Best AI Inference Platforms - Page 2

Compare the Top AI Inference Platforms as of November 2026 - Page 2

  • 1
    Fireworks AI

    Fireworks AI

    Fireworks AI

    Fireworks partners with the world's leading generative AI researchers to serve the best models, at the fastest speeds. Independently benchmarked to have the top speed of all inference providers. Use powerful models curated by Fireworks or our in-house trained multi-modal and function-calling models. Fireworks is the 2nd most used open-source model provider and also generates over 1M images/day. Our OpenAI-compatible API makes it easy to start building with Fireworks. Get dedicated deployments for your models to ensure uptime and speed. Fireworks is proudly compliant with HIPAA and SOC2 and offers secure VPC and VPN connectivity. Meet your needs with data privacy - own your data and your models. Serverless models are hosted by Fireworks, there's no need to configure hardware or deploy models. Fireworks.ai is a lightning-fast inference platform that helps you serve generative AI models.
    Starting Price: $0.20 per 1M tokens
  • 2
    Lamini

    Lamini

    Lamini

    Lamini makes it possible for enterprises to turn proprietary data into the next generation of LLM capabilities, by offering a platform for in-house software teams to uplevel to OpenAI-level AI teams and to build within the security of their existing infrastructure. Guaranteed structured output with optimized JSON decoding. Photographic memory through retrieval-augmented fine-tuning. Improve accuracy, and dramatically reduce hallucinations. Highly parallelized inference for large batch inference. Parameter-efficient finetuning that scales to millions of production adapters. Lamini is the only company that enables enterprise companies to safely and quickly develop and control their own LLMs anywhere. It brings several of the latest technologies and research to bear that was able to make ChatGPT from GPT-3, as well as Github Copilot from Codex. These include, among others, fine-tuning, RLHF, retrieval-augmented training, data augmentation, and GPU optimization.
    Starting Price: $99 per month
  • 3
    Msty

    Msty

    Msty

    Chat with any AI model in a single click. No prior model setup experience is needed. Msty is designed to function seamlessly offline, ensuring reliability and privacy. For added flexibility, it also supports popular online model vendors, giving you the best of both worlds. Revolutionize your research with split chats. Compare and contrast multiple AI models' responses in real time, streamlining your workflow and uncovering new insights. Msty puts you in the driver's seat. Take your conversations wherever you want, and stop whenever you're satisfied. Replace an existing answer or create and iterate through several conversation branches. Delete branches that don't sound quite right. With delve mode, every response becomes a gateway to new knowledge, waiting to be discovered. Click on a keyword, and embark on a journey of discovery. Leverage Msty's split chat feature to move your desired conversation branches into a new split chat or a new chat session.
    Starting Price: $50 per year
  • 4
    VESSL AI

    VESSL AI

    VESSL AI

    Build, train, and deploy models faster at scale with fully managed infrastructure, tools, and workflows. Deploy custom AI & LLMs on any infrastructure in seconds and scale inference with ease. Handle your most demanding tasks with batch job scheduling, only paying with per-second billing. Optimize costs with GPU usage, spot instances, and built-in automatic failover. Train with a single command with YAML, simplifying complex infrastructure setups. Automatically scale up workers during high traffic and scale down to zero during inactivity. Deploy cutting-edge models with persistent endpoints in a serverless environment, optimizing resource usage. Monitor system and inference metrics in real-time, including worker count, GPU utilization, latency, and throughput. Efficiently conduct A/B testing by splitting traffic among multiple models for evaluation.
    Starting Price: $100 + compute/month
  • 5
    Inferable

    Inferable

    Inferable

    Create your first AI automation in 60 seconds. Inferable seamlessly integrates with your existing codebase and infrastructure, allowing you to create powerful AI automation without compromising on control or security. Works with your existing codebase. Integrates with your existing services via opt-in. Enforce determinism through source code. Create and manage automation programmatically. You own the computer, in your own infrastructure. Inferable comes out of the box with delightful DX to kickstart your AI automation journey. We bring the best in class vertically integrated LLM orchestration. You bring your product and domain expertise. At the core of Inferable is a distributed message queue that ensures your AI automation is scalable and reliable. It makes sure your automations are executed correctly, and that failures are handled gracefully. Decorate your existing functions, REST APIs, and GraphQL endpoints with decorators to require human approval.
    Starting Price: $0.006 per KB
  • 6
    WebLLM

