Alternatives to Sup AI
Compare Sup AI alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Sup AI in 2026. Compare features, ratings, user reviews, pricing, and more from Sup AI competitors and alternatives in order to make an informed decision for your business.
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1
Inkling
Thinking Machines Lab
Inkling is an open-weights multimodal AI model from Thinking Machines designed as a customizable foundation model for developers, researchers, and enterprises. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, and support for context windows up to 1 million tokens. Inkling was trained from scratch on text, images, audio, and video, giving it native capabilities across reasoning, coding, agentic tool use, vision, audio, factuality, and instruction following. It is built with controllable thinking effort so users can balance performance, latency, and token efficiency for different workloads. The model is available for fine-tuning on Tinker, with playground access, API availability through ecosystem partners, and full weights published on Hugging Face. Built for customization, Inkling gives teams an open-weights base model for building domain-specific AI systems, multimodal agents, coding workflows, research tools, and more.Starting Price: Free -
2
Rauno
Rauno
Rauno is a platform that lets you prompt multiple AI models at once and see them discuss responses with each other real-time in a single chat. Compare perspectives from ChatGPT, Gemini, and Claude as they cross‑verify, factcheck, disagree, and refine answers, helping you spot errors and find the truth. Beyond simple comparison, Rauno introduces an engine designed to combat AI hallucinations. Whether you are debugging complex code, fact-checking academic research, or brainstorming creative concepts, having a diverse council of AI experts ensures you aren't reliant on a single model's inherent biases. The founder of Rauno, Robin Rauno, says: "I got tired of switching tabs to verify AI answers. So I built a roundtable to let the main AI models debate and check eachother's anwers. The first time I saw the best AI models discuss any topic with each other in a brutally honest way, I felt that this tool was not only useful to myself, but also to others. Thats why I launched it in 2026."Starting Price: Free -
3
LLM Council
LLM Council
LLM Council is a lightweight multi-model orchestration tool that enables users to query several large language models simultaneously and synthesize their outputs into a single, higher-confidence response. Instead of relying on one AI system, it routes a prompt to a panel of models, each of which produces an independent answer before anonymously reviewing and ranking the others’ work. A designated “Chairman” model then combines the strongest insights into a unified final output, mimicking the dynamics of a panel of experts reaching consensus. It typically runs as a simple local web interface with a Python backend and React frontend and connects through aggregation services to access models from providers such as OpenAI, Google, and Anthropic. This structured peer-review workflow is designed to surface blind spots, reduce hallucinations, and improve answer reliability by introducing multiple perspectives and cross-model critique.Starting Price: $25 per month -
4
OpenRouter Model Fusion
OpenRouter
OpenRouter Fusion turns a prompt into a small multi-model deliberation, making combined model results as easy to call as a single model. A panel of expert models analyzes the prompt in parallel with web search and web fetch enabled, then a judge model compares their responses and returns structured analysis that includes consensus, contradictions, partial coverage, unique insights, and blind spots. The final answer is written from that analysis, helping users benefit from multiple perspectives rather than relying on one model alone. Fusion is built for cases where a single model is not enough, such as research, expert critique, compare-and-contrast prompts, multi-domain questions, or any task where being wrong is expensive. Users can call Fusion directly through the openrouter/fusion model alias, enable it as the fusion server tool, or configure it through the Fusion plugin; all three entry points use the same pipeline.Starting Price: Free -
5
Voyage AI
MongoDB
Voyage AI provides best-in-class embedding models and rerankers designed to supercharge search and retrieval for unstructured data. Its technology powers high-quality Retrieval-Augmented Generation (RAG) by improving how relevant context is retrieved before responses are generated. Voyage AI offers general-purpose, domain-specific, and company-specific models to support a wide range of use cases. The models are optimized for accuracy, low latency, and reduced costs through shorter vector dimensions. With long-context support of up to 32K tokens, Voyage AI enables deeper understanding of complex documents. The platform is modular and integrates easily with any vector database or large language model. Voyage AI is trusted by industry leaders to deliver reliable, factual AI outputs at scale. -
6
AI Fiesta
AI Fiesta
AI Fiesta is a unified AI workspace that brings together the world's leading large language models under a single roof. With one subscription, users unlock access to ChatGPT, Google Gemini, Anthropic Claude, Perplexity AI, DeepSeek, Grok, Kimi, Qwen, Llama, Seedream, and 25+ more models. Features include Super Fiesta Mode (auto model selection), side-by-side model comparison, Consensus Feature (synthesized multi-model answers), AI Avatars, Deep Research, Image Studio, Document Generation, Promptbook, Projects, and a Community. At $12/month, AI Fiesta is the most cost-effective way to access the world's best AI with no API keys required.Starting Price: $12/month/user -
