Alternatives to GLM-OCR

Compare GLM-OCR alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to GLM-OCR in 2026. Compare features, ratings, user reviews, pricing, and more from GLM-OCR competitors and alternatives in order to make an informed decision for your business.

  • 1
    Google Cloud Vision AI
    Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.
  • 2
    CodeT5

    CodeT5

    Salesforce

    Code for CodeT5, a new code-aware pre-trained encoder-decoder model. Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation. This is the official PyTorch implementation for the EMNLP 2021 paper from Salesforce Research. CodeT5-large-ntp-py is specially optimized for Python code generation tasks and employed as the foundation model for our CodeRL, yielding new SOTA results on the APPS Python competition-level program synthesis benchmark. This repo provides the code for reproducing the experiments in CodeT5. CodeT5 is a new pre-trained encoder-decoder model for programming languages, which is pre-trained on 8.35M functions in 8 programming languages (Python, Java, JavaScript, PHP, Ruby, Go, C, and C#). In total, it achieves state-of-the-art results on 14 sub-tasks in a code intelligence benchmark - CodeXGLUE. Generate code based on the natural language description.
  • 3
    HunyuanOCR

    HunyuanOCR

    Tencent

    Tencent Hunyuan is a large-scale, multimodal AI model family developed by Tencent that spans text, image, video, and 3D modalities, designed for general-purpose AI tasks like content generation, visual reasoning, and business automation. Its model lineup includes variants optimized for natural language understanding, multimodal vision-language comprehension (e.g., image & video understanding), text-to-image creation, video generation, and 3D content generation. Hunyuan models leverage a mixture-of-experts architecture and other innovations (like hybrid “mamba-transformer” designs) to deliver strong performance on reasoning, long-context understanding, cross-modal tasks, and efficient inference. For example, the vision-language model Hunyuan-Vision-1.5 supports “thinking-on-image”, enabling deep multimodal understanding and reasoning on images, video frames, diagrams, or spatial data.
  • 4
    Mu

    Mu

    Microsoft

    Mu is a 330-million-parameter encoder–decoder language model designed to power the agent in Windows settings by mapping natural-language queries to Settings function calls, running fully on-device via NPUs at over 100 tokens per second while maintaining high accuracy. Drawing on Phi Silica optimizations, Mu’s encoder–decoder architecture reuses a fixed-length latent representation to cut computation and memory overhead, yielding 47 percent lower first-token latency and 4.7× higher decoding speed on Qualcomm Hexagon NPUs compared to similar decoder-only models. Hardware-aware tuning, including a 2/3–1/3 encoder–decoder parameter split, weight sharing between input and output embeddings, Dual LayerNorm, rotary positional embeddings, and grouped-query attention, enables fast inference at over 200 tokens per second on devices like Surface Laptop 7 and sub-500 ms response times for settings queries.
  • 5
    ByteScout Text Recognition SDK
    Text Recognition is the process of detecting and converting images or documents (e.g. PDF) that contain typed or printed text into a computer encoded text using OCR (Optical Character Recognition) process powered by Machine Learning and AI. Automates tedious tasks such as data entry from specific documents such as driver licenses, passports, receipts, technical documents, bank statements, etc. Functions to specify rectangular areas of an image those are subject to the recognition with optional rotation and flipping. We combine very sophisticated technologies with any tools you’ll find on the website. We make our SDKs respond to your needs. If you are looking for tutorials and explanations, source codes and documentation will give you a better understanding of what is going on.
  • 6
    Mistral OCR 3

    Mistral OCR 3

    Mistral AI

    Mistral OCR 3 is the third-generation optical character recognition model from Mistral AI designed to achieve a new frontier in accuracy and efficiency for document processing by extracting text, embedded images, and structure from a wide range of documents with exceptional fidelity. It delivers breakthrough performance with a 74% overall win rate over the previous generation on forms, scanned documents, complex tables, and handwriting, outperforming both enterprise document processing solutions and AI-native OCR tools. OCR 3 supports output in clean text, Markdown, or structured JSON with HTML table reconstruction to preserve layout, enabling downstream systems and workflows to understand both content and structure. It powers the Document AI Playground in Mistral AI Studio for drag-and-drop parsing of PDFs and images and integrates via API for developers to automate document extraction workflows.
    Starting Price: $14.99 per month
  • 7
    Whisper