    WebLLM

    WebLLM

    WebLLM is a high-performance, in-browser language model inference engine that leverages WebGPU for hardware acceleration, enabling powerful LLM operations directly within web browsers without server-side processing. It offers full OpenAI API compatibility, allowing seamless integration with functionalities such as JSON mode, function-calling, and streaming. WebLLM natively supports a range of models, including Llama, Phi, Gemma, RedPajama, Mistral, and Qwen, making it versatile for various AI tasks. Users can easily integrate and deploy custom models in MLC format, adapting WebLLM to specific needs and scenarios. The platform facilitates plug-and-play integration through package managers like NPM and Yarn, or directly via CDN, complemented by comprehensive examples and a modular design for connecting with UI components. It supports streaming chat completions for real-time output generation, enhancing interactive applications like chatbots and virtual assistants.
    Starting Price: Free
  • 7
    NVIDIA TensorRT
    NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.
    Starting Price: Free
  • 8
    E2B

    E2B

    E2B

    E2B is an open source runtime designed to securely execute AI-generated code within isolated cloud sandboxes. It enables developers to integrate code interpretation capabilities into their AI applications and agents, facilitating the execution of dynamic code snippets in a controlled environment. The platform supports multiple programming languages, including Python and JavaScript, and offers SDKs for seamless integration. E2B utilizes Firecracker microVMs to ensure robust security and isolation for code execution. Developers can deploy E2B within their own infrastructure or utilize the provided cloud service. The platform is designed to be LLM-agnostic, allowing compatibility with various large language models such as OpenAI, Llama, Anthropic, and Mistral. E2B's features include rapid sandbox initialization, customizable execution environments, and support for long-running sessions up to 24 hours.
    Starting Price: Free
  • 9
    Pruna AI

    Pruna AI

    Pruna AI

    Pruna uses generative AI to enable companies to produce professional-grade visual content quickly and affordably. By eliminating the traditional need for studios and manual editing, it empowers brands to create consistent, customized images for advertising, product displays, and digital campaigns with minimal effort.
    Starting Price: $0.40 per runtime hour
  • 10
    LangDB

    LangDB

    LangDB

    LangDB offers a community-driven, open-access repository focused on natural language processing tasks and datasets for multiple languages. It serves as a central resource for tracking benchmarks, sharing tools, and supporting the development of multilingual AI models with an emphasis on openness and cross-linguistic representation.
    Starting Price: $49 per month
  • 11
    FriendliAI

    FriendliAI

    FriendliAI

    FriendliAI is a generative AI infrastructure platform that offers fast, efficient, and reliable inference solutions for production environments. It provides a suite of tools and services designed to optimize the deployment and serving of large language models (LLMs) and other generative AI workloads at scale. Key offerings include Friendli Endpoints, which allow users to build and serve custom generative AI models, saving GPU costs and accelerating AI inference. It supports seamless integration with popular open source models from the Hugging Face Hub, enabling lightning-fast, high-performance inference. FriendliAI's cutting-edge technologies, such as Iteration Batching, Friendli DNN Library, Friendli TCache, and Native Quantization, contribute to significant cost savings (50–90%), reduced GPU requirements (6× fewer GPUs), higher throughput (10.7×), and lower latency (6.2×).
    Starting Price: $5.9 per hour
  • 12
    kluster.ai

    kluster.ai

    kluster.ai

    Kluster.ai is a developer-centric AI cloud platform designed to deploy, scale, and fine-tune large language models (LLMs) with speed and efficiency. Built for developers by developers, it offers Adaptive Inference, a flexible and scalable service that adjusts seamlessly to workload demands, ensuring high-performance processing and consistent turnaround times. Adaptive Inference provides three distinct processing options: real-time inference for ultra-low latency needs, asynchronous inference for cost-effective handling of flexible timing tasks, and batch inference for efficient processing of high-volume, bulk tasks. It supports a range of open-weight, cutting-edge multimodal models for chat, vision, code, and more, including Meta's Llama 4 Maverick and Scout, Qwen3-235B-A22B, DeepSeek-R1, and Gemma 3 . Kluster.ai's OpenAI-compatible API allows developers to integrate these models into their applications seamlessly.
    Starting Price: $0.15per input
  • 13
    SiliconFlow

