Best AI Inference Platforms for Visual Studio Code
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Compare the Top AI Inference Platforms that integrate with Visual Studio Code as of October 2026
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This a list of AI Inference platforms that integrate with Visual Studio Code. Use the filters on the left to add additional filters for products that have integrations with Visual Studio Code. View the products that work with Visual Studio Code in the table below.
What are AI Inference Platforms for Visual Studio Code?
AI inference platforms enable the deployment, optimization, and real-time execution of machine learning models in production environments. These platforms streamline the process of converting trained models into actionable insights by providing scalable, low-latency inference services. They support multiple frameworks, hardware accelerators (like GPUs, TPUs, and specialized AI chips), and offer features such as batch processing and model versioning. Many platforms also prioritize cost-efficiency, energy savings, and simplified API integrations for seamless model deployment. By leveraging AI inference platforms, organizations can accelerate AI-driven decision-making in applications like computer vision, natural language processing, and predictive analytics. Compare and read user reviews of the best AI Inference platforms for Visual Studio Code currently available using the table below. This list is updated regularly.
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1
LM-Kit.NET
LM-Kit
LM-Kit.NET brings advanced AI to C# and VB.NET by letting you create and deploy context-aware agents that run small language models directly on edge devices, trimming latency, protecting data, and delivering real-time performance even in resource-constrained environments so both enterprise systems and rapid prototypes can ship faster, smarter, and more reliable applications.Starting Price: Free (Community) or $1000/year -
2
Anaconda
Anaconda
Inference costs grow fast once AI reaches production. Anaconda helps teams match each workload to the right model and infrastructure. Builders choose from 500+ open and closed models through Kilo by Anaconda, and routing sends each task to an approved model that balances performance and cost. Anaconda delivers the NVIDIA CUDA software stack as version-matched Python packages, so GPU-accelerated environments install with a single command. AI Orchestration deploys models and workflows across cloud, hybrid, on-premises, and sovereign infrastructure, lets you switch targets without rebuilding, and tracks resource use and cost as workloads scale. Runtime guardrails from Enkrypt AI by Anaconda detect and block unsafe model behavior. -
3
EmpirioLabs AI
EmpirioLabs AI
EmpirioLabs AI is specialized AI model hosting for open, proprietary, and custom stacks. We run open-source models on GPU infrastructure we manage, serve optimized endpoints for proprietary models, and help teams deploy their own models to real users. The catalog spans text, image, video, audio, transcription, embedding, reranking, research, and 3D models, with a browser playground, GPU Cloud instances, and hosted AI agents. It comes with live per-model pricing, a REST API, a remote MCP server for Claude, ChatGPT, and code editors, and integrations for LangChain, LiteLLM, Dify, n8n, and VS Code. New models and features are available as they launch.Starting Price: $19.90/month -
4
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
Intel Open Edge Platform
Intel
The Intel Open Edge Platform simplifies the development, deployment, and scaling of AI and edge computing solutions on standard hardware with cloud-like efficiency. It provides a curated set of components and workflows that accelerate AI model creation, optimization, and application development. From vision models to generative AI and large language models (LLM), the platform offers tools to streamline model training and inference. By integrating Intel’s OpenVINO toolkit, it ensures enhanced performance on Intel CPUs, GPUs, and VPUs, allowing organizations to bring AI applications to the edge with ease.
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