    Whisper

    OpenAI

    We’ve trained and are open-sourcing a neural net called Whisper that approaches human-level robustness and accuracy in English speech recognition. Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web. We show that the use of such a large and diverse dataset leads to improved robustness to accents, background noise, and technical language. Moreover, it enables transcription in multiple languages, as well as translation from those languages into English. We are open-sourcing models and inference code to serve as a foundation for building useful applications and for further research on robust speech processing. The Whisper architecture is a simple end-to-end approach, implemented as an encoder-decoder Transformer. Input audio is split into 30-second chunks, converted into a log-Mel spectrogram, and then passed into an encoder.
  • 8
    Qwen3-VL

    Qwen3-VL

    Alibaba

    Qwen3-VL is the newest vision-language model in the Qwen family (by Alibaba Cloud), designed to fuse powerful text understanding/generation with advanced visual and video comprehension into one unified multimodal model. It accepts inputs in mixed modalities, text, images, and video, and handles long, interleaved contexts natively (up to 256 K tokens, with extensibility beyond). Qwen3-VL delivers major advances in spatial reasoning, visual perception, and multimodal reasoning; the model architecture incorporates several innovations such as Interleaved-MRoPE (for robust spatio-temporal positional encoding), DeepStack (to leverage multi-level features from its Vision Transformer backbone for refined image-text alignment), and text–timestamp alignment (for precise reasoning over video content and temporal events). These upgrades enable Qwen3-VL to interpret complex scenes, follow dynamic video sequences, read and reason about visual layouts.
    Starting Price: Free
  • 9
    Pixtral Large

    Pixtral Large

    Mistral AI

    Pixtral Large is a 124-billion-parameter open-weight multimodal model developed by Mistral AI, building upon their Mistral Large 2 architecture. It integrates a 123-billion-parameter multimodal decoder with a 1-billion-parameter vision encoder, enabling advanced understanding of documents, charts, and natural images while maintaining leading text comprehension capabilities. With a context window of 128,000 tokens, Pixtral Large can process at least 30 high-resolution images simultaneously. The model has demonstrated state-of-the-art performance on benchmarks such as MathVista, DocVQA, and VQAv2, surpassing models like GPT-4o and Gemini-1.5 Pro. Pixtral Large is available under the Mistral Research License for research and educational use, and under the Mistral Commercial License for commercial applications.
    Starting Price: Free
  • 10
    Reka

    Reka

    Reka

    Our enterprise-grade multimodal assistant carefully designed with privacy, security, and efficiency in mind. We train Yasa to read text, images, videos, and tabular data, with more modalities to come. Use it to generate ideas for creative tasks, get answers to basic questions, or derive insights from your internal data. Generate, train, compress, or deploy on-premise with a few simple commands. Use our proprietary algorithms to personalize our model to your data and use cases. We design proprietary algorithms involving retrieval, fine-tuning, self-supervised instruction tuning, and reinforcement learning to tune our model on your datasets.
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    GLM-4.1V

    GLM-4.1V

    Zhipu AI

    GLM-4.1V is a vision-language model, providing a powerful, compact multimodal model designed for reasoning and perception across images, text, and documents. The 9-billion-parameter variant (GLM-4.1V-9B-Thinking) is built on the GLM-4-9B foundation and enhanced through a specialized training paradigm using Reinforcement Learning with Curriculum Sampling (RLCS). It supports a 64k-token context window and accepts high-resolution inputs (up to 4K images, any aspect ratio), enabling it to handle complex tasks such as optical character recognition, image captioning, chart and document parsing, video and scene understanding, GUI-agent workflows (e.g., interpreting screenshots, recognizing UI elements), and general vision-language reasoning. In benchmark evaluations at the 10 B-parameter scale, GLM-4.1V-9B-Thinking achieved top performance on 23 of 28 tasks.
    Starting Price: Free
  • 12
    Qwen3-Omni

