The Best Model Hosting in 2026
We researched model hosting products using vendors’ official websites, including pricing pages, plan tables, and product documentation. Rankings focus on the category’s core job: deploying and serving models, value for money, and features buyers can verify, such as supported runtimes, scaling controls, and endpoint options.
Our top picks
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Top ranked
Amazon SageMaker AI#1 of 259.3/10A broad AWS-managed ML lifecycle, with usage-based costs and no ongoing free plan.
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Runner-up
9.2/10A full ML lifecycle platform with visual workflows, managed compute, tracking, and online serving.
Free plan
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Top-ranked free plan
IBM watsonx.ai#6 of 258.8/10An enterprise AI studio spanning model development, hosting, and lifecycle management.
Free plan
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.
The full ranking 25 tools, best first
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Best forTeams wanting end-to-end managed ML on AWS
A broad AWS-managed ML lifecycle, with usage-based costs and no ongoing free plan.
9.3/10★★★★★Visit AWS -
Best forTeams needing an affordable full ML lifecycle platform
A full ML lifecycle platform with visual workflows, managed compute, tracking, and online serving.
9.2/10★★★★★Visit Alibaba Cloud -
Best forData-platform teams building and serving models
A cloud platform linking model development, governed data, orchestration, and serving.
9.1/10★★★★★Visit Databricks -
Best forAzure teams with automated, monitored ML workflows
Automates model development and deployment, with Azure compute billed separately.
9.0/10★★★★☆Visit Azure ML -
Best forOCI teams deploying machine-learning models
A fit for OCI teams that need managed training, pipelines, model serving, and monitoring.
8.9/10★★★★☆Visit Oracle Cloud -
Best forEnterprises building AI across the lifecycle
An enterprise AI studio spanning model development, hosting, and lifecycle management.
8.8/10★★★★☆Visit IBM -
Best forTeams serving custom models on serverless or GPUs
A flexible serving stack for teams choosing between per-token inference and dedicated GPUs.
- Autoscaling
8.8/10★★★★☆Visit Fireworks AI -
Best forTeams deploying observable model APIs on managed compute
Managed model APIs, GPU deployments and observability, with compute billed by usage.
- Autoscaling
8.7/10★★★★☆Visit Baseten -
Best forKubernetes teams needing flexible self-hosted serving
Flexible model serving for Kubernetes teams prepared to run their own infrastructure.
- Autoscaling
8.6/10★★★★☆Visit KServe -
Best forTeams deploying community or custom models quickly
A cloud platform for running community or custom models, with deployment controls and usage-based pricing.
- Autoscaling
8.5/10★★★★☆Visit Replicate -
Best forDevelopers building with Gemini through an API
A cloud API for Gemini generation, structured outputs, file processing, and tool calls.
7.9/10★★★★☆Visit site -
Best forTeams needing OpenAI models through hosted APIs
Hosted OpenAI models, agent workflows and tools for applications built through APIs.
7.9/10★★★★☆Visit OpenAI API -
Best forTeams adding live or on-demand video to apps
A video hosting and delivery service, not a host for machine-learning models.
7.9/10★★★★☆Visit site -
Best forTeams serving LLMs with Ray Serve or vLLM
A flexible serving platform for teams deploying LLMs with Ray Serve or vLLM.
- Custom model hosting
- GPU inference
- Autoscaling
7.9/10★★★★☆Visit Anyscale -
Best forDevelopers seeking flexible, open-source model serving
Flexible model serving with open-source packaging, managed deployments, and self-hosted options.
- Autoscaling
7.8/10★★★★☆Visit BentoML -
Best forTeams deploying Hub models on managed endpoints
Deploy Hub models on managed endpoints with configurable hardware, runtimes, and scaling.
- Autoscaling
7.7/10★★★★☆Visit Hugging Face -
Best forTeams needing hosted inference across model types
A broad hosted inference catalog with dedicated endpoints and GPU options.
- GPU inference
- Autoscaling
7.6/10★★★★☆Visit DeepInfra -
Best forTeams running containerized GPU inference workers
A container-first option for GPU inference, with autoscaling and per-second compute billing.
7.5/10★★★★☆Visit Runpod -
Best forTeams seeking usage-priced custom GPU endpoints
Usage-priced hosting for custom and Hugging Face models, with serverless and dedicated GPU options.
