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Interfaze vs Mistral OCR

Q: Does Mistral also offer document Q&A and audio models?

Yes. Mistral offers document Q&A through chat models and audio processing through Voxtral. The pipeline above compares one Mistral OCR request, not the whole Mistral platform. Interfaze accepts the document and recording together in one model request.

Q: How is Interfaze different from Mistral OCR?

Mistral OCR is a document-processing endpoint with layout-aware text and structured annotations. Interfaze uses a Chat Completions interface for document extraction and other tasks across documents, images and audio. Both support structured JSON and OCR metadata; the choice depends on your workload and integration.

Q: Do these examples prove Interfaze is always more accurate?

No. The examples show selected fields from three pages across our 39-page run and 20-page follow-up in October 2026. Both APIs received the same image, field schema and extraction instruction. We display the first successful responses, including correct answers from both providers. Ambiguous answer-key fields are excluded. These examples are not an overall accuracy score.

Q: Which Mistral model did you test?

Our API examples used Mistral OCR 4.1: mistral-ocr-latest, which has pointed to mistral-ocr-4-1 since July 16, 2026, with document annotations, block extraction and block confidence. The benchmark table uses the same 4.1 runs on 39 documents. The olmOCR charts use the Mistral OCR 4.1 scores on our olmOCR leaderboard.

Q: Does Mistral OCR also provide boxes and confidence?

Yes. Its OCR API returns block-level bounding boxes and configurable confidence scores. In the examples above, each Interfaze box is the set of OCR word boxes that spell the value, and each Mistral box is the returned block that contains it. Where Mistral returned a whole table or drawing as one block, the field has no box of its own. Green marks a correct value, red a wrong or empty one.

Q: What changes when I migrate?

Send the document and your schema through Interfaze's Chat Completions interface, then read the JSON from the completion instead of Mistral's document annotation. Preserve field names, check empty and missing values, and validate the result with your existing schema. Page Markdown and block consumers need their own migration checks.

Q: Can I self-host Interfaze?

The separate interfaze-1.1-lite model has open weights and runs on a supported 80 GB GPU. The examples on this page used the hosted interfaze-1 model; they are not a benchmark of Lite.

Q: Which API will cost less for my documents?

Interfaze uses token-based pricing; Mistral OCR uses page-based pricing with a separate annotation rate. Compare the total cost of extracting the same fields, including retries and review. These examples do not establish a cost or latency advantage.

Q: Where can I check the documents and feature sources?

Original scans and product documentation are linked below. Feature documentation checked October 28, 2026.

More fields right on hard scans, in one API call.

One API call reads documents, images and audio and returns structured JSON. Every response also includes the OCR underneath, with bounding boxes and a confidence score for each word.

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Why teams choose Interfaze over Mistral OCR

Word boxes you can check, more fields right on hard scans, documents and audio in one call, and the SDK you already use.

INVOICE

NO.

INV-20418

DATE

2026-09-03

1,200.00

3,620.50

TOTAL

$4,820.50

total_due

0.98

Data you can verify

Check extracted text with word boxes and confidence scores. Flag uncertain reads for review.

Documents and audio together

Send a document and a recording in one request. Mistral OCR takes one document per request, and audio goes to a separate model.

LINE ITEMS

ITEM

QTY

AMOUNT

Valve, 2in

1,104.00

Gasket kit

386.40

Labour, site

720.00

TOTAL

2,210.40

Net 30. 1.5% monthly on overdue balances. Prices exclude VAT at the prevailing rate.

Better on hard-to-read scans

On our 39-document test, interfaze-1 read 97.5% of fields right against 90.1% for Mistral OCR 4.1, with the widest gap on rotated and faint text.

OpenAI SDK

import OpenAI from "openai";

new OpenAI({

baseURL:

"https://api.interfaze.ai/v1",

apiKey: INTERFAZE_API_KEY

});

Stream response

Keep your existing client

Extract documents through OpenAI-compatible Chat Completions. Use your current SDK and stream the result.

Try for free

Interfaze vs Mistral OCR on the same document

Same pages and same fields, sent to both APIs. Three selected pages where interfaze-1 got more fields right. Pick one to see where each API placed its fields, or the JSON it returned.