7
DataGemma
Google
DataGemma represents a pioneering effort by Google to enhance the accuracy and reliability of large language models (LLMs) when dealing with statistical and numerical data. Launched as a set of open models, DataGemma leverages Google's Data Commons, a vast repository of public statistical data—to ground its responses in real-world facts. This initiative employs two innovative approaches: Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). The RIG method integrates real-time data checks during the generation process to ensure factual accuracy, while RAG retrieves relevant information before generating responses, thereby reducing the likelihood of AI hallucinations. By doing so, DataGemma aims to provide users with more trustworthy and factually grounded answers, marking a significant step towards mitigating the issue of misinformation in AI-generated content. -
8
Llama Guard
Meta
Llama Guard is an open-source safeguard model developed by Meta AI to enhance the safety of large language models in human-AI conversations. It functions as an input-output filter, classifying both prompts and responses into safety risk categories, including toxicity, hate speech, and hallucinations. Trained on a curated dataset, Llama Guard achieves performance on par with or exceeding existing moderation tools like OpenAI's Moderation API and ToxicChat. Its instruction-tuned architecture allows for customization, enabling developers to adapt its taxonomy and output formats to specific use cases. Llama Guard is part of Meta's broader "Purple Llama" initiative, which combines offensive and defensive security strategies to responsibly deploy generative AI models. The model weights are publicly available, encouraging further research and adaptation to meet evolving AI safety needs. -
9
DeepEval
Confident AI
DeepEval is a simple-to-use, open source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning, LangChain, or LlamaIndex, DeepEval has you covered. With it, you can easily determine the optimal hyperparameters to improve your RAG pipeline, prevent prompt drifting, or even transition from OpenAI to hosting your own Llama2 with confidence. The framework supports synthetic dataset generation with advanced evolution techniques and integrates seamlessly with popular frameworks, allowing for efficient benchmarking and optimization of LLM systems.Starting Price: Free -
10
LLMWise
LLMWise
LLMWise is a multi-model AI platform that lets you access 52+ models from 18 providers using a single credit wallet and one API key. It’s designed to replace multiple separate AI subscriptions by offering GPT, Claude, Gemini, and many more models in one dashboard and API. Users can compare model answers side-by-side, blend outputs, judge responses, and set up failover routing for reliability. The platform supports multiple data paths per prompt, evaluating options like speed and cost to return the best response. It offers usage-settled billing so you pay for actual token consumption rather than a flat monthly fee, with free starter credits that never expire. Developers can integrate quickly using REST, cURL, or SDKs for Python and TypeScript with streaming support. LLMWise also emphasizes production readiness with features like audit-ready routing traces, encrypted key storage, and optional zero-retention mode. -
11
Grounded Language Model (GLM)
Contextual AI
Contextual AI introduces its Grounded Language Model (GLM), engineered specifically to minimize hallucinations and deliver highly accurate, source-based responses for retrieval-augmented generation (RAG) and agentic applications. The GLM prioritizes faithfulness to the provided data, ensuring responses are grounded in specific knowledge sources and backed by inline citations. With state-of-the-art performance on the FACTS groundedness benchmark, the GLM outperforms other foundation models in scenarios requiring high accuracy and reliability. The model is designed for enterprise use cases like customer service, finance, and engineering, where trustworthy and precise responses are critical to minimizing risks and improving decision-making. -
12
Kuse AI
Kuse AI
Kuse AI is an AI-powered visual workspace that blends an infinite canvas interface with powerful, multi-model AI, enabling users to organize, analyze, and ideate across diverse media like text, PDFs, videos, links, and images. It supports intuitive drag-and-drop structuring in open-ended layouts, while AI offers context-aware suggestions, content summaries, formatting, and source-verified insights to transform chaotic inputs into structured, polished outputs. Trusted for its transparency and reliability, Kuse ensures responses include citations to reliable sources, mitigating hallucinations. Additional capabilities include automatic document formatting, exam-paper generation from templates, customizable project canvases, and real-time collaboration. Together, these features make Kuse a dynamic environment for creative thinkers, researchers, educators, marketers, and strategists to map ideas, generate deliverables like reports or slides. -
13
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. -
14
GPT-5 thinking
OpenAI
