Baidu unveils proprietary ERNIE 5 beating GPT-5 performance on charts, document understanding and more

Mere hours after OpenAI up to date its flagship basis mannequin GPT-5 to GPT-5.1, promising decreased token utilization total and a extra nice persona with extra preset choices, Chinese language search large Baidu unveiled its next-generation foundation model, ERNIE 5.0, alongside a set of AI product upgrades and strategic worldwide expansions.

The purpose: to place as a worldwide contender within the more and more aggressive enterprise AI market.

Introduced on the firm’s Baidu World 2025 occasion, ERNIE 5.0 is a proprietary, natively omni-modal mannequin designed to collectively course of and generate content material throughout textual content, photographs, audio, and video.

Not like Baidu’s lately launched ERNIE-4.5-VL-28B-A3B-Pondering, which is open supply underneath an enterprise-friendly and permissive Apache 2.0 license, ERNIE 5.0 is a proprietary mannequin and is accessible solely through Baidu’s ERNIE Bot web site (I wanted to pick it manuallyu from the mannequin picker dropdown) and the Qianfan cloud platform application programming interface (API) for enterprise customers.

Alongside the mannequin launch, Baidu launched main updates to its digital human platform, no-code instruments, and general-purpose AI brokers — all focused at increasing its AI footprint past China.

The corporate additionally launched ERNIE 5.0 Preview 1022, a variant optimized for text-intensive duties, alongside the final preview mannequin that balances throughout modalities.

Baidu emphasised that ERNIE 5.0 represents a shift in how intelligence is deployed at scale, with CEO Robin Li stating: “Once you internalize AI, it turns into a local functionality and transforms intelligence from a value right into a supply of productiveness.”

The place ERNIE 5.0 outshines GPT-5 and Gemini 2.5 Professional

ERNIE 5.0’s benchmark outcomes counsel that Baidu has achieved parity—or near-parity—with the highest Western basis fashions throughout a large spectrum of duties.

In public benchmark slides shared throughout the Baidu World 2025 occasion, ERNIE 5.0 Preview outperformed or matched OpenAI’s GPT-5-Excessive and Google’s Gemini 2.5 Professional in multimodal reasoning, doc understanding, and image-based QA, whereas additionally demonstrating robust language modeling and code execution skills.

The corporate emphasised its capacity to deal with joint inputs and outputs throughout modalities, slightly than counting on post-hoc modality fusion, which it framed as a technical differentiator.

On visible duties, ERNIE 5.0 achieved main scores on OCRBench, DocVQA, and ChartQA, three benchmarks that check doc recognition, comprehension, and structured knowledge reasoning.

Baidu claims the mannequin beat each GPT-5-Excessive and Gemini 2.5 Professional on these doc and chart-based benchmarks, areas it describes as core to enterprise purposes like automated doc processing and monetary evaluation.

In picture technology, ERNIE 5.0 tied or exceeded Google’s Veo3 throughout classes together with semantic alignment and picture high quality, in line with Baidu’s inner GenEval-based analysis. Baidu claimed that the mannequin’s multimodal integration permits it to generate and interpret visible content material with better contextual consciousness than fashions counting on modality-specific encoders.

For audio and speech duties, ERNIE 5.0 demonstrated aggressive outcomes on MM-AU and TUT2017 audio understanding benchmarks, in addition to query answering from spoken language inputs. Its audio efficiency, whereas not as closely emphasised as imaginative and prescient or textual content, suggests a broad functionality footprint meant to assist full-spectrum multimodal purposes.

In language duties, the mannequin confirmed robust outcomes on instruction following, factual query answering, and mathematical reasoning—core areas that outline the enterprise utility of enormous language fashions.

The Preview 1022 variant of ERNIE 5.0, tailor-made for textual efficiency, confirmed even stronger language-specific ends in early developer entry. Whereas Baidu doesn’t declare broad superiority typically language reasoning, its inner evaluations counsel that ERNIE 5.0 Preview 1022 closes the hole with top-tier English-language fashions and outperforms them in Chinese language-language efficiency.

Whereas Baidu didn’t launch full benchmark particulars or uncooked scores publicly, its efficiency positioning suggests a deliberate try to border ERNIE 5.0 not as a distinct segment multimodal system however as a flagship mannequin aggressive with the most important closed fashions in general-purpose reasoning.

The place Baidu claims a transparent lead is in structured doc understanding, visible chart reasoning, and integration of a number of modalities right into a single, native modeling structure. Unbiased verification of those outcomes stays pending, however the breadth of claimed capabilities positions ERNIE 5.0 as a critical different within the multimodal basis mannequin panorama.