- Custom model hosting
- GPU inference
- Autoscaling
7.4/10★★★★☆Visit Novita AI -
Best forPython teams deploying autoscaling inference functions
A fit for autoscaling inference functions, with GPU compute and a free Starter tier.
7.4/10★★★★☆Visit Modal -
Best forDevelopers building with hosted model inference APIs
A cloud API for hosted model inference, with free access and pay-as-you-go options.
7.2/10★★★★☆Visit GroqCloud -
Best forTeams needing API inference for supported models
API-based inference with streaming, structured outputs, and dedicated endpoints.
- Custom model hosting
7.1/10★★★★☆Visit Cerebras -
Best forDevelopers wanting hosted model API access
A serverless model API with a web playground, streaming, and OpenAI and Anthropic compatibility.
7.0/10★★★★☆Visit SambaNova -
Best forEnterprises deploying connected-data agents privately
A private-deployment AI workspace for organizational search and workflow agents.
6.5/10★★★☆☆Visit Cohere -
Best forTeams building generative video APIs and custom models
A cloud platform for video-generation APIs, asynchronous workflows, and custom model deployment.
6.3/10★★★☆☆Visit fal
No tools match those filters.
Compare at a glance
| # | Tool | Free plan | Paid from | Score |
|---|---|---|---|---|
| 1 | Amazon SageMaker AI | No | 9.3 | |
| 2 | Alibaba Cloud Machine Learning Platform for AI | Yes | $0.06/unit usage-based | 9.2 |
| 3 | Databricks Mosaic AI | 9.1 | ||
| 4 | Azure Machine Learning | No | 9.0 | |
| 5 | Oracle Cloud Infrastructure Data Science | No | 8.9 | |
| 6 | IBM watsonx.ai | Yes | $1,110/mo | 8.8 |
| 7 | Fireworks AI | No | $0.05/unit usage-based | 8.8 |
| 8 | Baseten | Yes | 8.7 | |
| 9 | KServe | Free | 8.6 | |
| 10 | Replicate | No | 8.5 | |
| 11 | Google Gemini API | Yes | Free | 7.9 |
| 12 | OpenAI API | 7.9 | ||
| 13 | Cloudflare Stream | No | $5/unit/mo | 7.9 |
| 14 | Anyscale | No | 7.9 | |
| 15 | BentoML | Yes | 7.8 | |
| 16 | Hugging Face Inference Endpoints | No | $0.06/unit usage-based | 7.7 |
| 17 | DeepInfra | 7.6 | ||
| 18 | Runpod Serverless | No | $0.58 usage-based | 7.5 |
| 19 | Novita AI | $0.61/device usage-based | 7.4 | |
| 20 | Modal | Yes | $250/mo | 7.4 |
| 21 | GroqCloud | Yes | 7.2 | |
| 22 | Cerebras Inference | No | 7.1 | |
| 23 | SambaNova Cloud | Yes | 7.0 | |
| 24 | Cohere North | 6.5 | ||
| 25 | fal | No | 6.3 |
Head-to-head All 18 comparisons →
- Amazon SageMaker AI vs IBM watsonx.ai
- Amazon SageMaker AI vs Fireworks AI
- Amazon SageMaker AI vs Baseten
- Alibaba Cloud Machine Learning Platform for AI vs IBM watsonx.ai
- Alibaba Cloud Machine Learning Platform for AI vs Fireworks AI
- Alibaba Cloud Machine Learning Platform for AI vs Baseten
- Databricks Mosaic AI vs Oracle Cloud Infrastructure Data Science
- Databricks Mosaic AI vs Fireworks AI
- Databricks Mosaic AI vs Baseten
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How we rank model hosting
Every tool on this page was researched by iTechGuides Editors from its official website — pricing pages, plan tables and product documentation. We rank on how well each one does this category's core job, what the free or entry plan includes, and where it falls short. Where we have enough verified facts, the score out of 10 is a rubric — job fit, value and how much we could verify — shown with its breakdown on every tool's page; a tool we have not verified enough to score yet shows its rank without a number. Scores are re-checked when a product changes its plans. Read the full editorial policy, or submit a tool we missed.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update