GPT-5 Thinking is the deeper reasoning mode within the GPT-5 unified AI system, designed to tackle complex, open-ended problems that require extended cognitive effort. It works alongside the faster GPT-5 model, dynamically engaging when queries demand more detailed analysis and thoughtful responses. This mode significantly reduces hallucinations and improves factual accuracy, producing more reliable answers on challenging topics like science, math, coding, and health. GPT-5 Thinking is also better at recognizing its own limitations, communicating clearly when tasks are impossible or underspecified. It incorporates advanced safety features to minimize harmful outputs and provide nuanced, helpful answers even in ambiguous or sensitive contexts. Available to all users, it helps bring expert-level intelligence to everyday and advanced use cases alike. -
15
Opik
Comet
Confidently evaluate, test, and ship LLM applications with a suite of observability tools to calibrate language model outputs across your dev and production lifecycle. Log traces and spans, define and compute evaluation metrics, score LLM outputs, compare performance across app versions, and more. Record, sort, search, and understand each step your LLM app takes to generate a response. Manually annotate, view, and compare LLM responses in a user-friendly table. Log traces during development and in production. Run experiments with different prompts and evaluate against a test set. Choose and run pre-configured evaluation metrics or define your own with our convenient SDK library. Consult built-in LLM judges for complex issues like hallucination detection, factuality, and moderation. Establish reliable performance baselines with Opik's LLM unit tests, built on PyTest. Build comprehensive test suites to evaluate your entire LLM pipeline on every deployment.Starting Price: $39 per month -
16
Qwen3.5-Plus
Alibaba
Qwen3.5-Plus is a high-performance native vision-language model designed for efficient text generation, deep reasoning, and multimodal understanding. Built on a hybrid architecture that combines linear attention with a sparse mixture-of-experts design, it delivers strong performance while optimizing inference efficiency. The model supports text, image, and video inputs and produces text outputs, making it suitable for complex multimodal workflows. With a massive 1 million token context window and up to 64K output tokens, Qwen3.5-Plus enables long-form reasoning and large-scale document analysis. It includes advanced capabilities such as structured outputs, function calling, web search, and tool integration via the Responses API. The model supports prefix continuation, caching, batch processing, and fine-tuning for flexible deployment. Designed for developers and enterprises, Qwen3.5-Plus provides scalable, high-throughput AI performance with OpenAI-compatible API access.Starting Price: $0.4 per 1M tokens -
17
Ithy
Ithy
Ithy is an advanced AI-powered research and knowledge synthesis platform designed to combine the capabilities of multiple leading artificial intelligence models into a single, unified system that produces comprehensive, high-quality answers. It operates as an “AI aggregator,” meaning it does not rely on a single model but instead queries and integrates responses from multiple large language models, including systems similar to ChatGPT, Gemini, and others, to generate more accurate and nuanced outputs. It transforms user queries into interactive, article-style responses that can include text, charts, videos, and other visual elements, creating a richer and more engaging research experience compared to traditional chat-based tools. It offers different research modes, such as fast analysis for quick answers and deep research for more detailed, multi-perspective insights, allowing users to choose the level of depth and speed they need. -
18
GPT-4o mini
OpenAI
A small model with superior textual intelligence and multimodal reasoning. GPT-4o mini enables a broad range of tasks with its low cost and latency, such as applications that chain or parallelize multiple model calls (e.g., calling multiple APIs), pass a large volume of context to the model (e.g., full code base or conversation history), or interact with customers through fast, real-time text responses (e.g., customer support chatbots). Today, GPT-4o mini supports text and vision in the API, with support for text, image, video and audio inputs and outputs coming in the future. The model has a context window of 128K tokens, supports up to 16K output tokens per request, and has knowledge up to October 2023. Thanks to the improved tokenizer shared with GPT-4o, handling non-English text is now even more cost effective. -
19
Wikis.ai
Wikis.ai
Wikis.ai is a multi-model AI workspace designed to let users ask one question and compare clear, independent answers from leading AI models side by side. Instead of switching between separate tabs and services, users can send a shared prompt to models such as GPT, Claude, Gemini, DeepSeek, and others, watch each response stream independently, and compare different approaches in a stable grid. It keeps nuance visible rather than flattening multiple perspectives into one anonymous answer, helping users spot where models agree, where they differ, and which claims may need further verification. Consensus can serve as a starting signal for confidence, while disagreement highlights areas worth checking more closely. Wikis.ai also includes an AI Wiki with editorially structured guides across AI fundamentals, models, infrastructure, agents, safety, and other topics.Starting Price: $14.99 per month -
