Alternatives to Mu
Compare Mu alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Mu in 2026. Compare features, ratings, user reviews, pricing, and more from Mu competitors and alternatives in order to make an informed decision for your business.
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1
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. -
2
GLM-OCR
Z.ai
GLM-OCR is a multimodal optical character recognition model and open source repository that provides accurate, efficient, and comprehensive document understanding by combining text and visual modalities into a unified encoder–decoder architecture derived from the GLM-V family. Built with a visual encoder pre-trained on large-scale image–text data and a lightweight cross-modal connector feeding into a GLM-0.5B language decoder, the model supports layout detection, parallel region recognition, and structured output for text, tables, formulas, and complicated real-world document formats. It introduces Multi-Token Prediction (MTP) loss and stable full-task reinforcement learning to improve training efficiency, recognition accuracy, and generalization, achieving state-of-the-art benchmarks on major document understanding tasks.Starting Price: Free -
3
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 -
4
OpenAI Whisper
OpenAI
Whisper is an automatic speech recognition (ASR) system developed by OpenAI for converting spoken language into text. It is trained on 680,000 hours of multilingual and multitask audio data collected from the web. The model is designed to handle diverse accents, background noise, and technical language with high accuracy. Whisper supports transcription in multiple languages as well as translation into English. It uses an encoder-decoder Transformer architecture to process audio inputs and generate text outputs. The system can also perform tasks like language identification and timestamp generation. Overall, Whisper enables developers to build robust voice-enabled applications with ease. -
5
Uni-1
Luma AI
UNI-1 is a multimodal artificial intelligence model developed by Luma AI that unifies visual generation and reasoning capabilities within a single architecture, representing a step toward multimodal general intelligence. It was designed to overcome the limitations of traditional AI pipelines, where language models, image generators, and other systems operate independently without shared reasoning. UNI-1 integrates these capabilities so that language, visual understanding, and image generation work together inside one system, allowing the model to reason about scenes, interpret instructions, and generate visual outputs that follow logical and spatial constraints. At its core, UNI-1 is a decoder-only autoregressive transformer that processes text and images as a single interleaved sequence of tokens, enabling the model to treat language and visual information within the same computational framework rather than through separate encoders. -
6
Yi-Large
01.AI
Yi-Large is a proprietary large language model developed by 01.AI, offering a 32k context length with both input and output costs at $2 per million tokens. It stands out with its advanced capabilities in natural language processing, common-sense reasoning, and multilingual support, performing on par with leading models like GPT-4 and Claude3 in various benchmarks. Yi-Large is designed for tasks requiring complex inference, prediction, and language understanding, making it suitable for applications like knowledge search, data classification, and creating human-like chatbots. Its architecture is based on a decoder-only transformer with enhancements such as pre-normalization and Group Query Attention, and it has been trained on a vast, high-quality multilingual dataset. This model's versatility and cost-efficiency make it a strong contender in the AI market, particularly for enterprises aiming to deploy AI solutions globally.Starting Price: $0.19 per 1M input token -
7
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 -
8
Falcon-7B
Technology Innovation Institute (TII)
Falcon-7B is a 7B parameters causal decoder-only model built by TII and trained on 1,500B tokens of RefinedWeb enhanced with curated corpora. It is made available under the Apache 2.0 license. Why use Falcon-7B? It outperforms comparable open-source models (e.g., MPT-7B, StableLM, RedPajama etc.), thanks to being trained on 1,500B tokens of RefinedWeb enhanced with curated corpora. See the OpenLLM Leaderboard. It features an architecture optimized for inference, with FlashAttention and multiquery. It is made available under a permissive Apache 2.0 license allowing for commercial use, without any royalties or restrictions.Starting Price: Free -
