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Medical Visual LLM - 30B

John Snow Labs Inc · Software Development

Virtual MachinesNo attestation published

Certification per Microsoft Marketplace.

Provenance reach3 of 12 layers traced

Evidence tier Source Confirmed · 8 captures on record

User ratingNot rated0 reviews on the listing
Runs onVirtual MachinesVirtual machine
ProvenanceUnknown33% of the provenance layers this product can disclose
Evidence riskHighSign in to see the basis for this band.

What the publisher says

As described on Microsoft Marketplace.

This 30B parameter vision language foundation model seamlessly integrates advanced medical reasoning with powerful visual understanding. Designed specifically for the healthcare domain, it can interpret and analyze both textual and visual medical data, including clinical notes, lab reports, X rays, MRIs, CT scans, pathology slides, and anatomical diagrams. By combining domain-specific medical expertise with multimodal comprehension, the model enables deeper insights across diagnostic, research, and clinical workflows. Its dual modality architecture allows it to jointly process patient text records and visual imaging data, offering physicians a unified perspective for accurate, context aware decision making. It can summarize complex clinical documents, generate detailed yet concise medical reports, and answer domain specific questions with high factual precision while maintaining critical nuance and detail. Featuring a 32K token context window, the model supports extended medical reports, multi image cases, and long contextual reasoning in a single prompt. Optimized for RAG and integration with electronic health records and imaging systems, it delivers informed, evidence grounded responses that bridge the gap between visual diagnostics and textual analysis, advancing the future of intelligent medical assistance.

Benchmarking Results:

Show the rest of the publisher’s description (8 more lines)

Achieves 83.5% average across OpenMed benchmarks

Scores 85.66% on clinical knowledge assessment

Reaches 95% on medical genetics understanding

Performs at 93.75% for college biology concepts

Processes professional medicine with 89.34% accuracy

Handles medical MCQAs with 68.8% precision

Maintains 77.61% accuracy on MedQA 4-options test

Recommended Instance for this model is Standard_NC96ads_A100_v4

Agent build and provenance

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The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.

Compliance

Government
  • FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27

Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.

Sources

Marketplace listingmarketplace.microsoft.comSource
Privacy PolicyPrivacy PolicySource
License TermsLicense TermsSource

Publisher resources

5 links
Measuring the Benefits of Healthcare Specific Large Language Modelswww.nlpsummit.orgSource
Advance Industry Benchmarkswww.johnsnowlabs.comSource
Improving Radiology Workflows with Vision-Language Modelswww.johnsnowlabs.comSource
Code Samplegithub.comSource

Linked repositories

1 repo
JohnSnowLabs/spark-nlp-workshopgithub · Microsoft MarketplaceSource

Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.

Pricing
Unknown
Not stated
Delivery
Virtual machine
https://spark-nlp.slack.com/archives/C0651LEG2HH
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