    Qwen3-Omni

    Alibaba

    Qwen3-Omni is a natively end-to-end multilingual omni-modal foundation model that processes text, images, audio, and video and delivers real-time streaming responses in text and natural speech. It uses a Thinker-Talker architecture with a Mixture-of-Experts (MoE) design, early text-first pretraining, and mixed multimodal training to support strong performance across all modalities without sacrificing text or image quality. The model supports 119 text languages, 19 speech input languages, and 10 speech output languages. It achieves state-of-the-art results: across 36 audio and audio-visual benchmarks, it hits open-source SOTA on 32 and overall SOTA on 22, outperforming or matching strong closed-source models such as Gemini-2.5 Pro and GPT-4o. To reduce latency, especially in audio/video streaming, Talker predicts discrete speech codecs via a multi-codebook scheme and replaces heavier diffusion approaches.
  • 13
    HunyuanCustom
    HunyuanCustom is a multi-modal customized video generation framework that emphasizes subject consistency while supporting image, audio, video, and text conditions. Built upon HunyuanVideo, it introduces a text-image fusion module based on LLaVA for enhanced multi-modal understanding, along with an image ID enhancement module that leverages temporal concatenation to reinforce identity features across frames. To enable audio- and video-conditioned generation, it further proposes modality-specific condition injection mechanisms, an AudioNet module that achieves hierarchical alignment via spatial cross-attention, and a video-driven injection module that integrates latent-compressed conditional video through a patchify-based feature-alignment network. Extensive experiments on single- and multi-subject scenarios demonstrate that HunyuanCustom significantly outperforms state-of-the-art open and closed source methods in terms of ID consistency, realism, and text-video alignment.
  • 14
    Janus-Pro-7B
    Janus-Pro-7B is an innovative open-source multimodal AI model from DeepSeek, designed to excel in both understanding and generating content across text, images, and videos. It leverages a unique autoregressive architecture with separate pathways for visual encoding, enabling high performance in tasks ranging from text-to-image generation to complex visual comprehension. This model outperforms competitors like DALL-E 3 and Stable Diffusion in various benchmarks, offering scalability with versions from 1 billion to 7 billion parameters. Licensed under the MIT License, Janus-Pro-7B is freely available for both academic and commercial use, providing a significant leap in AI capabilities while being accessible on major operating systems like Linux, MacOS, and Windows through Docker.
    Starting Price: Free
  • 15
    SmolVLM

    SmolVLM

    Hugging Face

    SmolVLM-Instruct is a compact, AI-powered multimodal model that combines the capabilities of vision and language processing, designed to handle tasks like image captioning, visual question answering, and multimodal storytelling. It works with both text and image inputs, providing highly efficient results while being optimized for smaller, resource-constrained environments. Built with SmolLM2 as its text decoder and SigLIP as its image encoder, the model offers improved performance for tasks that require integration of both textual and visual information. SmolVLM-Instruct can be fine-tuned for specific applications, offering businesses and developers a versatile tool for creating intelligent, interactive systems that require multimodal inputs.
    Starting Price: Free
  • 16
    EasyOCR

    EasyOCR

    EURESYS

    Euresys EasyOCR is an optical character recognition software library within the Open eVision suite that provides teachable, template-based printed text recognition designed to read short text such as part numbers, serial numbers, expiry dates, manufacturing dates, and lot codes from images or parts in machine vision applications; it uses a font-dependent template matching algorithm that can be trained with custom character examples and comes with pre-defined fonts, enabling reliable recognition even when characters vary in size, are poorly printed, broken, or connected, and supports separation of adjacent text elements in challenging conditions. It is size-invariant and rapid, and can be trained on sample images to build a character database (font) that improves recognition performance for specific industrial text styles. EasyOCR is typically embedded into vision inspection systems via the Open eVision API.
  • 17
    Ray2

    Ray2

    Luma AI

    Ray2 is a large-scale video generative model capable of creating realistic visuals with natural, coherent motion. It has a strong understanding of text instructions and can take images and video as input. Ray2 exhibits advanced capabilities as a result of being trained on Luma’s new multi-modal architecture scaled to 10x compute of Ray1. Ray2 marks the beginning of a new generation of video models capable of producing fast coherent motion, ultra-realistic details, and logical event sequences. This increases the success rate of usable generations and makes videos generated by Ray2 substantially more production-ready. Text-to-video generation is available in Ray2 now, with image-to-video, video-to-video, and editing capabilities coming soon. Ray2 brings a whole new level of motion fidelity. Smooth, cinematic, and jaw-dropping, transform your vision into reality. Tell your story with stunning, cinematic visuals. Ray2 lets you craft breathtaking scenes with precise camera movements.
    Starting Price: $9.99 per month
  • 18
    PaperStream