20
PingPrompt
PingPrompt
PingPrompt is a specialized AI prompt management platform that centralizes the storage, editing, version control, testing, and iteration of prompts used with large language models, helping users treat prompts as reusable, improvable assets rather than disposable text buried in chat histories or scattered files. It provides a centralized workspace where every prompt edit is tracked with automated version history and visual diff comparisons, so users can see exactly what changed, when, and why, roll back to earlier versions, and maintain a clear audit trail while refining prompt quality over time. An inline copilot assists with targeted edits without overwriting entire prompts, and a multi-LLM testing playground lets users connect their own API keys to run the same prompt across different models and parameter settings to compare outputs, measure metrics like latency and token usage, and validate improvements before deployment.Starting Price: $8 per month -
21
Steerlab
Steerlab
Steerlab is an AI-driven platform designed to automate and enhance the response process for Requests for Proposals (RFPs) and security questionnaires. By leveraging advanced AI models, Steerlab auto-generates over 80% of responses, ensuring high-quality, factual, and sourced answers without hallucinations. The platform features an auto-managed content library that keeps internal knowledge bases up-to-date, eliminating manual upkeep. Users can track and manage progress, contribute, comment, and collaborate seamlessly, all within a secure environment built to the highest security standards. Steerlab integrates with various tools and offers extensions like a Chrome extension, Slack bot, and more. The platform provides actionable insights, including data-backed win probability and competitor bias detection, to help teams focus on the right opportunities. Steerlab's mission is to transform the RFP and vendor questionnaire response process, enabling businesses to win more deals with AI. -
22
Gemini 3.1 Flash Live
Google
Gemini 3.1 Flash Live is Google’s most advanced real-time audio model, designed to deliver natural, reliable, and low-latency voice interactions for the next generation of conversational AI. It is optimized for real-time dialogue, enabling fluid, human-like conversations with improved precision, faster response times, and a more natural rhythm that better reflects how people actually speak. It enhances tonal understanding, allowing it to recognize nuances such as pitch, pace, and emotional cues, and dynamically adapt responses to user intent, including frustration or confusion. Built for both developers and enterprises, it can be accessed through the Gemini Live API in Google AI Studio, as well as integrated into production environments to power voice-first agents capable of handling complex, multi-step tasks at scale. It supports multimodal inputs including text, audio, images, and video, and produces both text and audio outputs, enabling richer, context-aware interactions. -
23
Llama 4 Scout
Meta
Llama 4 Scout is a powerful 17 billion active parameter multimodal AI model that excels in both text and image processing. With an industry-leading context length of 10 million tokens, it outperforms its predecessors, including Llama 3, in tasks such as multi-document summarization and parsing large codebases. Llama 4 Scout is designed to handle complex reasoning tasks while maintaining high efficiency, making it perfect for use cases requiring long-context comprehension and image grounding. It offers cutting-edge performance in image-related tasks and is particularly well-suited for applications requiring both text and visual understanding.Starting Price: Free -
24
Shieldstral
Mistral AI
Shieldstral is a 3B open-weights, policy-adaptive multimodal safety classifier designed to evaluate text, images, and text-plus-image content using policies defined at inference time. Instead of relying on a fixed taxonomy of harm categories, it frames moderation as a binary question-answering task: users provide an instruction describing the evaluation context and strictness, a yes-or-no safety question, and the content to judge. The model reads the “yes” and “no” logits and converts them into a continuous, calibrated safety score, allowing applications to threshold or rank results by confidence rather than depend on a single discrete label. This formulation unifies prompt classification, response moderation, refusal detection, toxicity detection, and multimodal safety in one interface, while letting teams adapt policies without retraining the model. Shieldstral can evaluate prompts, responses, prompt-response pairs, images, and images with accompanying text. -
25
Whizi
Whizi
Whizi is a multi-model AI chat workspace. It connects to more than 280 language models through a single account, including GPT, Claude, Gemini, Kimi, GLM, DeepSeek, Grok and Qwen. A prompt can be sent to one model or to several at once. When several are selected, the responses appear side by side so they can be compared for reasoning, tone and factual accuracy rather than taken on trust. The active model can also be changed partway through a conversation and the existing context carries across, so a thread can start on a cheaper model and move to a larger one only when the question requires it. Whizi runs in the browser and as native iOS and Android apps, with conversations synced across all three. Pricing is subscription based. Starter is $15.99 per month, Pro is $29.99 and Powerhouse is $49.99, and annual billing lowers the effective monthly rate on each tier.Starting Price: $15.99/month -
