Beamr’s Benchmark Testing Validates ML-Safe Video Data Workflows for Autonomous Vehicles

Rhea-AI Summary

Beamr (NASDAQ: BMR) published benchmark testing showing its Content-Adaptive Bitrate (CABR) technology reduces autonomous vehicle video storage by roughly 48% while keeping ML model performance intact.

Testing used PandaSet multi-camera data and a YOLOv8 (Nano) object detection model; results reported less than 2% mAP difference versus baseline and strong scores on PSNR and LPIPS. Beamr will discuss results at CES 2026, Jan 6–9 and invites meetings with AV teams.

Positive

• Average file size reduction of ~48%
• Model accuracy impact of less than 2% mAP
• Validation on PandaSet with YOLOv8 (Nano)

Negative

• Measured up to ~2% mAP difference versus baseline

Key Figures

File size reduction 48% Testing demonstrates file size reduction with robust ML accuracy

Storage reduction potential 50% CABR technology delivers up to 50% storage reduction for AV video data

Model accuracy impact <2% Benchmark notes less than 2% ML model accuracy impact with compression

mAP difference <2% Less than 2% difference in mean Average Precision on CABR-compressed videos

CES 2026 dates January 6–9, 2026 AV teams invited to meet Beamr at CES 2026 in Las Vegas

Market Reality Check

$2.00 Last Close

Volume Volume 66,476 is 0.76x the 20-day average of 87,451, showing moderate trading interest. normal

Technical Shares trade below the 200-day MA of 2.73, at a pre-news price of 1.99.

Peers on Argus 1 Down

BMR was up 2.42% pre-news while the only momentum-scanned peer, AMOD, was down 8.93%, indicating stock-specific rather than sector-wide drivers.

Historical Context

Date	Event	Sentiment	Move	Catalyst
Nov 26	Conference participation	Positive	+6.9%	Announced AWS re:Invent 2025 participation showcasing GPU-accelerated video optimization.
Nov 13	Business update	Positive	-1.9%	Q3-2025 CEO letter highlighting AV pipeline expansion and nine-month revenue figures.
Oct 23	Investor conference	Positive	+4.4%	Announcement of presentation at The ThinkEquity Conference with company leadership.
Oct 21	Analyst call	Positive	-4.2%	Participation in Loop Capital expert call focused on Gen AI Video impacts.
Oct 15	Product showcase	Positive	-5.0%	Showcase of NVIDIA-powered video solutions and CABR at Oracle AI World and NAB Show.

Pattern Detected

Recent news, often positive and event-focused, has produced mixed reactions, with more instances of divergence than alignment between upbeat headlines and next-day price moves.

Recent Company History

Over the last few months, Beamr has focused on commercial and visibility milestones in video optimization and autonomous vehicles. Events include participation at AWS re:Invent 2025 on Dec 1–5, 2025, a Q3-2025 CEO letter citing nine‑month revenue of $1.54M and cash of $12.2M, and multiple conference and expert call appearances. Price reactions have ranged from a 6.9% gain to a 5.03% decline, underscoring inconsistent trading responses to largely positive updates.

Market Pulse Summary

This announcement details benchmark results showing Beamr’s CABR technology achieving roughly 48% file size reduction for AV video while keeping ML accuracy impact under 2%. It reinforces the company’s focus on ML-safe compression for autonomous driving workloads, complementing earlier AV pipeline and conference updates. Investors may track further technical disclosures, adoption signals from AV teams, and how these capabilities translate into commercial deals and revenue progression.

Key Terms

content-adaptive bitrate (cabr) technical

"its patented Content-Adaptive Bitrate (CABR) technology delivers up to 50%"

Content-adaptive bitrate (CABR) is a video-delivery method that adjusts streaming quality in real time based on both the viewer’s network conditions and the complexity of what's on-screen, so simple scenes use less data while complex scenes get more detail. For investors, CABR matters because it can improve user experience and reduce bandwidth costs, which affects subscriber retention, platform scalability, and the economics of streaming services.

machine learning technical

"while maintaining the fidelity required for accurate ML model performance"

Machine learning is a set of computer programs that learn patterns from large amounts of data and improve their predictions or decisions over time, like a recipe that gets better each time it’s adjusted based on taste tests. For investors it matters because these systems can speed up analysis, spot trends or risks humans might miss, automate routine work, and potentially create competitive advantages or cost savings that affect a company’s performance.

object detection technical

"The validation focused on object detection, a foundational task for AV"

Object detection is software that finds and identifies specific items within images or video and marks where they are, like a smart camera that draws boxes around cars, medical signs or products on a shelf. For investors, it signals how companies can automate inspection, monitoring or compliance tasks, reduce labor and error, and create new product capabilities that may drive revenue, cost savings and competitive advantage.

yolov8 (nano) technical

"deploying a YOLOv8 (Nano) model on both baseline and CABR-compressed videos"

Yolov8 (nano) is a very small, fast version of a computer vision model that finds and tracks objects in images or video, designed to run on limited hardware like phones, cameras, or factory sensors. For investors it signals how companies can add real-time automation or safety features at low cost and power—think of it as a lightweight, efficient pair of machine eyes that enables new products, reduces manual labor, and speeds up deployments.

mean average precision (map) technical

"less than 2% difference in mean Average Precision (mAP), a standard metric"

Mean average precision (mAP) is a single-number score that summarizes how well a search, recommendation, or detection system places the most relevant items near the top of its results across many queries. Think of it like grading a playlist curator by checking, for each songlist, how many of the best tracks appear near the top and then averaging those grades across many lists. Investors care because higher mAP means users find what they want faster, improving engagement, ad revenue and the reliability of algorithm-driven decisions.