    PaperStream

    PFU America, Inc., a Ricoh Company

    PaperStream Capture Pro is a powerful front-end capture software that transforms paper documents (or imported digital files) into clean, indexed, searchable digital data ready for document-management workflows. It supports batch scanning with any TWAIN-compatible scanner, whether a desktop model or an enterprise-grade device, and uses advanced image-processing via its integrated engine to automatically enhance scanned images, remove noise, correct skew/rotation/color issues, and improve clarity for better OCR and readability. It offers robust data-extraction capabilities; full-text OCR, zonal OCR, barcode and patch-code reading, and even optical-mark-recognition and handprint recognition for handwritten block text or checkboxes. It can extract many fields per document (for example, from forms, applications, or surveys), automatically separate documents in mixed batches (using blank pages, barcodes, patch codes, or form-template recognition), and assign metadata.
    Starting Price: $334.55 per year
  • 19
    Yandex Vision
    Yandex Vision OCR recognizes text in an image and outputs it along with automatic punctuation. The service supports and automatically identifies more than 50 languages. Extract standard fields and recognize text in templates and documents, e.g., passports, driver’s licenses, vehicle registration certificates, and license plates. With support for Russian and English, as well as combinations of handwritten and printed texts. The service scans the table structure and outputs text in row and column coordinates. Optical character recognition (OCR), document recognition, and license plate number recognition. Yandex Vision OCR allows you to work with JPEG, PNG, and PDF formats. File sizes should be no larger than 20 MB with no more than 300 pages per file. The service can scan images and find passports from 20 countries, driver’s licenses, vehicle registration documents, and license plates.
  • 20
    RoboOCR

    RoboOCR

    Softdiv Software

    Easy to use OCR software (optical character recognition) that can capture text from screen, images, PDFs, videos and other digital documents. It can quickly extract and recognize any non-selectable and non-editable text on your Windows screen.
    Starting Price: $29.95
  • 21
    GLM-4.5V-Flash
    GLM-4.5V-Flash is an open source vision-language model, designed to bring strong multimodal capabilities into a lightweight, deployable package. It supports image, video, document, and GUI inputs, enabling tasks such as scene understanding, chart and document parsing, screen reading, and multi-image analysis. Compared to larger models in the series, GLM-4.5V-Flash offers a compact footprint while retaining core VLM capabilities like visual reasoning, video understanding, GUI task handling, and complex document parsing. It can serve in “GUI agent” workflows, meaning it can interpret screenshots or desktop captures, recognize icons or UI elements, and assist with automated desktop or web-based tasks. Although it forgoes some of the largest-model performance gains, GLM-4.5V-Flash remains versatile for real-world multimodal tasks where efficiency, lower resource usage, and broad modality support are prioritized.
    Starting Price: Free
  • 22
    Mistral Document AI
    Mistral Document AI is an enterprise-grade document processing solution that combines advanced Optical Character Recognition (OCR) with structured data extraction capabilities. It achieves over 99% accuracy in extracting and understanding complex text, handwriting, tables, and images from various documents across global languages. It can process up to 2,000 pages per minute on a single GPU, offering minimal latency and cost-efficient throughput. Mistral Document AI integrates OCR with powerful AI tooling to enable flexible, full document lifecycle workflows, making archives instantly accessible. It supports annotations, allowing users to extract information in a structured JSON format, and combines OCR with large language model capabilities to enable natural language interaction with document content. This allows for tasks such as question answering about specific document content, information extraction, and summarization, and context-aware responses.
    Starting Price: $14.99 per month
  • 23
    KamuSEO

    KamuSEO

    KamuSEO

    It's a complete visitor and SEO analytics, a great tool to analyze your site's visitors and analyze any site's information. It has the ability to analyze your own website's information. It has the ability to analyze any other website's information. It has a native API by which developers can integrate its facilities with another app. KamuSEO is an app to analyze your site visitors and analyze any site's information such as Alexa data, similar web data, whois data, social media data, Moz check, search engine index, Google page rank, IP analysis, malware check, etc. Input a domain name and you will get a js code. Copy the embedded js code and paste it into your web page. You will get a daily report about your website. You will get some bonus utility tools such as email encoder/decoder, metatag generator, tag generator, plagiarism check, valid email check, duplicate email filter, URL encoder/decoder, etc.
    Starting Price: $29 per month
  • 24
    MedGemma

    MedGemma

    Google DeepMind

    MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension. Developers can use MedGemma to accelerate building healthcare-based AI applications. MedGemma currently comes in two variants: a 4B multimodal version and a 27B text-only version. MedGemma 4B utilizes a SigLIP image encoder that has been specifically pre-trained on a variety of de-identified medical data, including chest X-rays, dermatology images, ophthalmology images, and histopathology slides. Its LLM component is trained on a diverse set of medical data, including radiology images, histopathology patches, ophthalmology images, and dermatology images. MedGemma 4B is available in both pre-trained (suffix: -pt) and instruction-tuned (suffix -it) versions. The instruction-tuned version is a better starting point for most applications.
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    LLaVA