26
Gemini 3.1 Flash-Lite
Google
Gemini 3.1 Flash-Lite is Google’s fastest and most cost-efficient model in the Gemini 3 series, designed for high-volume developer workloads. It delivers strong performance at scale while maintaining affordability, with pricing set at $0.25 per million input tokens and $1.50 per million output tokens. The model significantly improves speed, offering a 2.5x faster time to first answer token and a 45% increase in output speed compared to Gemini 2.5 Flash. Despite its lower cost tier, it achieves high benchmark results, including an Elo score of 1432 and strong performance across reasoning and multimodal evaluations. Gemini 3.1 Flash-Lite supports adaptive “thinking levels,” allowing developers to control how much reasoning power is used for different tasks. It is suitable for large-scale applications such as translation, content moderation, user interface generation, and simulation building. -
27
Sonar
Perplexity
Perplexity has recently introduced an enhanced version of its AI search engine, named Sonar. Built upon the Llama 3.3 70B model, Sonar has undergone additional training to improve the factual accuracy and readability of responses in Perplexity's default search mode. This advancement aims to deliver users more precise and comprehensible answers while maintaining the platform's characteristic efficiency and speed. Sonar also provides real-time, web-wide research and Q&A capabilities, allowing developers to integrate these features into their products through a lightweight, cost-effective, and user-friendly API. The Sonar API supports advanced models like sonar-reasoning-pro and sonar-pro, designed for complex tasks requiring deep understanding and context retention. These models offer detailed answers with an average of twice as many citations as previous versions, enhancing the transparency and reliability of the information provided.Starting Price: Free -
28
Grok 4.1 Thinking
SpaceXAI
Grok 4.1 Thinking is xAI’s advanced reasoning-focused AI model designed for deeper analysis, reflection, and structured problem-solving. It uses explicit thinking tokens to reason through complex prompts before delivering a response, resulting in more accurate and context-aware outputs. The model excels in tasks that require multi-step logic, nuanced understanding, and thoughtful explanations. Grok 4.1 Thinking demonstrates a strong, coherent personality while maintaining analytical rigor and reliability. It has achieved the top overall ranking on the LMArena Text Leaderboard, reflecting strong human preference in blind evaluations. The model also shows leading performance in emotional intelligence and creative reasoning benchmarks. Grok 4.1 Thinking is built for users who value clarity, depth, and defensible reasoning in AI interactions. -
29
GPT-5.4
OpenAI
GPT-5.4 is an advanced artificial intelligence model developed by OpenAI to support complex professional and technical work. The model combines improvements in reasoning, coding, and agent-based workflows into a single system designed for real-world productivity tasks. GPT-5.4 can generate, analyze, and edit documents, spreadsheets, presentations, and other work outputs with greater accuracy and efficiency. It also features improved tool integration, enabling the model to interact with software environments and external tools to complete multi-step workflows. With enhanced context capabilities supporting up to one million tokens, GPT-5.4 can process and reason over very large amounts of information. The model also improves factual accuracy and reduces errors compared to earlier versions. By combining strong reasoning, coding ability, and tool use, GPT-5.4 helps users complete complex tasks faster and with fewer iterations. -
30
IONOS Cloud AI Model Hub
IONOS
IONOS AI Model Hub is a fully managed cloud platform designed to simplify the integration and deployment of advanced artificial intelligence models within applications and digital services. It provides access to powerful open-source foundation models that can generate text, create images, and support conversational question-and-answer systems through a unified API. It enables developers to build AI-driven applications without needing to manage the underlying infrastructure or specialized hardware required to run large machine learning models. It incorporates technologies such as vector databases and Retrieval-Augmented Generation (RAG), which allow applications to retrieve relevant information from data sources and combine it with generative AI responses to produce more accurate and contextual outputs.Starting Price: $0.17 per 1M tokens -
31
Humiris AI
Humiris AI
Humiris AI is a next-generation AI infrastructure platform that enables developers to build advanced applications by integrating multiple Large Language Models (LLMs). It offers a multi-LLM routing and reasoning layer, allowing users to optimize generative AI workflows with a flexible, scalable infrastructure. Humiris AI supports various use cases, including chatbot development, fine-tuning multiple LLMs simultaneously, retrieval-augmented generation, building super reasoning agents, advanced data analysis, and code generation. The platform's unique data format adapts to all foundation models, facilitating seamless integration and optimization. To get started, users can register for an account, create a project, add LLM provider API keys, and define parameters to generate a mixed model tailored to their specific needs. It allows deployment on users' own infrastructure, ensuring full data sovereignty and compliance with internal and external regulations. -
