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PulseReporter > Blog > Tech > New imaginative and prescient mannequin from Cohere runs on two GPUs, beats top-tier VLMs on visible duties
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New imaginative and prescient mannequin from Cohere runs on two GPUs, beats top-tier VLMs on visible duties

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Last updated: August 1, 2025 11:24 pm
Pulse Reporter 16 hours ago
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New imaginative and prescient mannequin from Cohere runs on two GPUs, beats top-tier VLMs on visible duties
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The rise in Deep Analysis options and different AI-powered evaluation has given rise to extra fashions and companies seeking to simplify that course of and browse extra of the paperwork companies truly use. 

Canadian AI firm Cohere is banking on its fashions, together with a newly launched visible mannequin, to make the case that Deep Analysis options must also be optimized for enterprise use circumstances. 

The corporate has launched Command A Imaginative and prescient, a visible mannequin particularly focusing on enterprise use circumstances, constructed on the again of its Command A mannequin. The 112 billion parameter mannequin can “unlock worthwhile insights from visible knowledge, and make extremely correct, data-driven choices via doc optical character recognition (OCR) and picture evaluation,” the corporate says.

“Whether or not it’s decoding product manuals with complicated diagrams or analyzing pictures of real-world scenes for danger detection, Command A Imaginative and prescient excels at tackling essentially the most demanding enterprise imaginative and prescient challenges,” the corporate stated in a weblog put up. 


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This implies Command A Imaginative and prescient can learn and analyze the most typical sorts of photographs enterprises want: graphs, charts, diagrams, scanned paperwork and PDFs. 

? @cohere simply dropped Command A Imaginative and prescient on @huggingface ?

Designed for enterprise multimodal use circumstances: decoding product manuals, analyzing images, asking about charts… ❓??

A 112B dense vision-language mannequin with SOTA efficiency – take a look at the benchmark metrics in… pic.twitter.com/ORMfM5f8cF

— Jeff Boudier ? (@jeffboudier) July 31, 2025

Because it’s constructed on Command A’s structure, Command A Imaginative and prescient requires two or fewer GPUs, similar to the textual content mannequin. The imaginative and prescient mannequin additionally retains the textual content capabilities of Command A to learn phrases on photographs and understands at the very least 23 languages. Cohere stated that, in contrast to different fashions, Command A Imaginative and prescient reduces the whole value of possession for enterprises and is absolutely optimized for retrieval use circumstances for companies. 

How Cohere is architecting Command A

Cohere stated it adopted a Llava structure to construct its Command A fashions, together with the visible mannequin. This structure turns visible options into smooth imaginative and prescient tokens, which might be divided into completely different tiles. 

These tiles are handed into the Command A textual content tower, “a dense, 111B parameters textual LLM,” the corporate stated. “On this method, a single picture consumes as much as 3,328 tokens.”

Cohere stated it educated the visible mannequin in three phases: vision-language alignment, supervised fine-tuning (SFT) and post-training reinforcement studying with human suggestions (RLHF).

“This method permits the mapping of picture encoder options to the language mannequin embedding house,” the corporate stated. “In distinction, in the course of the SFT stage, we concurrently educated the imaginative and prescient encoder, the imaginative and prescient adapter and the language mannequin on a various set of instruction-following multimodal duties.”

Visualizing enterprise AI 

Benchmark exams confirmed Command A Imaginative and prescient outperforming different fashions with comparable visible capabilities. 

Cohere pitted Command A Imaginative and prescient towards OpenAI’s GPT 4.1, Meta’s Llama 4 Maverick, Mistral’s Pixtral Giant and Mistral Medium 3 in 9 benchmark exams. The corporate didn’t point out if it examined the mannequin towards Mistral’s OCR-focused API, Mistral OCR. 

It permits brokers to securely see inside your group’s visible knowledge, unlocking the automation of tedious duties involving slides, diagrams, PDFs, and images. pic.twitter.com/iHZnUWekrk

— cohere (@cohere) July 31, 2025

Command A Imaginative and prescient outscored the opposite fashions in exams resembling ChartQA, OCRBench, AI2D and TextVQA. General, Command A Imaginative and prescient had a mean rating of 83.1% in comparison with GPT 4.1’s 78.6%, Llama 4 Maverick’s 80.5% and the 78.3% from Mistral Medium 3. 

Most massive language fashions (LLMs) nowadays are multimodal, that means they’ll generate or perceive visible media like images or movies. Nevertheless, enterprises usually use extra graphical paperwork resembling charts and PDFs, so extracting data from these unstructured knowledge sources typically proves troublesome. 

With Deep Analysis on the rise, the significance of bringing in fashions able to studying, analyzing and even downloading unstructured knowledge has grown.

Cohere additionally stated it’s providing Command A Imaginative and prescient in an open weights system, in hopes that enterprises seeking to transfer away from closed or proprietary fashions will begin utilizing its merchandise. Thus far, there’s some curiosity from builders.

Very impressed at its accuracy extracting hand handwritten notes from a picture!

— Adam Sardo (@sardo_adam) July 31, 2025

Lastly, an AI that gained’t decide my horrible doodles.

— Martha Wisener ? (@martwisener) August 1, 2025

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