    LLaVA

    LLaVA

    LLaVA (Large Language-and-Vision Assistant) is an innovative multimodal model that integrates a vision encoder with the Vicuna language model to facilitate comprehensive visual and language understanding. Through end-to-end training, LLaVA exhibits impressive chat capabilities, emulating the multimodal functionalities of models like GPT-4. Notably, LLaVA-1.5 has achieved state-of-the-art performance across 11 benchmarks, utilizing publicly available data and completing training in approximately one day on a single 8-A100 node, surpassing methods that rely on billion-scale datasets. The development of LLaVA involved the creation of a multimodal instruction-following dataset, generated using language-only GPT-4. This dataset comprises 158,000 unique language-image instruction-following samples, including conversations, detailed descriptions, and complex reasoning tasks. This data has been instrumental in training LLaVA to perform a wide array of visual and language tasks effectively.
    Starting Price: Free
  • 26
    MonoQwen-Vision
    MonoQwen2-VL-v0.1 is the first visual document reranker designed to enhance the quality of retrieved visual documents in Retrieval-Augmented Generation (RAG) pipelines. Traditional RAG approaches rely on converting documents into text using Optical Character Recognition (OCR), which can be time-consuming and may result in loss of information, especially for non-textual elements like graphs and tables. MonoQwen2-VL-v0.1 addresses these limitations by leveraging Visual Language Models (VLMs) that process images directly, eliminating the need for OCR and preserving the integrity of visual content. This reranker operates in a two-stage pipeline, initially, it uses separate encoding to generate a pool of candidate documents, followed by a cross-encoding model that reranks these candidates based on their relevance to the query. By training a Low-Rank Adaptation (LoRA) on top of the Qwen2-VL-2B-Instruct model, MonoQwen2-VL-v0.1 achieves high performance without significant memory overhead.
  • 27
    CodeQwen

    CodeQwen

    Alibaba

    CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.
    Starting Price: Free
  • 28
    MyFreeOCR

    MyFreeOCR

    MyFreeOCR

    Optical character recognition is the process of recognizing characters from an image. This is especially useful if you want to edit a scanned document. You can use our free online OCR service to convert your scanned documents and download it as a text file ready for editing. Your document should be a valid PDF file or image, for example: PDF, JPG, PNG. Our free OCR service can handle several languages, including: Chinese, English, Portuguese, Spanish, etc. Start converting image to text now!
  • 29
    ScanScan

    ScanScan

    ScanScan

    ScanScan is a high accurate and efficient OCR text recognition and document scanning App. It has high recognition accuracy, faster speed, clean scanning effect and can generate PDF. Translate text on image, pick text on image, make reading notes, paper documents to electronic files, identification of identity cards and so on. Leaders of the same area, handle 50 pictures at a time for text recognition and document scanning. Form recognition, recognize form image to .xls files, which can be continue edited in Excel or Numbers. The recognition result is automatically saved as a historical record and easy to search. Automatically continuous document scanning and generate PDF. Restore the original paragraph.
  • 30
    VideoPoet
    VideoPoet is a simple modeling method that can convert any autoregressive language model or large language model (LLM) into a high-quality video generator. It contains a few simple components. An autoregressive language model learns across video, image, audio, and text modalities to autoregressively predict the next video or audio token in the sequence. A mixture of multimodal generative learning objectives are introduced into the LLM training framework, including text-to-video, text-to-image, image-to-video, video frame continuation, video inpainting and outpainting, video stylization, and video-to-audio. Furthermore, such tasks can be composed together for additional zero-shot capabilities. This simple recipe shows that language models can synthesize and edit videos with a high degree of temporal consistency.
  • 31
    Taggun

    Taggun

    Taggun

    Automatic receipt transcription that doesn’t suck. Receipt OCR is a software technology that scans receipt images and digitizes the receipt into meaningful and structured data that other software can understand. The data commonly includes in OCR (optical character recognition) receipt recognition are the total amount, tax amount, date and merchant name of the receipt. Developer friendly RESTful API web services. TAGGUN APIs accept JPG, PDF, PNG, GIF, and URL of a file. Automatically detects the language on the receipt. Converts image to plain raw text. Takes advantage of the best OCR engines in the industry. Machine learning model classifies keywords on a receipt. TAGGUN engine extracts key information from raw text. Calculate the confidence level for each field for accuracy. Returns detailed information in JSON format. Results ready to be consumed by your app.
  • 32
    Tencent Cloud OCR
    Tencent Cloud Optical Character Recognition (OCR) can automatically locate and recognize text in images. It features robustness and an average accuracy rate of above 95% for printed text and 90% for handwritten text. Developed independently by the Tencent YouTu Lab, OCR covers all core algorithms for identity document analysis and recognition. It supports both landscape and portrait modes, and can be applied in scenarios with perspective distortion, irregular illumination, partial occlusion and more. OCR not only provides developers with a full range of APIs that can be called directly, but also SDKs that are highly compatible and easy to use.It can recognize Chinese text, English text, Chinese/English text, numbers, and special symbols with higher accuracy. It can recognize complex text at higher accuracy and recall rates, making it suitable for scenarios with a large amount of text, long numeric strings, small font, blurry or skewed text, etc.
  • 33
    GPT-4