32
Seed1.8
ByteDance
Seed1.8 is ByteDance’s latest generalized agentic AI model designed to bridge understanding and real-world action by combining multimodal perception, agent-like task execution, and wide-ranging reasoning capabilities into a single foundation model that goes beyond simple language generation. It supports multimodal inputs, including text, images, and video, processes very large context windows (hundreds of thousands of tokens at once), and is optimized to handle complex workflows in real environments, such as information retrieval, code generation, GUI interaction, and multi-step decision logic, with efficient, accurate responses suitable for real-world applications. Seed1.8 unifies skills such as search, code understanding, visual context interpretation, and autonomous reasoning so developers and AI systems can build interactive agents and next-generation workflows capable of synthesizing evidence, following instructions deeply, and acting on tasks like automation. -
33
eRAG
GigaSpaces
GigaSpaces eRAG (Enterprise Retrieval Augmented Generation) is an AI-powered platform designed to enhance enterprise decision-making by enabling natural language interactions with structured data sources such as relational databases. Unlike traditional generative AI models that may produce inaccurate or "hallucinated" responses when dealing with structured data, eRAG employs deep semantic reasoning to accurately translate user queries into SQL, retrieve relevant data, and generate precise, context-aware answers. This approach ensures that responses are grounded in real-time, authoritative data, mitigating the risks associated with unverified AI outputs. eRAG seamlessly integrates with various data sources, allowing organizations to unlock the full potential of their existing data infrastructure. eRAG offers built-in governance features that monitor interactions to ensure compliance with regulations. -
34
OpenAI Output Detector
Hugging Face
This is an online demo of the GPT-2 output detector model, based on the 🤗/Transformers implementation of RoBERTa. Enter some text in the text box; the predicted probabilities will be displayed below. The results start to get reliable after around 50 tokens.Starting Price: Free -
35
Talkory.ai
Talkory.ai
Talkory.ai helps users stop tab-switching between AI tools by sending one question to five models at once and turning the results into one answer they can trust. From a single prompt, Talkory sends the query to GPT, Claude, Gemini, Perplexity Sonar, and Grok simultaneously, then shows where the models agree, where they differ, and which response performed best. Instead of manually copying the same question into different tools and synthesizing the answers by hand, users get all five responses side by side in seconds, ranked by quality, completeness, and clarity. Talkory generates a Consensus Answer, which combines and ranks all LLM responses into one authoritative, high-confidence result, and a Common Answer, which highlights the specific points and ideas that appeared consistently across all models. Its Recursive Correction feature asks each model to review, correct, and refine its own first response, producing a sharper second round automatically.Starting Price: $5 per month -
36
GPT-5 mini
OpenAI
GPT-5 mini is a streamlined, faster, and more affordable variant of OpenAI’s GPT-5, optimized for well-defined tasks and precise prompts. It supports text and image inputs and delivers high-quality text outputs with a 400,000-token context window and up to 128,000 output tokens. This model excels at rapid response times, making it suitable for applications requiring fast, accurate language understanding without the full overhead of GPT-5. Pricing is cost-effective, with input tokens at $0.25 per million and output tokens at $2 per million, providing savings over the flagship model. GPT-5 mini supports advanced features like streaming, function calling, structured outputs, and fine-tuning, but does not support audio input or image generation. It integrates well with various API endpoints including chat completions, responses, and embeddings, making it versatile for many AI-powered tasks.Starting Price: $0.25 per 1M tokens -
37
UpTrain
UpTrain
Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users. -
38
Featherless
Featherless
Featherless is an AI model provider that offers our subscribers access to a continually expanding library of Hugging Face models. With hundreds of new models daily, you need dedicated tools to keep up with the hype. No matter your use case, find and use the state-of-the-art AI model with Featherless. At present, we support LLaMA-3-based models, including LLaMA-3 and QWEN-2. Note that QWEN-2 models are only supported up to 16,000 context length. We plan to add more architectures to our supported list soon. We continuously onboard new models as they become available on Hugging Face. As we grow, we aim to automate this process to encompass all publicly available Hugging Face models with compatible architecture. To ensure fair individual account use, concurrent requests are limited according to the plan you've selected. Output is delivered at a speed of 10-40 tokens per second, depending on the model and prompt size.Starting Price: $10 per month -