Newspaper op-ed

LinkedIn printout

Tiny-print table

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

Interfazeinterfaze-1

structured JSON

22/22 field checks passed

✓

headline

Climate of Fear

1.00

✓

byline

By Richard Lindzen

0.99

✓

publication_name

The Wall Street Journal

0.99

✓

section_label

OPINION

0.99

✓

issue_date

WEDNESDAY, APRIL 12, 2006

1.00

✓

author_affiliation

Mr. Lindzen is Alfred P. Sloan Professor of Atmospheric Science at MIT.

0.97

✓

climate_research_spending_today

$1.7 billion

0.99

✓

co2_increase_percent

30%

0.96

✓

warmest_year_claimed

1998

0.99

✓

hearings_year

1992

0.99

✓

named_effect

Iris Effect

0.93

✓

photo_credit

Images.com/Corbis

0.59

✓

tv_host

Ted Koppel

0.99

✓

libel_author

Ross Gelbspan

0.99

✓

dismissed_director

Henk Tennekes

0.99

✓

wmo_director

Aksel Winn-Nielsen

Read correctly.

✓

ipcc_first_head

Bert Bolin

0.97

✓

debate_year

1991

0.99

✓

ipcc_claim_source

Sir John Houghton

0.99

✓

texas_rep

Joe Barton

0.99

✓

paleoclimatologist

Michael Mann

0.99

✓

climate_plan_year

2003

0.99

Mistralmistral-ocr-latest

structured JSON

19/22 field checks passed

✗

warmest_year_claimed

1988 · page says 1998

No box returned. The box marks where the value is on the page.

✗

libel_author

Ross Geibspan · page says Ross Gelbspan

No box returned. The box marks where the value is on the page.

○

photo_credit

not returned · page says Images.com/Corbis

Not returned. The box marks where the value is on the page.

✓

headline

Climate of Fear

0.99

✓

byline

By Richard Lindzen

1.00

✓

publication_name

The Wall Street Journal

1.00

✓

section_label

OPINION

1.00

✓

issue_date

WEDNESDAY, APRIL 12, 2006

1.00

✓

author_affiliation

Mr. Lindzen is Alfred P. Sloan Professor of Atmospheric Science at MIT.

1.00

✓

climate_research_spending_today

$1.7 billion

Read correctly.

✓

co2_increase_percent

about 30%

Read correctly.

✓

hearings_year

1992

Read correctly.

✓

named_effect

"Iris Effect"

Read correctly.

✓

tv_host

Ted Koppel

Read correctly.

✓

dismissed_director

Henk Tennekes

Read correctly.

✓

wmo_director

Aksel Winn-Nielsen

Read correctly.

✓

ipcc_first_head

Bert Bolin

Read correctly.

✓

debate_year

1991

Read correctly.

✓

ipcc_claim_source

Sir John Houghton

Read correctly.

✓

texas_rep

Joe Barton

Read correctly.

✓

paleoclimatologist

Michael Mann

Read correctly.

✓

climate_plan_year

2003

Read correctly.

See detailed breakdown

One API call instead of a pipeline

Mistral OCR reads one document per request, and audio goes to a separate model. With Interfaze you send them together.

Audio docs

Claims intake

Form + photo

Claims intake

integration steps

Interfaze

1 call · 1 API

done first

Mistral OCR

3/3 steps · 2 APIs

done

With Interfaze

With Mistral OCR

Call + files

Transcribe

Voxtral

OCR

Mistral OCR

Your code

you

Interfaze

transcribeocrmerge

One request

Claim JSON

Interfaze

1 call · 1 API

first

Mistral OCR

3/3 steps · 2 APIs

done

Call + files

Transcribe

Voxtral

OCR

Mistral OCR

Your code

you

Interfaze

transcribeocrmerge

Claim JSON

Interfaze vs Mistral OCR accuracy benchmarks

Same 39 documents, same field list, first call to each API. Share of fields read correctly, with disagreements checked by hand against the page.