    SiliconFlow

    SiliconFlow

    SiliconFlow is a high-performance, developer-focused AI infrastructure platform offering a unified and scalable solution for running, fine-tuning, and deploying both language and multimodal models. It provides fast, reliable inference across open source and commercial models, thanks to blazing speed, low latency, and high throughput, with flexible options such as serverless endpoints, dedicated compute, or private cloud deployments. Platform capabilities include one-stop inference, fine-tuning pipelines, and reserved GPU access, all delivered via an OpenAI-compatible API and complete with built-in observability, monitoring, and cost-efficient smart scaling. For diffusion-based tasks, SiliconFlow offers the open source OneDiff acceleration library, while its BizyAir runtime supports scalable multimodal workloads. Designed for enterprise-grade stability, it includes features like BYOC (Bring Your Own Cloud), robust security, and real-time metrics.
    Starting Price: $0.04 per image
  • 14
    LEAP

    LEAP

    Liquid AI

    The LEAP Edge AI Platform offers a full-stack on-device AI toolchain that enables developers to build edge AI applications, from model selection through inference, entirely on device. It includes a best-model search engine to find the most appropriate model for a given task and device constraint, a curated library of pre-trained model bundles ready for download, and fine-tuning tools (such as GPU-optimized scripts) for customizing models like LFM2 to specific use cases. It supports vision-enabled capabilities across iOS, Android, and laptop devices, and includes function-calling so AI models can interact with external systems via structured outputs. For deployment, LEAP provides an Edge SDK that lets developers load and query models locally, just like a cloud API, but entirely offline, and a model bundling service to package any supported model or checkpoint into a bundle optimized for edge deployment.
    Starting Price: Free
  • 15
    Nebius Token Factory
    Nebius Token Factory is a scalable AI inference platform designed to run open-source and custom AI models in production without manual infrastructure management. It offers enterprise-ready inference endpoints with predictable performance, autoscaling throughput, and sub-second latency — even at very high request volumes. It delivers 99.9% uptime availability and supports unlimited or tailored traffic profiles based on workload needs, simplifying the transition from experimentation to global deployment. Nebius Token Factory supports a broad set of open source models such as Llama, Qwen, DeepSeek, GPT-OSS, Flux, and many others, and lets teams host and fine-tune models through an API or dashboard. Users can upload LoRA adapters or full fine-tuned variants directly, with the same enterprise performance guarantees applied to custom models.
    Starting Price: $0.02
  • 16
    Photon

    Photon

    Moondream

    Photon is Moondream’s official high-performance inference engine, designed to run vision-language models efficiently across cloud, desktop, and edge environments while delivering real-time performance for production AI systems. It is built as a custom inference layer tightly integrated with the Moondream model architecture, using optimized scheduling, native image processing, and purpose-built CUDA kernels to maximize speed and efficiency. This co-designed approach allows Photon to significantly reduce latency compared to traditional VLM setups, enabling responsive interactions on edge devices and real-time throughput on server-grade hardware. It supports deployment across a wide range of NVIDIA GPUs, from embedded systems like Jetson devices to high-end multi-GPU servers, making it adaptable for diverse operational needs. It includes production-ready features such as automatic batching, prefix caching, and memory-efficient attention mechanisms.
    Starting Price: $300 per month
  • 17
    Oxlo.ai

    Oxlo.ai

    Oxlo.ai

    Oxlo.ai is a privacy-first inference stack for agents, built to run frontier-class open-source models with unlimited agentic tool calls, secure failover, and zero data retention or training. It gives developers request-based access to curated open models through a unified HTTP API designed for predictable usage, low-latency inference, and clean integration into production systems. Teams can call models through OpenAI-compatible endpoints, switch from another provider by changing the base URL and API key, and keep support for streaming, function calling, JSON mode, vision models, embeddings, and image generation. Oxlo.ai supports more than 40 models across text, chat, reasoning, coding, image generation, audio, embeddings, computer vision, vision-language, speech-to-text, text-to-speech, long-context, and detection workflows.
    Starting Price: $80 per month
  • 18
    Wafer