    GPT-4

    OpenAI

    GPT-4 (Generative Pre-trained Transformer 4) is a large-scale unsupervised language model, yet to be released by OpenAI. GPT-4 is the successor to GPT-3 and part of the GPT-n series of natural language processing models, and was trained on a dataset of 45TB of text to produce human-like text generation and understanding capabilities. Unlike most other NLP models, GPT-4 does not require additional training data for specific tasks. Instead, it can generate text or answer questions using only its own internally generated context as input. GPT-4 has been shown to be able to perform a wide variety of tasks without any task specific training data such as translation, summarization, question answering, sentiment analysis and more.
    Starting Price: $0.0200 per 1000 tokens
  • 34
    Amazon Textract
    Amazon Textract is a fully managed machine learning service that automatically extracts text and data from scanned documents that goes beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables. Many companies today extract data from scanned documents, such as PDF's, tables and forms, through manual data entry (that is slow, expensive and prone to errors), or through simple OCR software that requires manual configuration which needs to be updated each time the form changes to be usable. To overcome these manual processes, Textract uses machine learning to instantly read and process any type of document, accurately extracting text, forms, tables, and, other data without the need for any manual effort or custom code. With Textract you can quickly automate manual document activities, enabling you to process millions of document pages in hours.
  • 35
    SmartOCR

    SmartOCR

    SmartSoft

    With Smart OCR you can easily convert scanned PDF documents, images and scanned text into editable and searchable files. SmartOCR delivers highly accurate optical character recognition technology to help you convert scanned paper documents and screenshots into fully editable and searchable digital files. The product offers a convenient interface that lets you perform conversion easily without any previous training. With SmartOCR, you can easily recognize low-quality documents, screenshots and fax documents. The application supports various image formats, such as BMP, JPEG, TIFF, GIFF and more. The built-in text editor with a spell-checker helps you fix any errors quickly and very easily. Batch OCR conversion is also supported, enabling you to convert multiple documents simultaneously. SmartOCR offers multiple output formats, including DOC, RTF and HTML. With the innovative OCR technology you can create edit-ready digital documents, retaining the original layout.
    Starting Price: $49.90 one-time payment
  • 36
    GLM-4.5V

    GLM-4.5V

    Zhipu AI

    GLM-4.5V builds on the GLM-4.5-Air foundation, using a Mixture-of-Experts (MoE) architecture with 106 billion total parameters and 12 billion activation parameters. It achieves state-of-the-art performance among open-source VLMs of similar scale across 42 public benchmarks, excelling in image, video, document, and GUI-based tasks. It supports a broad range of multimodal capabilities, including image reasoning (scene understanding, spatial recognition, multi-image analysis), video understanding (segmentation, event recognition), complex chart and long-document parsing, GUI-agent workflows (screen reading, icon recognition, desktop automation), and precise visual grounding (e.g., locating objects and returning bounding boxes). GLM-4.5V also introduces a “Thinking Mode” switch, allowing users to choose between fast responses or deeper reasoning when needed.
    Starting Price: Free
  • 37
    NVIDIA DeepStream SDK
    NVIDIA's DeepStream SDK is a comprehensive streaming analytics toolkit based on GStreamer, designed for AI-based multi-sensor processing, including video, audio, and image understanding. It enables developers to create stream-processing pipelines that incorporate neural networks and complex tasks like tracking, video encoding/decoding, and rendering, facilitating real-time analytics on various data types. DeepStream is integral to NVIDIA Metropolis, a platform for building end-to-end services that transform pixel and sensor data into actionable insights. The SDK offers a powerful and flexible environment suitable for a wide range of industries, supporting multiple programming options such as C/C++, Python, and Graph Composer's intuitive UI. It allows for real-time insights by understanding rich, multi-modal sensor data at the edge and supports managed AI services through deployment in cloud-native containers orchestrated with Kubernetes.
  • 38
    UBIAI