9
Arctic Embed 2.0
Snowflake
Snowflake's Arctic Embed 2.0 introduces multilingual capabilities to its text embedding models, enhancing global-scale retrieval without compromising English performance or scalability. Building upon the robust foundation of previous releases, Arctic Embed 2.0 supports multiple languages, enabling 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. The model leverages Matryoshka Representation Learning (MRL) for efficient embedding storage, allowing for significant compression with minimal quality degradation. This advancement ensures that enterprises can handle demanding workloads such as training large-scale models, fine-tuning, real-time inference, and high-performance computing tasks across diverse languages and regions.Starting Price: $2 per credit -
10
yarl
Python Software Foundation
All URL parts, scheme, user, password, host, port, path, query, and fragment are accessible by properties. All URL manipulations produce a new URL object. Strings passed to constructor and modification methods are automatically encoded giving canonical representation as result. Regular properties are percent-decoded, use raw_ versions for getting encoded strings. Human-readable representation of URL is available as .human_repr(). PyPI contains binary wheels for Linux, Windows and MacOS. If you want to install yarl on another operating system (like Alpine Linux, which is not manylinux-compliant because of the missing glibc and therefore, cannot be used with our wheels) the tarball will be used to compile the library from the source code. It requires a C compiler and Python headers installed. Please note that the pure-Python (uncompiled) version is much slower. However, PyPy always uses a pure-Python implementation, and, as such, it is unaffected by this variable.Starting Price: Free -
11
DeepSeek-OCR
DeepSeek
DeepSeek-OCR is an open source model for Contexts Optical Compression, built to explore the boundaries of visual-text compression and investigate the role of vision encoders from an LLM-centric viewpoint. It is designed to compress long contexts through optical 2D mapping, using DeepEncoder as the core engine and DeepSeek3B-MoE-A570M as the decoder. DeepEncoder maintains low activations under high-resolution input while achieving high compression ratios, keeping the number of vision tokens manageable for document understanding. The model supports OCR and document parsing workflows for images and PDFs, with inference through vLLM or Transformers. Users can run image OCR with streaming output, process PDFs with high concurrency, or run batch evaluation for benchmarks. DeepSeek-OCR can convert documents to Markdown, perform free OCR without layouts, parse figures, describe images in detail, and locate referenced text inside an image.Starting Price: Free -
12
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 -
13
Use Of Tools
Use Of Tools
A collection of free online tools for developers, content writers, researchers, analysts, and others may be found at UseOfTools.com, including conversion tools, different text and SEO tools, encoder and decoder, and more.Starting Price: Free -
14
Phi-4-mini-flash-reasoning
Microsoft
Phi-4-mini-flash-reasoning is a 3.8 billion‑parameter open model in Microsoft’s Phi family, purpose‑built for edge, mobile, and other resource‑constrained environments where compute, memory, and latency are tightly limited. It introduces the SambaY decoder‑hybrid‑decoder architecture with Gated Memory Units (GMUs) interleaved alongside Mamba state‑space and sliding‑window attention layers, delivering up to 10× higher throughput and a 2–3× reduction in latency compared to its predecessor without sacrificing advanced math and logic reasoning performance. Supporting a 64 K‑token context length and fine‑tuned on high‑quality synthetic data, it excels at long‑context retrieval, reasoning tasks, and real‑time inference, all deployable on a single GPU. Phi-4-mini-flash-reasoning is available today via Azure AI Foundry, NVIDIA API Catalog, and Hugging Face, enabling developers to build fast, scalable, logic‑intensive applications. -
15
Falcon-40B
Technology Innovation Institute (TII)
Falcon-40B is a 40B parameters causal decoder-only model built by TII and trained on 1,000B tokens of RefinedWeb enhanced with curated corpora. It is made available under the Apache 2.0 license. Why use Falcon-40B? It is the best open-source model currently available. Falcon-40B outperforms LLaMA, StableLM, RedPajama, MPT, etc. See the OpenLLM Leaderboard. It features an architecture optimized for inference, with FlashAttention and multiquery. It is made available under a permissive Apache 2.0 license allowing for commercial use, without any royalties or restrictions. ⚠️ This is a raw, pretrained model, which should be further finetuned for most usecases. If you are looking for a version better suited to taking generic instructions in a chat format, we recommend taking a look at Falcon-40B-Instruct.Starting Price: Free -
