket kit 40 386.40 Labour, site 6h 720.00 TOTAL 2,210.40 Net 30. 1.5% monthly on overdue balances. Prices exclude VAT at the prevailing rate. 03 ### Ahead on olmOCR On the public olmOCR benchmark, interfaze-1 scores 85.7% against 82.3% for Gemini 3.8 Flash, with the widest leads on old scans and long tiny text. ](https://interfaze.ai/compare/gemini#leaderboard) [Try for free](https://interfaze.ai/dashboard/playground) ## Interfaze vs Gemini on the same document Same pages and same fields, sent to both APIs. Three selected pages, two of them upside down, where interfaze-1 read every field right and Gemini missed at least one. Gemini was asked for values only, so its pane has no boxes. Pick one to see the boxes, or the JSON each API returned. Handwritten plan Upside-down fax Upside-down slide Boxes on the page Returned JSON correct value wrong value, boxed where the API read it no box from the API: boxed where the value is ○ not returned ![](https://interfaze.ai/interfaze_icon.svg)Interfazeinterfaze-1 structured JSON ![Handwritten notes](https://r2public.jigsawstack.com/interfaze/compare/proof/fmhx0223_p1.jpg) 15/15 field checks passed Show all fields ✓ test\_market\_date Jan. 1967 0.96 ✓ slogan "Me and My Winstons" 0.94 ✓ mediums TV; Print; Merchandising; Sale- Promotions 0.82 ✓ no\_plans\_years 1971- 1973 Read correctly. ✓ campaign\_1973 "Theres a lot of Good" Read correctly. ✓ test\_markets 4 mini mkts and 1 full test market Read correctly. ✓ bates\_number 53727 7036 0.99 ✓ first\_heading Winston 1969 0.97 ✓ second\_heading Winston 1970 0.91 ✓ fourth\_heading Winston - 1974 0.93 ✓ item\_3\_1969 3\. Combined brand group 0.98 ✓ research\_item\_1 \- awareness Read correctly. ✓ national\_month April 0.95 ✓ volume\_item 1\. Establish volume momentum 0.90 ✓ last\_bullet \- Camp Comm Study 0.90 ![](https://interfaze.ai/compare/gemini/gemini_icon.svg)Geminigemini-3.8-flash structured JSON ![Handwritten notes](https://r2public.jigsawstack.com/interfaze/compare/proof/fmhx0223_p1.jpg) 14/15 field checks passed Show all fields ✗ mediums TV; Print; Merchandising; Sales Promotion · page says TV; Print; Merchandising; Sale Promotions No box returned. The box marks where the value is on the page. ✓ test\_market\_date Jan. 1967 Read correctly. ✓ slogan "Me and My Winstons" Read correctly. ✓ no\_plans\_years 1971- 1973 Read correctly. ✓ campaign\_1973 "Theres a lot of Good" Read correctly. ✓ test\_markets (4 mini mkts and 1 full test market) Read correctly. ✓ bates\_number 53727 7036 Read correctly. ✓ first\_heading Winston 1969 Read correctly. ✓ second\_heading Winston 1970 Read correctly. ✓ fourth\_heading Winston - 1974 Read correctly. ✓ item\_3\_1969 3\. Combined brand group Read correctly. ✓ research\_item\_1 \- awareness Read correctly. ✓ national\_month April Read correctly. ✓ volume\_item 1\. Establish volume momentum Read correctly. ✓ last\_bullet \- Camp Comm Study Read correctly. [See detailed breakdown](https://interfaze.ai/compare/gemini/documents) ## One call instead of extract, then OCR Gemini can estimate a box per field if you ask. Word boxes with confidence scores take a second OCR service and matching code; Interfaze returns both. [OCR docs](https://interfaze.ai/docs/vision/ocr) Fields with locations integration steps Interfaze 1 call · 1 API done first Gemini 3/3 steps · 2 APIs done With Interfaze With Gemini Scanned form Extract Gemini OCR OCR API Your code you ![](https://interfaze.ai/interfaze_icon.svg) Interfaze ocrextractboxesconfidence One request Fields + boxes Interfaze 1 call · 1 API first Gemini 3/3 steps · 2 APIs done Scanned form Extract Gemini OCR OCR API Your code you ![](https://interfaze.ai/interfaze_icon.svg) Interfaze ocrextractboxesconfidence Fields + boxes ## Interfaze vs Gemini on olmOCR-bench Scores from the public olmOCR benchmark. The overall ranking first, then the three tasks with the biggest gap. [Full breakdown](https://interfaze.ai/leaderboards/olmocr) ## Interfaze vs Gemini, feature by feature Checked against both companies' docs. ![](https://interfaze.ai/interfaze_icon.svg) Interfaze ![](https://interfaze.ai/compare/gemini/gemini_icon.svg) Gemini Bounding boxes with confidence scores Every word and line with exact pixel bounds and a 0–1 confidence, in every response, no prompting needed Bounding boxes with confidence scores No OCR layer and no confidence scores; boxes only if you prompt for them, as model estimates on a 0–1000 grid olmOCR and OCRBench v2 scores 1st on olmOCR (85.7%) and OCRBench v2 (70.7%) olmOCR and OCRBench v2 scores Behind on both: 82.3% on olmOCR (Gemini 3.8 Flash), 55.8% on OCRBench v2 (Gemini 3 Flash) Open weights