Accuracy by content type

higher is better

Content

Interfaze

Mistral

All fields

every field on all 39 documents · 433 fields

97.5%

90.1%

Rotated, upside-down & faint text

upside-down pages, rotated margin numbers, vertical and faint text · 22 fields

86.4%

59.1%

Fine print

stamps, footers, Bates numbers, small type · 72 fields

95.8%

83.3%

Tables

cells in dense and scanned tables · 74 fields

97.3%

90.5%

Numbers

amounts, IDs, dates and counts · 97 fields

99.0%

93.8%

Handwriting

handwritten notes, stamps and envelopes · 34 fields

88.2%

85.3%

Body text

names, titles, labels and running text · 120 fields

99.2%

92.5%

Method ->

Interfaze vs Mistral OCR on olmOCR-bench

Scores from the public olmOCR benchmark. The overall ranking first, then the three tasks with the biggest gap.

Full breakdown

Interfaze vs Mistral OCR, feature by feature

Checked against both companies' docs. Mistral entries refer to its OCR service; open weights refer to Interfaze Lite.

Interfaze

Mistral OCR

Word-level bounding boxes

Locate individual words and lines with pixel bounds in OCR precontext.

Word-level bounding boxes

Its docs list paragraph-level boxes, not individual word boxes. Word confidence is supported.

Streaming output

Stream text and structured output as it is generated.

Streaming output

The documented OCR endpoint returns a complete response, without streaming.

OpenAI-compatible extraction

Use Chat Completions with your existing OpenAI or Vercel AI SDK client.

OpenAI-compatible extraction

OCR uses a separate endpoint and request format, outside Chat Completions.

Open weights

The separate interfaze-1.1-lite model runs on one 80 GB GPU.

Open weights

No public weights listed for Mistral OCR; other Mistral models have open weights.

Audio and video input

One interface for documents, images and audio; interfaze-1 also accepts video.

Audio and video input

The OCR endpoint accepts documents and images. Audio uses separate Mistral models.

Structured JSON output

Your JSON schema through Chat Completions, alongside OCR precontext.

Structured JSON output

Your JSON schema through document annotations on the OCR endpoint.

OCR confidence scores

Word and line confidence scores in OCR precontext.

OCR confidence scores

Configurable word, block or page confidence scores.

How to migrate from Mistral OCR to Interfaze

The same document and schema, side by side. Keep your validation, switch the API call, or let your coding agent help.

SDK guide

Interfaze

OpenAI SDK

Vercel AI SDK

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);

Mistral OCR

import { Mistral } from "@mistralai/mistralai";

const client = new Mistral({
  apiKey: process.env.MISTRAL_API_KEY,
});

const res = await client.ocr.process({
  model: "mistral-ocr-latest",
  document: { type: "document_url", documentUrl: pdfUrl },
  documentAnnotationFormat: {
    type: "json_schema",
    jsonSchema: {
      name: "invoice",
      schemaDefinition: INVOICE_SCHEMA,
      strict: true,
    },
  },
  documentAnnotationPrompt: "Extract the fields",
});
if (!res.documentAnnotation) throw new Error("No annotation");
const invoice = JSON.parse(res.documentAnnotation);

Interfaze vs Mistral OCR: common questions

Accuracy, integration and what to check before switching.

Does Mistral also offer document Q&A and audio models?

How is Interfaze different from Mistral OCR?

Do these examples prove Interfaze is always more accurate?

Which Mistral model did you test?

Does Mistral OCR also provide boxes and confidence?

What changes when I migrate?

Can I self-host Interfaze?

Which API will cost less for my documents?

Where can I check the documents and feature sources?

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 Talk to a founder

Interfaze vs Mistral OCR

Why teams choose Interfaze over Mistral OCR

Data you can verify

Documents and audio together

Better on hard-to-read scans

Keep your existing client

Interfaze vs Mistral OCR on the same document

One API call instead of a pipeline

Interfaze vs Mistral OCR accuracy benchmarks

Interfaze vs Mistral OCR on olmOCR-bench

Interfaze vs Mistral OCR, feature by feature

How to migrate from Mistral OCR to Interfaze

Interfaze vs Mistral OCR: common questions

Send us your hardest PDF.If we can't beat your current provider,we'll give you $3,000 in credits.

Send us your hardest PDF.
If we can't beat your current provider,
we'll give you $3,000 in credits.