16
Nimble Streamer
Softvelum
Light-weight fast freeware media server. Nimble Streamer provides wide feature set for live streaming via various protocols including SRT, NDI and Apple Low Latency HLS with codecs like AVC/H.264, HEVC/H.265 and more. Decode, transform and encode live video and audio streams with Nimble Streamer transcoding premium add-on.Starting Price: $50 USD/m -
17
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 -
18
LFM2
Liquid AI
LFM2 is a next-generation series of on-device foundation models built to deliver the fastest generative-AI experience across a wide range of endpoints. It employs a new hybrid architecture that achieves up to 2x faster decode and prefill performance than comparable models, and up to 3x improvements in training efficiency compared to the previous generation. These models strike an optimal balance of quality, latency, and memory for deployment on embedded systems, allowing real-time, on-device AI across smartphones, laptops, vehicles, wearables, and other endpoints, enabling millisecond inference, device resilience, and full data sovereignty. Available in three dense checkpoints (0.35 B, 0.7 B, and 1.2 B parameters), LFM2 demonstrates benchmark performance that outperforms similarly sized models in tasks such as knowledge recall, mathematics, multilingual instruction-following, and conversational dialogue evaluations. -
19
SafeJSON
SafeJSON
SafeJSON is an all-in-one local JSON toolkit built exclusively for developers. All parsing, comparison, JWT decoding and validation runs 100% inside your browser, with zero user data uploaded to external servers. Core features include standard JSON formatter, visual JSON Diff, JWT token decoder, JSONPath query engine, and JSON Schema validator. It supports huge 50MB+ JSON files powered by Web Workers, dark mode, collapsible tree views, and one-click raw JSON export. Users can independently verify full privacy via Chrome DevTools Network panel — no API keys, tokens or confidential payloads leave your device. The core toolset is permanently free, with advanced features (Diff & JWT) available via SafeJSON Pro ($5/month or $39/year). The full codebase is fully open-source on GitHub for full audit.Starting Price: $5/month, $39 -
20
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. -
21
GLM-4.5
Z.ai
GLM‑4.5 is Z.ai’s latest flagship model in the GLM family, engineered with 355 billion total parameters (32 billion active) and a companion GLM‑4.5‑Air variant (106 billion total, 12 billion active) to unify advanced reasoning, coding, and agentic capabilities in one architecture. It operates in a “thinking” mode for complex, multi‑step reasoning and tool use, and a “non‑thinking” mode for instant responses, supporting up to 128 K token context length and native function calling. Available via the Z.ai chat platform and API, with open weights on HuggingFace and ModelScope, GLM‑4.5 ingests diverse inputs to solve general problem‑solving, common‑sense reasoning, coding from scratch or within existing projects, and end‑to‑end agent workflows such as web browsing and slide generation. Built on a Mixture‑of‑Experts design with loss‑free balance routing, grouped‑query attention, and an MTP layer for speculative decoding, it delivers enterprise‑grade performance. -
22
FonePaw Video Converter Ultimate
FonePaw
Multifunctional software makes it possible for you to convert, edit and play videos, DVD and audios. In addition, you can also create you own videos or GIF image freely with it. You can convert one video at a time or add several video files for converting simultaneously. It can decode and encode videos on a CUDA-enabled graphics card, leading to your fast and high quality HD and SD video conversion. Your video will not be quality loss. Equipped with NVIDIA's CUDA and AMD APP acceleration technology, you're able to experience 6X faster conversion speed and supports multi-core processor completely. Supported with NVIDIA® CUDA™, AMD®, etc. technologies, FonePaw Video Converter Ultimate can decode and encode videos on a CUDA-enabled graphics card, leading to your fast and high quality HD and SD video conversion. This all-in-one video converter is capable of converting video, audio and DVD files efficiently and even editing them with better effect.Starting Price: $39 one-time payment -
23
myDevices
myDevices
