Claude: Using images, audio, and video in practical workflows

Graziano Stefanelli
15 minutes ago
3 min read

Claude’s multimodal capabilities have expanded from basic text generation to structured support for images, audio, and limited video workflows. While the system is not yet a full video processor, its current features already enable developers, enterprises, and end users to embed media into conversations, workflows, and automated analysis pipelines.

Image analysis is supported with multiple formats and detailed extraction.

Claude 4 Opus and its preview variants can process JPG, PNG, WEBP, and TIFF images. Files up to 10–15 MB and resolutions up to 16–20 megapixels are accepted, depending on the model tier. Users can attach up to three images per prompt, which the model interprets as about 500 tokens of context each.

Image processing goes beyond captioning. Claude can return bounding-box data, color histograms, OCR outputs, and object tags when tool mode is activated. For enterprise use, these outputs are delivered in JSON format, allowing direct integration with content moderation, cataloging, or accessibility workflows.

Model	Image limit	Max resolution	Processing time	Advanced features
Claude 4 Opus	3 images	16 MP	5–9 seconds	OCR, bounding boxes
Claude 4 Heavy	3 images	20 MP	8–12 seconds	Depth maps, similarity hashing
Claude Sonnet 4	2 images	12 MP	3–6 seconds	Caption-only outputs

This makes the system viable for tasks ranging from e-commerce tagging and document digitization to image accessibility support.

Audio transcription is real-time with streaming options.

Claude handles WAV, MP3, and FLAC uploads, with a maximum of 10–15 minutes per file depending on the model. File size caps range from 25 MB to 40 MB. Transcription is tokenized at about 1 token per second of audio, meaning a 10-minute file consumes roughly 600 tokens.

The system delivers streaming transcripts in intervals of 1–2 seconds, which is particularly useful for meetings, customer service calls, and content creation. Advanced variants can generate speaker diarisation, distinguishing voices and labeling transcripts accordingly.

Tier	Duration limit	File size limit	Output features	Enterprise additions
Claude 4 Opus	10 minutes	25 MB	Full transcript, summary	Language ID auto-detect
Claude 4 Heavy (prev)	15 minutes	40 MB	Transcript + speakers	JSON timestamps, diarisation
Claude Sonnet 4	5 minutes	10 MB	Transcript only	—

These features provide structured support for podcasts, lectures, and legal transcripts, where both accuracy and metadata are critical.

Video support is indirect through audio and frame extraction.

Claude does not process video files directly, but users can employ work-arounds. By extracting key frames (e.g., one per second) and feeding them as a batch of images, Claude can analyze visual content. Alternatively, the audio track can be separated and transcribed, or a scene list can be provided as structured text for summarisation.

The Heavy preview accepts zipped archives of up to 50 frames, treating each as an individual image. Each frame counts toward the three-image limit per request.

Method	Purpose	How it works
Key-frame extraction	Visual content analysis	Use ffmpeg to generate stills; submit as images
Audio track processing	Dialogue transcription	Extract audio as WAV and submit for transcription
Scene text submission	Structural summary	Feed a shot list; Claude generates highlight reports

This approach allows creators and enterprises to use Claude for video summarisation, compliance checks, and media indexing even without native video ingestion.

Prompting strategies enhance multimodal use.

Effective use of media inputs requires structured prompts. For example:

Object tagging: “Identify all visible products in this image with category and color.”
Accessibility alt-text: “Produce a WCAG-compliant description under 120 characters.”
Meeting summaries: “Transcribe and summarise this audio, highlighting action points.”
Document Q&A: “Extract all text from this image and answer the user’s question based on it.”

Adding constraints such as JSON schemas or word limits reduces ambiguity and improves reliability for operational tasks.

Enterprise governance ensures compliance and control.

Claude includes no-train toggles, ensuring that uploaded media is not stored for model retraining. Data can be region-locked to EU, US, or APAC clusters for compliance with local regulations. Audit logs track source media type, size, latency, and hash values for security oversight.

Control	Function
Region lock	Restricts processing to specific jurisdictions
No-train toggle	Prevents media from contributing to retraining
Audit logs	Record usage metadata for compliance checks
Red-team filter	Blurs faces when content lacks rights flags

Such controls make Claude suitable for enterprise translation, healthcare transcription, and compliance-focused industries.

The roadmap expands multimodal use further.

In the coming months, Claude’s multimodal features are expected to expand with:

Polygon masks and spatial reasoning for image analysis.
Automated podcast segmentation with audio topic modeling.
Low-latency captioning for messaging platforms (<2 seconds).
Frame-based video summarisation with GIF preview outputs.

These updates show a direction toward deeper multimodal integration, balancing real-time performance, governance, and enterprise-scale use cases.

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