    UBIAI

    UBIAI

    Leverage UBIAI's powerful labeling platform to train and deploy your custom NLP model faster than ever! When dealing with semi-structured text such as invoices or contracts, preserving document layout is key to training a high-performance model. Combining natural language processing and computer vision, UBIAI’s OCR feature allows you to perform NER, relation extraction, and classification annotation directly on native PDF documents, scanned images or pictures from your phone without losing any layout information, resulting in a significant boost of your NLP model performance. With UBIAI text annotation tool you can perform named entity recognition (NER), relation extraction and document classification all in the same interface. Unlike other tools, UBIAI enables you to create nested and overlapping entities containing multiple relations.
    Starting Price: $299 per month
  • 39
    Hunyuan Motion 1.0

    Hunyuan Motion 1.0

    Tencent Hunyuan

    Hunyuan Motion (also known as HY-Motion 1.0) is a state-of-the-art text-to-3D motion generation AI model that uses a billion-parameter Diffusion Transformer with flow matching to turn natural language prompts into high-quality, skeleton-based 3D character animation in seconds. It understands descriptive text in English and Chinese and produces smooth, physically plausible motion sequences that integrate seamlessly into standard 3D animation pipelines by exporting to skeleton formats such as SMPL or SMPLH and common formats like FBX or BVH for use in Blender, Unity, Unreal Engine, Maya, and other tools. The model’s three-stage training pipeline (large-scale pre-training on thousands of hours of motion data, fine-tuning on curated sequences, and reinforcement learning from human feedback) enhances its ability to follow complex instructions and generate realistic, temporally coherent motion.
  • 40
    ERNIE 3.0 Titan
    Pre-trained language models have achieved state-of-the-art results in various Natural Language Processing (NLP) tasks. GPT-3 has shown that scaling up pre-trained language models can further exploit their enormous potential. A unified framework named ERNIE 3.0 was recently proposed for pre-training large-scale knowledge enhanced models and trained a model with 10 billion parameters. ERNIE 3.0 outperformed the state-of-the-art models on various NLP tasks. In order to explore the performance of scaling up ERNIE 3.0, we train a hundred-billion-parameter model called ERNIE 3.0 Titan with up to 260 billion parameters on the PaddlePaddle platform. Furthermore, We design a self-supervised adversarial loss and a controllable language modeling loss to make ERNIE 3.0 Titan generate credible and controllable texts.
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    Karlo

    Karlo

    Kakao Brain

    Karlo stands as a groundbreaking model for generating images based on text prompts. It builds upon OpenAI's remarkable unCLIP architecture but takes a step further by enhancing the standard super-resolution model, allowing it to recover intricate details at a remarkable resolution of 256px, all while minimizing noise through a limited number of denoising steps. To create Karlo, we embarked on an extensive training process. We started from scratch, utilizing a vast dataset of 115 million image-text pairs, which included COYO-100M, CC3M, and CC12M. In the case of the Prior and Decoder components, we harnessed the power of ViT-L/14, a text encoder from OpenAI's CLIP repository. To optimize efficiency, we made a significant modification to the original unCLIP implementation. Instead of employing a trainable transformer in the decoder, we integrated the text encoder from ViT-L/14.
    Starting Price: Free
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    Online OCR

    Online OCR

    OnlineOCR

    Picture to text converter allows you to extract text from images or convert PDF to Doc, Excel or Text formats using Optical Character Recognition software online. To extract text and characters from scanned PDF documents (including multipage files), photos and digital camera captured images. Any JPG, BMP or PNG images can be converted into text output formats with the same layout as the original file. Convert PDF to WORD or EXCEL online. Extract text from scanned PDF documents, photos, and captured images without payment. You may convert files from mobile devices (iPhone or Android) or PC (Windows\Linux\MacOS). All documents uploaded under the free "Guest" account will be deleted automatically after conversion. Output files for registered users are stored one month. OCR service is free for "Guest" users (without registration) and allows you to convert 15 files per hour.
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    Towhee

    Towhee

    Towhee

    You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. Towhee includes a pythonic method-chaining API for describing custom data processing pipelines. We also support schemas, making processing unstructured data as easy as handling tabular data.
    Starting Price: Free
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    Qwen-7B