Maintains encrypted connections with devices supporting HTTP and MQTT protocols. Receives traffic from LoRa Network Servers and data stream from other IoT Clouds. All-purpose serverless computing or function as a service (FaaS) provides codecs and integrations online editing. Decodes and normalizes uplink device data and encodes downlink commands simplifying the deployment of integration functions. Manage device registry, configuration, provisioning, and FOTA scheduling and batching. Easily de-register and re-register devices via LNS Switch. Stores LoRaWAN keys and SSL/TLS certificates with access to real-time data insights. Industry-leading performance with large data volume storage to easily query billions of rows of telemetric and historic data. Fast ingest of millions of data points per second, plus vertical and horizontal scalability powered by data streaming processing engine. -
24
DiffusionGemma
Google
DiffusionGemma is an experimental open model that explores text diffusion, an exceptionally fast approach to text generation. Released under an Apache 2.0 license, this 26B Mixture of Experts (MoE) model moves beyond the sequential token-by-token processing of typical autoregressive Large Language Models (LLMs). Instead, it generates entire blocks of text simultaneously, delivering up to 4x faster text generation on GPUs. Built on the intelligence-per-parameter of the Gemma 4 family and Gemini Diffusion research, DiffusionGemma integrates a novel diffusion head designed to maximize generation speed. It is designed for researchers and developers exploring speed-critical, interactive local workflows such as in-line editing, rapid iteration, and non-linear text structures. By shifting the decode bottleneck from memory bandwidth to compute, it can generate more than 1,000 tokens per second on a single NVIDIA H100 and more than 700 tokens per second on an NVIDIA GeForce RTX 5090.Starting Price: Free -
25
PixelChain
PixelChain
Today most NFTs and CryptoArtworks share the same problem, the images are stored off-chain. If the project where the data is stored dies the graphic information of the artwork will be most probably lost. Storing all the artwork information and metadata on the chain solves this problem. Now you can create and store art 100% on chain that will live forever. Whenever a PixelChain gets minted our innovator smart contract will encode all the image data, compress it and send it to the blockchain, where it gets stored together with its name and author information. Later on, this data can be always accessible directly from the blockchain, decompressed and decoded by our open source decoder in order to rebuild the original image that was created by the artist. This is our MVP solution for storing Art 100% On-chain. We will apply the same principle to store other kinds of artwork like Music and Voxels.Starting Price: Free -
26
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 -
27
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 -
28
Tencent Cloud GPU Service
Tencent
Cloud GPU Service is an elastic computing service that provides GPU computing power with high-performance parallel computing capabilities. As a powerful tool at the IaaS layer, it delivers high computing power for deep learning training, scientific computing, graphics and image processing, video encoding and decoding, and other highly intensive workloads. Improve your business efficiency and competitiveness with high-performance parallel computing capabilities. Set up your deployment environment quickly with auto-installed GPU drivers, CUDA, and cuDNN and preinstalled driver images. Accelerate distributed training and inference by using TACO Kit, an out-of-the-box computing acceleration engine provided by Tencent Cloud.Starting Price: $0.204/hour -
29
Pioneer
Pioneer.ai
Pioneer is an inference API built for developers who would rather ship than babysit a GPU cluster. It lets teams point an existing OpenAI, Anthropic, or other client at Pioneer, keep the same API and code, and run inference like normal while Pioneer finds where the current model falls short. It clusters production traffic by use case, surfaces where accuracy, latency, or cost can improve, then builds and routes to small specialist models automatically. Its continuous improvement loop, Adaptive Inference, mines live production failures for high-signal examples, retrains a specialist model, evaluates the new checkpoint, and promotes improvements behind the same endpoint without requiring redeployment. Pioneer supports encoder models for structured extraction tasks such as named entity recognition, text classification, structured JSON extraction, privacy filtering, and safety classification, as well as decoder models for text generation, classification, open-ended prompting, etc. -