    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
  • 19
    Canopy Wave

    Canopy Wave

    Canopy Wave

    Canopy Wave is the best inference platform for open models, built to deliver high-quality, reliable, and secure AI services from infrastructure to build, tune, and scale AI models. Its model platform gives users instant access to advanced open source models optimized for quality, speed, and security through API, with a model library covering different types and fields, so users can call models directly without additional development or adaptation. Canopy Wave’s serverless inference service lets teams run pretrained models through simple API calls without managing infrastructure, with fast response, low latency, no cold start issues, and globally optimized performance powered by next-generation GPUs and edge caching. For production workloads that need stronger control, dedicated endpoints run inference at scale with exceptional speed and reliability on hardware instances dedicated exclusively to the user.
    Starting Price: $0.07 per GB per month
  • 20
    ExecuTorch

    ExecuTorch

    ExecuTorch

    ExecuTorch is PyTorch’s open source framework for deploying AI/ML models directly to edge devices, enabling text, vision, speech, recommendation, and multimodal inference without requiring the cloud. It exports models from PyTorch without intermediate conversion formats, preserves ATen operators, and uses ahead-of-time compilation to optimize performance for target hardware before deployment. Its modular design lets developers choose compile-time and runtime optimizations while staying inside the familiar PyTorch ecosystem, including torchao for quantization. A portable C++ runtime with a base footprint of about 50 KB can run on smartphones, desktops, embedded systems, microcontrollers, DSPs, and Cortex-M processors. ExecuTorch supports Android, iOS, Linux, Windows, macOS, and WebAssembly, with native APIs for C++, Swift, Kotlin, and Objective-C.
    Starting Price: Free
  • 21
    Confidential AI

    Confidential AI

    Confidential AI

    Confidential AI provides private inference, private agents, confidential VMs and confidential computing infrastructure for AI labs, inference providers, routers, and organizations handling sensitive workloads. Its hosted inference service runs open-weight models in hardware-backed trusted execution environments (TEEs), including Intel TDX and AMD SEV-SNP confidential VMs with NVIDIA GPUs in confidential computing mode. Prompts, responses, and workload data are protected from infrastructure operators, and clients can verify attestation before sending sensitive input. Customers can use an OpenAI-compatible API to deploy inference endpoints and agent workloads, or license the confidential-computing stack for on-premises infrastructure, bare metal, and major clouds. Use cases include serving models while limiting operator access to prompts and model assets, and running sensitive AI workloads on dedicated confidential compute.
    Starting Price: $0.30 per 1M input tokens
  • 22
    Experiential

    Experiential

    Experiential Labs

    Experiential is an AI model gateway and inference platform for software developers and organizations building AI-enabled products or internal applications. It provides a unified API for routing requests to hosted model providers, customer-supplied provider accounts, and self-hosted or custom models, with OpenAI-compatible and Anthropic API access. Teams can manage API keys, budgets and usage limits, attribute costs to keys or agents, monitor requests, and configure provider routing and fallback behavior. The hosted service includes a free plan and paid monthly plans, while the open-source gateway can also be self-hosted. Enterprise plans add organization controls and data-residency options; paid plans also include model-optimization features, and enterprise customers can commission a model trained on their traffic. Developers can connect compatible applications and coding agents by changing their API endpoint and credentials.
    Starting Price: $0/month
  • 23
    LunaRoute

    LunaRoute

    LunaRoute

    LunaRoute is a hosted AI inference gateway and API for developers and teams running coding agents, personal agents, applications, and automations. It routes requests to a curated catalog of open-weight models through OpenAI-compatible and Anthropic-compatible endpoints, with a command-line client and setup guides for connecting coding tools and agent frameworks. Plans provide priority concurrent inference capacity, overflow handling, model access, API keys, usage reporting, and team controls depending on the plan. An optional hosted MCP server provides web search, document conversion with OCR, and image generation and editing. Enterprise offerings add dedicated deployment options, custom routing, and policy controls. LunaRoute is intended for software developers and engineering teams seeking a managed way to connect existing AI clients to model inference.
    Starting Price: $19.99/month
  • 24
    DeepCube