interfaze-1.1-lite runs on your own 80 GB GPU Open weights Closed models, hosted by Google only; no weights to download Zero data retention Nothing kept after the request, on every plan, with one header Zero data retention Prompts and outputs kept 55 days for abuse monitoring unless you set up Google's zero-retention configuration Structured JSON output Your JSON schema in the same call as the OCR (OpenAI json\_schema, Zod, Pydantic) Structured JSON output Your JSON schema through responseJsonSchema Multimodal input Documents, images, audio and video Multimodal input Documents, images, audio and video Standard SDKs OpenAI Chat Completions compatible: OpenAI SDK, Vercel AI SDK, LangChain Standard SDKs Google Gen AI SDKs, plus an OpenAI-compatible endpoint ## How to migrate from Gemini to Interfaze The same extraction in Interfaze and Gemini, side by side. Your existing schema works as is. Or let your coding agent make the switch. [SDK guide](https://interfaze.ai/docs/integrations/interfaze-sdk) TypeScript TypeScript Python **OpenAI SDK · typescript** ```typescript import OpenAI from "openai"; const client = new OpenAI({ baseURL: "https://api.interfaze.ai/v1", apiKey: process.env.INTERFAZE_API_KEY, }); const res = await client.chat.completions.create({ model: "interfaze-1", response_format: { type: "json_schema", json_schema: { name: "invoice", schema: INVOICE_SCHEMA }, }, messages: [{ role: "user", content: [ { type: "text", text: "Extract the fields" }, { type: "file", file: { filename: "invoice.pdf", file_data: pdfUrl } }, ], }], }); const invoice = JSON.parse(res.choices[0].message.content); ``` **Vercel AI SDK · typescript** ```typescript import { generateText, jsonSchema, Output } from "ai"; import { interfaze } from "@interfaze-ai/ai-sdk"; const { output } = await generateText({ model: interfaze("interfaze-1"), output: Output.object({ schema: jsonSchema(INVOICE_SCHEMA), }), messages: [{ role: "user", content: [ { type: "text", text: "Extract the fields" }, { type: "file", data: pdfUrl, mediaType: "application/pdf" }, ], }], }); ``` **OpenAI SDK · python** ```python import json, os from openai import OpenAI client = OpenAI( base_url="https://api.interfaze.ai/v1", api_key=os.environ["INTERFAZE_API_KEY"], ) res = client.chat.completions.create( model="interfaze-1", response_format={ "type": "json_schema", "json_schema": {"name": "invoice", "schema": INVOICE_SCHEMA}, }, messages=[{ "role": "user", "content": [ {"type": "text", "text": "Extract the fields"}, {"type": "file", "file": {"filename": "invoice.pdf", "file_data": pdf_url}}, ], }], ) invoice = json.loads(res.choices[0].message.content) ``` **Interfaze SDK · python** ```python import json from interfaze import Interfaze, inputs, response_format interfaze = Interfaze() # reads INTERFAZE_API_KEY res = interfaze.chat.completions.create( messages=[{ "role": "user", "content": [ {"type": "text", "text": "Extract the fields"}, inputs.file(pdf_url, filename="invoice.pdf"), ], }], response_format=response_format(INVOICE_SCHEMA, "invoice"), ) invoice = json.loads(res.choices[0].message.content) ``` Migrate with agents ## Interfaze vs Gemini: common questions What people usually ask before switching from Gemini. Interfaze vs Gemini: what's the difference? Gemini is a general-purpose model: with a JSON schema it returns the values you ask for. Interfaze is built for deterministic extraction: the same call returns your JSON plus the OCR underneath, with a bounding box and a confidence score for every word, so each value can be checked against the page. Is Interfaze more accurate than Gemini? On the public olmOCR benchmark, interfaze-1 scores 85.7% and Gemini 3.8 Flash 82.3%. On our own 59-document field test the two read values at a similar rate: 532 of 541 fields for interfaze-1, 536 for Gemini 3.8 Flash. The difference is the OCR layer: word boxes and confidence scores in every response. How much code do I need to change? A few lines per call. Point the OpenAI SDK or Vercel AI SDK at Interfaze, send the PDF as a file and pass the same JSON schema you give Gemini. If you added a separate OCR step for locations, you can delete it. Can I self-host? Yes. interfaze-1.1-lite has open weights and runs on a single 80 GB GPU like an H100. What about security and data retention? Turn on zero data retention for any request with one header, on every plan. SOC 2 and HIPAA agreements are available on request. ## Send us your hardest PDF. If we can't beat your current provider, we'll give you $3,000 in credits. Start for free. No credit card required. [Build now](https://interfaze.ai/dashboard/playground)[Talk to a founder](https://interfaze.ai/sales)