30
ByteScout BarCode Reader SDK
ByteScout
Integrate barcode reading from PDF, JPG, PNG, TIFF images, and PDF into your applications in just a few minutes. Barcode Reader is pre-installed into POS-prepared Elo Tablet by Elo Touch. Elo Tablet clients have a nice method to easily decipher QR Code from a built-in webcam. Barcode Reader SDK and Barcode Generator SDK can help you to arrange your reports with a standardized identification classifier encoded into barcodes (like QR Code, Datamatrix, or similar) containing a label, classification, or unique id of your document. With Barcode Reader SDK these barcodes can be effectively decoded back into your app and process a vast number of scanned reports, and speed up the whole process significantly. You can use Barcode Reader to automatically track your gear by scanning barcode labels on hardware. Your app can use photo images to decode barcodes or even scan from the live camera.Starting Price: $9.99 per month -
31
Seed-Music
ByteDance
Seed-Music is a unified framework for high-quality and controlled music generation and editing, capable of producing vocal and instrumental works from multimodal inputs such as lyrics, style descriptions, sheet music, audio references, or voice prompts, and of supporting post-production editing of existing tracks by allowing direct modification of melodies, timbres, lyrics, or instruments. It combines autoregressive language modeling with diffusion approaches and a three-stage pipeline comprising representation learning (which encodes raw audio into intermediate representations, including audio tokens, symbolic music tokens, and vocoder latents), generation (which transforms these multimodal inputs into music representations), and rendering (which converts those representations into high-fidelity audio). The system supports lead-sheet to song conversion, singing synthesis, voice conversion, audio continuation, style transfer, and fine-grained control over music structure. -
32
ExtendsClass
ExtendsClass
ExtendsClass provides tools directly usable in a browser. It saves you from having to install add-ons to your browser in order to add features. You have at your disposal syntax validators, code formatters, testers, HTTP clients, mock server, but also a SQLite browser. These are small and easy-to-use tools that can help when you do not want to install software on your workstation. The available tools allow you to convert data (CSV, TSV, XML and JSON), compare data (Text, XML, JSON), format data (XML, JSON) and also encode and decode base 64 data.Starting Price: Free -
33
vLLM
vLLM
vLLM is a high-performance library designed to facilitate efficient inference and serving of Large Language Models (LLMs). Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. It offers state-of-the-art serving throughput by efficiently managing attention key and value memory through its PagedAttention mechanism. It supports continuous batching of incoming requests and utilizes optimized CUDA kernels, including integration with FlashAttention and FlashInfer, to enhance model execution speed. Additionally, vLLM provides quantization support for GPTQ, AWQ, INT4, INT8, and FP8, as well as speculative decoding capabilities. Users benefit from seamless integration with popular Hugging Face models, support for various decoding algorithms such as parallel sampling and beam search, and compatibility with NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs, and more. -
34
Wafer
Wafer
Wafer delivers the fastest open source LLMs for enterprise through serverless and dedicated inference built for production AI workloads. Its serverless inference gives teams access to top open models with no infrastructure, no deployment overhead, and fast APIs, including GLM-5.2-Fast for low-latency inference with EAGLE speculative decoding and a per-stream throughput SLA, GLM-5.2 as a flagship model with stronger coding and reasoning capabilities, and more. Wafer’s technology uses agents that optimize inference across the stack, identifying and enhancing bottlenecks in orchestration, algorithms, serving engines, GPU kernels, and diverse hardware. It profiles the stack to see whether latency or throughput comes from scheduling, decoding, kernels, memory pressure, or hardware fit, then tries many paths and ships the measured winner. Instead of relying on a single switch or heuristic, Wafer searches model, engine, kernel, and hardware combinations.Starting Price: Free -
35
EmbeddingGemma
Google