39
GPT-4 Turbo
OpenAI
GPT-4 is a large multimodal model (accepting text or image inputs and outputting text) that can solve difficult problems with greater accuracy than any of our previous models, thanks to its broader general knowledge and advanced reasoning capabilities. GPT-4 is available in the OpenAI API to paying customers. Like gpt-3.5-turbo, GPT-4 is optimized for chat but works well for traditional completions tasks using the Chat Completions API. GPT-4 is the latest GPT-4 model with improved instruction following, JSON mode, reproducible outputs, parallel function calling, and more. Returns a maximum of 4,096 output tokens. This preview model is not yet suited for production traffic.Starting Price: $0.0200 per 1000 tokens -
40
Aymo AI
Pimjo
Aymo AI is an all-in-one AI platform that gives teams and individuals access to 45+ leading AI models in a single workspace. Users can access GPT-5.5, Claude, Gemini, DeepSeek, Grok, Perplexity, Qwen, Llama, Mistral, and other models without managing multiple subscriptions or switching between tools. The platform helps users choose the best AI model for each task through instant model switching and side-by-side response comparison. Aymo AI supports content creation, software development, research, document analysis, image understanding, and web-powered AI workflows. Key features include multi-model chat, AI model comparison, file uploads, document analysis, image analysis, web search, shared workspaces, team collaboration, and Bring Your Own Key (BYOK) support. Teams can organize projects, share conversations, collaborate in real time, and work from a centralized AI workspace.Starting Price: $4/month/user -
41
Cerebro
AiFA Labs
Cerebro is a cutting-edge generative AI platform designed for enterprises. This versatile multi-model platform enables users to create, manage, and deploy generative AI applications 10x faster. With Cerebro, ensure responsible AI development through meticulous governance and adherence to applicable regulations. Empower your organization to innovate and thrive in the AI era. Key Features: Multi-model support Accelerated development and deployment Robust governance and compliance Scalable and adaptable architecture -
42
LLMetrics
LLMetrics
LLMetrics is LLM cost tracking software for teams shipping AI products, bringing model spend, token usage, feature attribution, and usage alerts into one live dashboard. It supports more than 100 models across OpenAI, Anthropic, Google Gemini, Mistral, Cohere, Together AI, Groq, and other providers, with pricing data synchronized daily. Teams tag each model call with a feature name, provider, model, input tokens, and output tokens, allowing them to see exactly whether a chatbot, summarizer, search feature, lesson generator, or other workflow is driving spend. Real-time updates and daily trend charts reveal how costs change after releases, prompt edits, traffic growth, or model swaps. Spend thresholds and spike-detection rules can alert teams through email or Slack when usage patterns look wrong, helping them catch runaway loops and unexpected cost increases before the provider invoice arrives.Starting Price: $49 per month -
43
LLM Scout
LLM Scout
LLM Scout is an evaluation and analysis platform designed to help users benchmark, compare, and interpret the performance of large language models across diverse tasks, datasets, and real-world prompts within a unified environment. It enables side-by-side comparisons of models by measuring accuracy, reasoning, factuality, bias, safety, and other key metrics using customizable evaluation suites, curated benchmarks, and domain-specific tests. It supports the ingestion of user-provided data and queries so teams can assess how different models respond to their own real-world workflows or industry-specific needs, and visualize outputs in an intuitive dashboard that highlights performance trends, strengths, and weaknesses. LLM Scout also includes tools for analyzing token usage, latency, cost implications, and model behavior under varied conditions, helping stakeholders make informed decisions about which models best fit specific applications or quality requirements.Starting Price: $39.99 per month -
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Patronus AI
Patronus AI
Patronus AI is an automated AI evaluation, security, and optimization platform for LLM applications and agentic systems. It helps teams confidently deploy AI products at scale by generating test suites, running experiments, logging traces, comparing outputs, monitoring production interactions, and evaluating model performance in real time. It provides industry-leading evaluators for RAG hallucinations, context quality, image relevance, answer correctness, prompt injection, sensitive data leakage, toxicity, bias, and other safety or reliability risks. Patronus Evaluators can score AI outputs on specific dimensions, and teams can also create custom evaluators for use-case-specific criteria. Its platform combines dashboards, APIs, plug-and-play evaluations, logs, traces, side-by-side comparisons, visualizations, analytics, and real-time alerts to help teams detect mistakes, benchmark models, improve prompts, and understand system behavior over time. -
45
Ling 3.0 Tiny
Ant Group
