Description
Bento is a comprehensive inference platform built for speed and control, empowering AI teams to deploy any model anywhere with tailored optimization, efficient scaling, and streamlined operations. It simplifies inference infrastructure while providing granular control over deployments, making it easier to manage, monitor, and optimize AI model inference.
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Bento supports deploying a wide range of models, including popular open-source options like Llama 4, DeepSeek, Ling/Ring, Flux, Qwen, and GPT-OSS, through its Open Model Catalog. It also offers a unified framework for packaging and deploying custom models of any architecture, framework, or modality, including fine-tuned open-source models and proprietary custom models. The platform automates deployment and CI/CD processes, provides comprehensive observability, fine-grained access control, and resource/quota tracking.
For efficient scaling, Bento features the Bento Compute Engine, which provides intelligent resource management for optimal compute utilization. It supports cross-region scaling, elastic auto-scaling, cold-start acceleration, multi-cloud compute orchestration, and scaling-to-zero capabilities. Users have complete control over their infrastructure and deployment environment, with options to deploy on their own cloud, on-premises Kubernetes, or leverage Bento Cloud for access to cutting-edge GPU hardware without procurement hassles, including Nvidia GPUs, AMD GPUs, and B200, H100, MI300X.
Bento accelerates the path to production for AI applications by providing developers with everything they need to build, ship, and scale AI inference. This includes a Dev Codespace for rapid cloud iteration, an LLM Gateway for a unified interface to all LLM providers with centralized cost control, and streamlined operations with full deployment lifecycle management, version control, rollbacks, and A/B testing. Full observability is achieved through comprehensive monitoring of compute, performance, and LLM-specific metrics.
The platform is built for enterprise-grade security, compliance, and operational capabilities, ensuring reliability with performance SLAs, 24/7 monitoring, uptime guarantees, and automatic failover. Bento also offers Forward Deployed Engineering with dedicated technical experts, inference optimization research, and continuous benchmarking. Data sovereignty is maintained with full control over user data. BentoML is now part of Modular.
- CategoryMLOps & Model Deployment
- Pricing ModelContact for details
- DeploymentCloud, On-Premises
- PlatformsWeb
Bento's Core Features
Deploy any model anywhere
Tailored inference optimization
Efficient scaling capabilities
Streamlined operations
Open Model Catalog for popular open-source models
Unified framework for custom model packaging and deployment
Automated deployment and CI/CD
Comprehensive observability and monitoring
Fine-grained access control
Resource and quota tracking
Intelligent resource management for compute utilization
Cross-region and elastic auto-scaling
Cold-start acceleration
Multi-cloud compute orchestration
Scaling-to-zero
How to use Bento?
Build: Package your model using the unified framework.
Deploy: Automate deployment with CI/CD pipelines.
Scale: Utilize intelligent resource management for efficient scaling.
Monitor: Track performance and system health with comprehensive observability.
Optimize: Tune every layer of your deployment for speed, cost, and quality.
Bento's Use Cases
- Model Deployment
- Inference Scaling
- Performance Optimization
- Streamlined Operations
- Cloud-Native Inference
- LLM Serving
- Batch Inference
- Real-time AI Features