EmbeddingGemma is a 308-million-parameter multilingual text embedding model, lightweight yet powerful, optimized to run entirely on everyday devices such as phones, laptops, and tablets, enabling fast, offline embedding generation that protects user privacy. Built on the Gemma 3 architecture, it supports over 100 languages, processes up to 2,000 input tokens, and leverages Matryoshka Representation Learning (MRL) to offer flexible embedding dimensions (768, 512, 256, or 128) for tailored speed, storage, and precision. Its GPU-and EdgeTPU-accelerated inference delivers embeddings in milliseconds, under 15 ms for 256 tokens on EdgeTPU, while quantization-aware training keeps memory usage under 200 MB without compromising quality. This makes it ideal for real-time, on-device tasks such as semantic search, retrieval-augmented generation (RAG), classification, clustering, and similarity detection, whether for personal file search, mobile chatbots, or custom domain use. -
36
Kaywa
Kaywa
QR Codes are a proven and easy-to-understand technology to bridge the gap between the physical (aka meatspace) and the digital world. You can encode any type of textual information in a QR Code, for example your website's address, a Facebook page, a coupon, a contact. Once published on paper, any other physical support (or even on the web), people with a QR App can scan your QR Code. By scanning they decode the information and the app then renders the website, the Facebook page, the coupon or the contact. QR Codes come in two types, either static or dynamic. We always recommend to use dynamic codes. Static code simply encode the information. With Kaywa you can create an unlimited number of static QR Codes free of charge. More interesting are dynamic codes and our QR MGMT only stores these. dynamic codes can be changed, tracked and they are ideal for scanning with a mobile phone.Starting Price: $13.75 per month -
37
requests
Python Software Foundation
Requests is a simple, yet elegant, HTTP library. Requests allows you to send HTTP/1.1 requests extremely easily. There’s no need to manually add query strings to your URLs, or to form-encode your PUT & POST data, but nowadays, just use the JSON method! Requests is one of the most downloaded Python packages today, pulling in around 30M downloads/week, according to GitHub, Requests is currently depended upon by 1,000,000+ repositories. You may certainly put your trust in this code. Requests is available on PyPI. Requests is ready for the demands of building robust and reliable HTTP–speaking applications, for the needs of today. Automatic content decompression and decoding. International domains and URLs. Sessions with cookie persistence. Browser-style TLS/SSL verification. Basic & digest authentication, and familiar dict–like cookies. Multi-part file uploads. SOCKS proxy support. Connection timeouts and streaming downloads.Starting Price: Free -
38
CortexDecoder
Code Corp.
Code has led the hardware & software barcode scanning industry for over 20 years. During that time, our decoding algorithm, known as CortexDecoder, has proven unmatched in its ability to decode complex barcode symbologies of nearly any quality, on any surface, quickly & without fail. CortexDecoder is available in the form of multiple SDKs, facilitating easy, rapid barcode data capture from any angle, including damaged codes & in less-than-ideal environmental conditions. Are you interested in seeing our unique barcode scanning software first-hand? We offer various FREE options for testing what is possible. These "demo" options include; -FREE temporary SDK licensing for set durations of time allowing for deployment testing & development -FREE mobile apps highlighting features for testing -Once ready to implement, flexible licensing options include both "offline" & "online" models -Fully scalable to match the growth needs you have today or will have in the future -
39
Mividi
Mividi
Mividi IP Video Monitoring System (TSM100) is an ideal choice for monitoring video QoS of IPTV services. In general, IPTV service providers acquire video content from multiple sources, including satellite, fiber optical cable, terrestrial broadcast, as well as locally generated videos. The source streams may be decoded and re-encoded to satisfy their bandwidth allocation needs and meet the specification of customers’ receiving devices. Therefore, it is common that hundreds of programs and many different transport streams are being processed in service providers’ head-ends. Additional complexity may be added in order to process advertisement insertion and provide EPG information. In order to provide their customers with video services with the best possible quality, service providers need to actively monitor their services at multiple points where streams are processed. -
40
GLM-Image
Z.ai