    DeepCube

    DeepCube

    DeepCube focuses on the research and development of deep learning technologies that result in improved real-world deployment of AI systems. The company’s numerous patented innovations include methods for faster and more accurate training of deep learning models and drastically improved inference performance. DeepCube’s proprietary framework can be deployed on top of any existing hardware in both datacenters and edge devices, resulting in over 10x speed improvement and memory reduction. DeepCube provides the only technology that allows efficient deployment of deep learning models on intelligent edge devices. After the deep learning training phase, the resulting model typically requires huge amounts of processing and consumes lots of memory. Due to the significant amount of memory and processing requirements, today’s deep learning deployments are limited mostly to the cloud.
  • 25
    NetApp AIPod
    NetApp AIPod is a comprehensive AI infrastructure solution designed to streamline the deployment and management of artificial intelligence workloads. By integrating NVIDIA-validated turnkey solutions, such as NVIDIA DGX BasePOD™ and NetApp's cloud-connected all-flash storage, AIPod consolidates analytics, training, and inference capabilities into a single, scalable system. This convergence enables organizations to rapidly implement AI workflows, from model training to fine-tuning and inference, while ensuring robust data management and security. With preconfigured infrastructure optimized for AI tasks, NetApp AIPod reduces complexity, accelerates time to insights, and supports seamless integration into hybrid cloud environments.
  • 26
    DeePhi Quantization Tool

    DeePhi Quantization Tool

    DeePhi Quantization Tool

    This is a model quantization tool for convolution neural networks(CNN). This tool could quantize both weights/biases and activations from 32-bit floating-point (FP32) format to 8-bit integer(INT8) format or any other bit depths. With this tool, you can boost the inference performance and efficiency significantly, while maintaining the accuracy. This tool supports common layer types in neural networks, including convolution, pooling, fully-connected, batch normalization and so on. The quantization tool does not need the retraining of the network or labeled datasets, only one batch of pictures are needed. The process time ranges from a few seconds to several minutes depending on the size of neural network, which makes rapid model update possible. This tool is collaborative optimized for DeePhi DPU and could generate INT8 format model files required by DNNC.
    Starting Price: $0.90 per hour
  • 27
    Phala

    Phala

    Phala

    Phala is a hardware-secured cloud platform designed to help organizations deploy confidential AI with verifiable trust and enterprise-grade privacy. Using Trusted Execution Environments (TEEs), Phala ensures that AI models, data, and computations run inside fully isolated, encrypted environments that even cloud providers cannot access. The platform includes pre-configured confidential AI models, confidential VMs, and GPU TEE support for NVIDIA H100, H200, and B200 hardware, delivering near-native performance with complete privacy. With Phala Cloud, developers can build, containerize, and deploy encrypted AI applications in minutes while relying on automated attestations and strong compliance guarantees. Phala powers sensitive workloads across finance, healthcare, AI SaaS, decentralized AI, and other privacy-critical industries. Trusted by thousands of developers and enterprise customers, Phala enables businesses to build AI that users can trust.
    Starting Price: $50.37/month
  • 28
    Seldon

    Seldon

    Seldon Technologies

    Deploy machine learning models at scale with more accuracy. Turn R&D into ROI with more models into production at scale, faster, with increased accuracy. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Deploy reduces the time to production by providing production grade inference servers optimized for popular ML framework or custom language wrappers to fit your use cases. Seldon Core Enterprise provides access to cutting-edge, globally tested and trusted open source MLOps software with the reassurance of enterprise-level support. Seldon Core Enterprise is for organizations requiring: - Coverage across any number of ML models deployed plus unlimited users - Additional assurances for models in staging and production - Confidence that their ML model deployments are supported and protected.
  • 29
    Google Cloud Inference API
    Time-series analysis is essential for the day-to-day operation of many companies. Most popular use cases include analyzing foot traffic and conversion for retailers, detecting data anomalies, identifying correlations in real-time over sensor data, or generating high-quality recommendations. With Cloud Inference API Alpha, you can gather insights in real-time from your typed time-series datasets. Get everything you need to understand your API queries results, such as groups of events that were examined, the number of groups of events, and the background probability of each returned event. Stream data in real-time, making it possible to compute correlations for real-time events. Rely on Google Cloud’s end-to-end infrastructure and defense-in-depth approach to security that’s been innovated on for over 15 years through consumer apps. At its core, Cloud Inference API is fully integrated with other Google Cloud Storage services.
  • 30
    Google Cloud AI Infrastructure
    Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. A range of NVIDIA GPUs to help with cost-effective inference or scale-up or scale-out training. Leverage RAPID and Spark with GPUs to execute deep learning. Run GPU workloads on Google Cloud where you have access to industry-leading storage, networking, and data analytics technologies. Access CPU platforms when you start a VM instance on Compute Engine. Compute Engine offers a range of both Intel and AMD processors for your VMs.