Ling 3.0 Tiny is an open-weights reasoning model with 7.9B total parameters, 1.3B active parameters, and a 262K-token context window. Built with a mixture-of-experts architecture, it extends the open-weights Pareto frontier for intelligence versus active parameters and is small enough to run locally in many settings. The model scores 25 on the Artificial Analysis Intelligence Index, comparable to gpt-oss-120b (high, 24) while using 15x fewer total parameters and 4x fewer active parameters. This parameter efficiency comes with relatively high token usage, with 213M output tokens required to run the Intelligence Index. Ling 3.0 Tiny also shows substantial improvements in hallucination behavior over Ling-mini-2.0, improving its AA-Omniscience score by 59 points while maintaining similar accuracy. Rather than guessing when uncertain, it attempted only 37% of questions in the evaluation, resulting in a 30% hallucination rate compared with 96% for the previous generation. -
46
Sarvam 105B
Sarvam
Sarvam-105B is the flagship large language model in Sarvam’s open source model family, designed to deliver high-performance reasoning, multilingual understanding, and agent-based execution within a single scalable system. Built as a Mixture-of-Experts (MoE) model with approximately 105 billion total parameters, of which only a fraction are activated per token, it achieves strong computational efficiency while maintaining high capability across complex tasks. The model is optimized for advanced reasoning, coding, mathematics, and agentic workflows, making it suitable for tasks that require multi-step problem solving and structured outputs rather than simple conversational responses. Sarvam-105B supports long-context processing of up to around 128K tokens, enabling it to handle large documents, extended conversations, and deep analytical queries without losing coherence.Starting Price: Free -
47
PromptUnit
PromptUnit
PromptUnit is an AI inference proxy that reduces AI costs automatically by sitting between an app and its AI providers with no code changes required. Teams swap the base URL, keep the same SDK, endpoints, response parsing, and error handling, then PromptUnit handles routing, failover, cost tracking, and quality validation. It logs every API call by model, feature, user segment, token count, latency, and cost, giving real-time visibility into where AI spend is going before any routing changes go live. In observation mode, PromptUnit watches traffic, shadow-classifies requests, forecasts savings, and explains routing decisions so teams can see exact savings before enabling live routing. Once enabled, Smart Routing uses task classification to route each request to the cheapest model that clears the configured quality bar. PromptUnit also includes prompt compression, token inflation defense, prompt efficiency scoring, semantic request caching, and multi-model consensus. -
48
GPT-5
OpenAI
GPT-5 is OpenAI’s most advanced AI model, delivering smarter, faster, and more useful responses across a wide range of topics including math, science, finance, and law. It features built-in thinking capabilities that allow it to provide expert-level answers and perform complex reasoning. GPT-5 can handle long context lengths and generate detailed outputs, making it ideal for coding, research, and creative writing. The model includes a ‘verbosity’ parameter for customizable response length and improved personality control. It integrates with business tools like Google Drive and SharePoint to provide context-aware answers while respecting security permissions. Available to everyone, GPT-5 empowers users to collaborate with an AI assistant that feels like a knowledgeable colleague.Starting Price: $1.25 per 1M tokens -
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Leni
Leni
Leni is an AI-powered work platform built for real estate, private equity, and investment professionals who need accurate, verifiable outputs for complex financial and operational tasks. The platform connects with industry systems such as Yardi, Entrata, ResMan, RealPage, and AppFolio to provide context-aware assistance across underwriting, asset management, reporting, market research, and document analysis. Leni uses a multi-agent architecture with built-in verification processes to reduce hallucinations and improve the reliability of AI-generated work. Its model-agnostic design allows organizations to leverage multiple large language models while maintaining security, institutional knowledge, and workflow consistency. The platform also creates a private organizational context graph that captures decisions and insights over time to strengthen future analysis. -
50
Oridica
Oridica
Ordica is an AI infrastructure layer designed to reduce the cost of using large language models by compressing prompts before they are sent to providers like GPT-4o, Claude, Gemini, or Grok. It operates as a lightweight proxy that sits directly in the request path, requiring no new dependencies. Users simply point their existing SDK to Ordica’s endpoint and continue using their current API keys unchanged. It processes prompts entirely in memory, compressing them in transit and forwarding them to the selected provider without storing, logging, or retaining any message content, ensuring that data privacy is preserved at every step. Ordica dynamically decides whether to compress a request based on confidence thresholds; if compression is expected to preserve output quality, it reduces token usage; if not, the request passes through unchanged, guaranteeing no degradation in responses. This approach allows developers to achieve measurable cost savings across different workloads.Starting Price: Free