GLM-Image is a next-generation, open source image generation model developed by Z.ai, designed to combine deep language understanding with high-fidelity visual synthesis. Unlike traditional diffusion-only models, it uses a hybrid architecture that integrates an autoregressive language model with a diffusion decoder, enabling it to first reason about the structure, meaning, and relationships within a prompt before generating the image itself. This approach allows GLM-Image to excel in scenarios that require precise semantic control, such as generating infographics, presentation slides, posters, and diagrams with accurate embedded text and complex layouts. With a total of around 16 billion parameters, the model achieves strong performance in rendering readable, correctly placed text within images, an area where many image models struggle, while maintaining detailed visual quality and consistency. -
41
HD Player
Khoa Tran Anh
HD Player is one of the few video players that can present Dolby Vision & HDR10+ videos correctly. Supports most video and audio codecs. Supports Dolby Vision videos. Supports HDR10+ videos. Hardware-accelerated H264 decoder. Hardware-accelerated HEVC decoder. Thanks to the hardware-accelerated decoder, HD Player provides an excellent video playback time than another software-based players. Thanks to the hardware-accelerated decoder, HD Player consumes less energy than another software-based player. Muti-core decoding, TV output & Bluetooth headset. iTunes & Wi-Fi file sharing. WebDAV & SMB file sharing. The SSA subtitle is fully supported. HD Player supports many playing modes, normal mode, repeat mode, and shuffle mode. Manage your videos by playlist. Save the video exit time, so it can start playing from the beginning or were left off. Protect your videos with a passcode. Select audio, subtitle stream, and disable subtitle track. Load external subtitles and delete external files.Starting Price: Free -
42
Pinecone Rerank v0
Pinecone
Pinecone Rerank V0 is a cross-encoder model optimized for precision in reranking tasks, enhancing enterprise search and retrieval-augmented generation (RAG) systems. It processes queries and documents together to capture fine-grained relevance, assigning a relevance score from 0 to 1 for each query-document pair. The model's maximum context length is set to 512 tokens to preserve ranking quality. Evaluations on the BEIR benchmark demonstrated that Pinecone Rerank V0 achieved the highest average NDCG@10, outperforming other models on 6 out of 12 datasets. For instance, it showed up to a 60% boost on the Fever dataset compared to Google Semantic Ranker and over 40% on the Climate-Fever dataset relative to cohere-v3-multilingual or voyageai-rerank-2. The model is accessible through Pinecone Inference and is available to all users in public preview.Starting Price: $25 per month -
43
Death By Captcha
Death By Captcha
Death By Captcha is a world-class captcha resolution service. With more than 14 years in the captcha bypass business, Death By Captcha has become one of the industry leaders in the market. Our teams of technical experts and specialized decoders have worked together to create an incredibly fast and highly accurate system. Death By Captcha offers an excellent low price of $1.39 per 1000 decoded captcha, a team of 24/7 captcha decoders with a 95% to 100% success rate, an average response time of 15 seconds, and multiple API clients. With Death By Captcha, you can solve any captcha. All you need to do is implement our API, pass us your captchas and we will return the text, it is easy. A hybrid system made up of the most advanced OCR system on the market, along with a team of captcha 24/7 solvers. An average response time of 9 seconds for normal text captchas, with an average precision rate of 90% or more.Starting Price: $1.39 per 1000 requests -
44
OmniPlayer
OmniPlayer
OmniPlayer for Mac is a comprehensive media player for almost any video and audio format on macOS. It has powerful features with a modern and clean design. You can use it to play various 4K/1080P/720P HD videos and normal/lossless audio easily with hardware decoding. OmniPlayer’s rich features let you conveniently control and adjust the playback, playlists, video images, audio tracks, subtitles, and screenshots, etc. Record media files to playlists automatically and automatically clear all when exiting the player. Change the encoding of subtitles in different languages to fix subtitle display problems. Play almost any format of the local and remote server videos and audios (SAMBA/FTP protocol). Play, search, delete, change repeat mode of media items in the playlist.Starting Price: Free -
45
LTM-2-mini
Magic AI