    Qwen-7B

    Alibaba

    Qwen-7B is the 7B-parameter version of the large language model series, Qwen (abbr. Tongyi Qianwen), proposed by Alibaba Cloud. Qwen-7B is a Transformer-based large language model, which is pretrained on a large volume of data, including web texts, books, codes, etc. Additionally, based on the pretrained Qwen-7B, we release Qwen-7B-Chat, a large-model-based AI assistant, which is trained with alignment techniques. The features of the Qwen-7B series include: Trained with high-quality pretraining data. We have pretrained Qwen-7B on a self-constructed large-scale high-quality dataset of over 2.2 trillion tokens. The dataset includes plain texts and codes, and it covers a wide range of domains, including general domain data and professional domain data. Strong performance. In comparison with the models of the similar model size, we outperform the competitors on a series of benchmark datasets, which evaluates natural language understanding, mathematics, coding, etc. And more.
    Starting Price: Free
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    PanGu-α

    PanGu-α

    Huawei

    PanGu-α is developed under the MindSpore and trained on a cluster of 2048 Ascend 910 AI processors. The training parallelism strategy is implemented based on MindSpore Auto-parallel, which composes five parallelism dimensions to scale the training task to 2048 processors efficiently, including data parallelism, op-level model parallelism, pipeline model parallelism, optimizer model parallelism and rematerialization. To enhance the generalization ability of PanGu-α, we collect 1.1TB high-quality Chinese data from a wide range of domains to pretrain the model. We empirically test the generation ability of PanGu-α in various scenarios including text summarization, question answering, dialogue generation, etc. Moreover, we investigate the effect of model scales on the few-shot performances across a broad range of Chinese NLP tasks. The experimental results demonstrate the superior capabilities of PanGu-α in performing various tasks under few-shot or zero-shot settings.
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    Aquaforest Searchlight
    Ensure your documents are 100% searchable with Aquaforest Searchlight's automated OCR for SharePoint, Office 365, and Windows. Aquaforest Searchlight automatically takes non-searchable documents such as Images PDFs, scanned image files, and faxes and convert the files to fully searchable PDF format. These types of files need to be processed with optical character recognition (OCR) technology to create a text version of the file contents which allows a searchable PDF to be created by merging the original page images with the text. This enables the file to be searched. For on-premises SharePoint you would install Searchlight on an on-premises server, communication is made between Searchlight and your on-prem SharePoint via standard Microsoft APIs and the document processing is performed on the server where Searchlight is installed. All our products are supported on virtual machines including Oracle VM virtual box.
    Starting Price: €416 per year
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    OPT

    OPT

    Meta

    Large language models, which are often trained for hundreds of thousands of compute days, have shown remarkable capabilities for zero- and few-shot learning. Given their computational cost, these models are difficult to replicate without significant capital. For the few that are available through APIs, no access is granted to the full model weights, making them difficult to study. We present Open Pre-trained Transformers (OPT), a suite of decoder-only pre-trained transformers ranging from 125M to 175B parameters, which we aim to fully and responsibly share with interested researchers. We show that OPT-175B is comparable to GPT-3, while requiring only 1/7th the carbon footprint to develop. We are also releasing our logbook detailing the infrastructure challenges we faced, along with code for experimenting with all of the released models.
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    SpeedOCR

    SpeedOCR

    Beyond Key

    Experience the transformative power of AI-powered OCR Solutions. This cutting-edge solution combines artificial intelligence and optical character recognition technology to streamline your document processing workflows. Extract key information from invoices, receipts, and contracts.
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    Blox.ai

    Blox.ai

    Blox.ai

    Business data is usually present in different formats, across sources. A lot of business data is unstructured and semi-structured. IDP (Intelligent Document Processing) leverages AI, along with programmable automation (such as repetitive tasks), to convert data into usable, structured formats, and for consumption by downstream systems.Using Natural Language Processing (NLP), Computer Vision (CV), Optical Character Recognition (OCR) and machine learning tools, Blox.ai identifies, labels and extracts relevant data from any type of document. The AI then maps this extracted information into a structured format while configuring a model which can be applied to all similar document types. The Blox.ai stack is set up to reconcile the data based on business requirements and to push the output to downstream systems automatically.
    Starting Price: $650
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    Hugging Face Transformers
    ​Transformers is a library of pretrained natural language processing, computer vision, audio, and multimodal models for inference and training. Use Transformers to train models on your data, build inference applications, and generate text with large language models. Explore the Hugging Face Hub today to find a model and use Transformers to help you get started right away.​ Simple and optimized inference class for many machine learning tasks like text generation, image segmentation, automatic speech recognition, document question answering, and more. A comprehensive trainer that supports features such as mixed precision, torch.compile, and FlashAttention for training and distributed training for PyTorch models.​ Fast text generation with large language models and vision language models. Every model is implemented from only three main classes (configuration, model, and preprocessor) and can be quickly used for inference or training.
    Starting Price: $9 per month