AI-generated analysis. Not financial advice.

Testing demonstrates 48% file size reduction with robust ML model accuracy across multiple industry-standard metrics. AV teams are invited to meet Beamr at CES 2026, January 6-9 in Las Vegas

Herzliya, Israel, Dec. 22, 2025 (GLOBE NEWSWIRE) -- Beamr Imaging Ltd. (NASDAQ: BMR), a leader in video optimization technology and solutions, published benchmark testing results validating that its patented Content-Adaptive Bitrate (CABR) technology delivers up to 50% storage reduction for autonomous vehicle (AV) video data with comprehensive technical demonstration of machine learning (ML) model accuracy.

AV teams and developers attending CES 2026 in Las Vegas, from January 6-9, 2026, are invited to schedule a meeting with Beamr’s video data experts to review the results and discuss ML-safe AV pipelines. To schedule a meeting at CES 2026, visit this link.

The new testing addresses a critical challenge in AV development: balancing the need to reduce massive amounts of real-world and synthetic video data while maintaining the fidelity required for accurate ML model performance. AV systems produce hundreds of petabytes of multi-camera footage, creating substantial costs in budget and infrastructure.

"AV teams need proven approaches to manage video data at scale without risking their ML pipeline integrity,” said Beamr Chief Product Officer, Dani Megrelishvili. “The benchmark testing validates that transformation is possible with confidence - less than 2% model accuracy impact while achieving significant compression efficiency."

The benchmark testing compared Beamr’s CABR technology against industry-standard workflows using PandaSet, a real-world, multi-camera AV dataset. The validation focused on object detection, a foundational task for AV perception systems, deploying a YOLOv8 (Nano) model on both baseline and CABR-compressed videos. The analysis measured model accuracy across the most prevalent classes in the AV industry: persons, cars, motorcycles, and trucks.

Results showed CABR achieved approximately 48% average file size reduction with less than 2% difference in mean Average Precision (mAP), a standard metric for object detection reliability. The testing confirmed robust results across multiple other industry-standard quality metrics, such as PSNR and LPIPS.

The complete benchmark testing methodology and results are available in Beamr's blog post.

To schedule a meeting at CES 2026, visit this link.

About Beamr

Beamr (Nasdaq: BMR) is a world leader in content-adaptive video compression, trusted by top media companies including Netflix and Paramount. Beamr’s perceptual optimization technology (CABR) is backed by 53 patents and a winner of Emmy® Award for Technology and Engineering. The innovative technology reduces video file sizes by up to 50% while preserving quality and enabling AI-powered enhancements.

Beamr powers efficient video workflows across high-growth markets, such as media and entertainment, user-generated content, machine learning, and autonomous vehicles. Its flexible deployment options include on-premises, private or public cloud, with convenient availability for Amazon Web Services (AWS) and Oracle Cloud Infrastructure (OCI) customers.

For more details, please visit www.beamr.com or the investors’ website www.investors.beamr.com

Forward-Looking Statements

This press release contains “forward-looking statements” that are subject to substantial risks and uncertainties. Forward-looking statements in this communication may include, among other things, statements about Beamr’s strategic and business plans, technology, relationships, objectives and expectations for its business, the impact of trends on and interest in its business, intellectual property or product and its future results, operations and financial performance and condition. All statements, other than statements of historical fact, contained in this press release are forward-looking statements. Forward-looking statements contained in this press release may be identified by the use of words such as “anticipate,” “believe,” “contemplate,” “could,” “estimate,” “expect,” “intend,” “seek,” “may,” “might,” “plan,” “potential,” “predict,” “project,” “target,” “aim,” “should,” “will” “would,” or the negative of these words or other similar expressions, although not all forward-looking statements contain these words. Forward-looking statements are based on the Company’s current expectations and are subject to inherent uncertainties, risks and assumptions that are difficult to predict. Further, certain forward-looking statements are based on assumptions as to future events that may not prove to be accurate. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s annual report filed with the SEC on March 4, 2025 and in subsequent filings with the SEC. Forward-looking statements contained in this announcement are made as of the date hereof and the Company undertakes no duty to update such information except as required under applicable law.

Investor Contact:
investorrelations@beamr.com

FAQ

What did Beamr (BMR) report about AV video storage reduction on Dec 22, 2025?

Beamr reported its CABR technology achieved approximately 48% average file size reduction for AV video data.

How did Beamr measure machine learning safety for its AV video compression (BMR)?

Testing used the PandaSet multi-camera dataset and a YOLOv8 (Nano) object detection model to compare baseline and CABR-compressed videos.

What was the impact on object detection accuracy reported by Beamr (BMR)?

Beamr reported less than 2% difference in mAP between baseline and CABR-compressed videos.

Which quality metrics besides mAP did Beamr (BMR) report in its benchmarks?

The company reported robust results across industry-standard metrics including PSNR and LPIPS.

When and where can investors or AV teams meet Beamr (BMR) to review the results?

Beamr will be at CES 2026 in Las Vegas, January 6–9, 2026; meetings can be scheduled through the company link.

Do Beamr's benchmarks support production AV pipelines according to the announcement?

The company presented the benchmarks as validating ML-safe AV pipelines with significant compression and minimal reported mAP impact.