Enterprise Pricing Technique

ERNIE 5.0 is positioned on the premium finish of Baidu’s mannequin pricing construction. The corporate has launched particular pricing for API utilization on its Qianfan platform, aligning the fee with different top-tier choices from Chinese language opponents like Alibaba.

The distinction in value between ERNIE 5.0 and earlier fashions similar to ERNIE 4.5 Turbo underscores Baidu’s technique to differentiate between high-volume, low-cost fashions and high-capability fashions designed for complicated duties and multimodal reasoning.

In comparison with different U.S. alternate options, it stays mid-range in pricing:

International Enlargement: Merchandise and Platforms

In tandem with the mannequin launch, Baidu is increasing internationally:

• GenFlow 3.0, now with 20M+ customers, is the corporate’s largest general-purpose AI agent and options enhanced reminiscence and multimodal job dealing with.

• Famou, a self-evolving agent able to dynamically fixing complicated issues, is now commercially out there through invite.

• MeDo, the worldwide model of Baidu’s no-code builder Miaoda, is reside globally through medo.dev.

• Oreate, a productiveness workspace with doc, slide, picture, video, and podcast assist, has reached over 1.2M customers worldwide.

Baidu’s digital human platform, already rolled out in Brazil, can also be a part of the worldwide push. In accordance with firm knowledge, 83% of livestreamers throughout this 12 months’s “Double 11” buying occasion in China used Baidu’s digital human tech, contributing to a 91% enhance in GMV.

In the meantime, Baidu’s autonomous ride-hailing service Apollo Go has surpassed 17 million rides, working driverless fleets in 22 cities and claiming the title of the world’s largest robotaxi community.

Open-Supply Imaginative and prescient-Language Mannequin Garners Trade Consideration

Two days earlier than the flagship ERNIE 5.0 occasion, Baidu additionally launched an open-source multimodal mannequin underneath the Apache 2.0 license: ERNIE-4.5-VL-28B-A3B-Pondering.

As reported by my colleague Michael Nuñez at VentureBeat, the mannequin prompts simply 3 billion parameters whereas sustaining a complete of 28 billion, utilizing a Combination-of-Specialists (MoE) structure for environment friendly inference.

Key technical improvements embody:

• “Pondering with Photographs”, which permits dynamic zoom-based visible evaluation

• Help for chart interpretation, doc understanding, visible grounding, and temporal consciousness in video

• Runtime on a single 80GB GPU, making it accessible to mid-sized organizations

• Full compatibility with Transformers, vLLM, and Baidu’s FastDeploy toolkits

This launch provides strain on closed-source opponents. With Apache 2.0 licensing, ERNIE-4.5-VL-28B-A3B-Pondering turns into a viable basis mannequin for industrial purposes with out licensing restrictions — one thing few high-performing fashions on this class supply.

Neighborhood Suggestions and Baidu’s Response

Following the launch of ERNIE 5.0, developer and AI evaluator Lisan al Gaib (@scaling01) posted a mixed review on X. Whereas initially impressed by the mannequin’s benchmark efficiency, they reported a persistent situation the place ERNIE 5.0 would repeatedly invoke instruments — even when explicitly instructed to not — throughout SVG technology duties.

“ERNIE 5.0 benchmarks appeared insane till I examined it… sadly it’s RL braindamaged or they’ve a critical situation with their chat platform / system immediate,” Lisan wrote.

In a matter of hours, Baidu’s developer-focused assist account, @ErnieforDevs, responded:

“Thanks for the suggestions! It’s a recognized bug — sure syntax can persistently set off it. We’re engaged on a repair. You may attempt rephrasing or altering the immediate to keep away from it for now.”

The fast turnaround displays Baidu’s rising emphasis on developer communication, particularly because it courts worldwide customers by way of each proprietary and open-source choices.

Outlook for Baidu and its ERNIE foundational LLM household

Baidu’s ERNIE 5.0 marks a strategic escalation within the international basis mannequin race. With efficiency claims that put it on par with essentially the most superior methods from OpenAI and Google, and a mixture of premium pricing and open-access alternate options, Baidu is signaling its ambition to develop into not only a home AI chief, however a reputable international infrastructure supplier.

At a time when enterprise AI customers are more and more demanding multimodal efficiency, versatile licensing, and deployment effectivity, Baidu’s two-track method—premium hosted APIs and open-source releases—could broaden its enchantment throughout each company and developer communities.

Whether or not the corporate’s efficiency claims maintain up underneath third-party testing stays to be seen. However in a panorama formed by rising prices, mannequin complexity, and compute bottlenecks, ERNIE 5.0 and its supporting ecosystem give Baidu a aggressive place within the subsequent wave of AI deployment.

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