LTM-2-mini is a 100M token context model: LTM-2-mini. 100M tokens equals ~10 million lines of code or ~750 novels. For each decoded token, LTM-2-mini’s sequence-dimension algorithm is roughly 1000x cheaper than the attention mechanism in Llama 3.1 405B1 for a 100M token context window. The contrast in memory requirements is even larger – running Llama 3.1 405B with a 100M token context requires 638 H100s per user just to store a single 100M token KV cache.2 In contrast, LTM requires a small fraction of a single H100’s HBM per user for the same context. -
46
LMCache
LMCache
LMCache is an open source Knowledge Delivery Network (KDN) designed as a caching layer for large language model serving that accelerates inference by reusing KV (key-value) caches across repeated or overlapping computations. It enables fast prompt caching, allowing LLMs to “prefill” recurring text only once and then reuse those stored KV caches, even in non-prefix positions, across multiple serving instances. This approach reduces time to first token, saves GPU cycles, and increases throughput in scenarios such as multi-round question answering or retrieval augmented generation. LMCache supports KV cache offloading (moving cache from GPU to CPU or disk), cache sharing across instances, and disaggregated prefill, which separates the prefill and decoding phases for resource efficiency. It is compatible with inference engines like vLLM and TGI and supports compressed storage, blending techniques to merge caches, and multiple backend storage options.Starting Price: Free -
47
AutoGlassCRM
AutoGlassCRM
Dealer part number to aftermarket part number match every time. Best Auto Glass VIN Decoder on the market today. Build and save all your quotes for when customers call back to schedule. Add the VIN Decoder to your own website to be used for customers to get quotes, schedule appointments and get pricing on all year make model vehicles. We offer NAGS pricing and NAGS labor hours alongside our VIN decoder for a per-search or monthly add-on. Allow multiple sales people to see and update customers jobs when they call in to change informatio. Price check all your distributors at the same time to get the best pricing and availability. Check pricing and availability while you are on the phone with customers. Pricing calculator included so you can give customers a price quickly and schedule.Starting Price: $19.99 per month -
48
ColBERT
Future Data Systems
ColBERT is a fast and accurate retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds. It relies on fine-grained contextual late interaction: it encodes each passage into a matrix of token-level embeddings. At search time, it embeds every query into another matrix and efficiently finds passages that contextually match the query using scalable vector-similarity (MaxSim) operators. These rich interactions allow ColBERT to surpass the quality of single-vector representation models while scaling efficiently to large corpora. The toolkit includes components for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. ColBERT integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts.Starting Price: Free -
49
AVPlayer
EPLAYWORKS
The AVPlayer can play almost any computer video file format such as AVI, Xvid, WMV, and much more clearly and effortlessly. No converting hassles. Just copy files via USB and just drag and drop them into the AVPlayer’s Media Explorer. The AVPlayer can also support external subtitle files such as SMI and SRT. So if you enjoy watching videos on your iPad, then the AVPlayer is an absolute necessity. High-quality video clips of 720P (1280 x 720) or more are recommended for MP4 format. MP4, MOV, and M4V formats that QuickTime supports can be played up to 1080P by using a H/W decoder, post-processing function isn’t provided. Support H/W decoding for MKV and AVI (720P supported on iPad1, 1080P supported on iPad2. Hybrid decoding mode is added and now it is able to play high-resolution videos by using the hardware accelerator feature embedded in iPhone/iPad even for mkv or avi in h264. Also, battery use time has extended.Starting Price: $2.99 one-time payment -
50
Decode
Entropik
Decode enables a data-driven approach to uncover meaningful patterns and trends with quantifiable insights from heat maps, transparency plots, and attention and engagement metrics through facial coding, eye tracking and voice tonality. Experience unrivaled convenience and precision as our AI transcribes and translates interviews within minutes. With support for 58 transcription and 135 translation languages, our platform delivers the best-in-class accuracy you can rely on for your valuable data. Decode is ahead of its game, integrating with ChatGPT to deliver comprehensive summaries, AI-generated highlights and topics, revolutionizing the way qualitative research is done.
