详细内容
Join us at the Late Shift after-party at AWS re:Invent on December 3.Register
AI infrastructure that developers love
Run inference, training, and batch processing with sub-second cold
starts, instant autoscaling, and a developer experience that feels
local.
Get Started Contact Us
PROGRAMMABLE INFRA
BUILT FOR PERFORMANCE
ELASTIC GPU SCALING
UNIFIED OBSERVABILITY
Why Modal
Designed to help AI teams deploy faster.
Programmable infra
Define everything in code, no YAML or config files. Keep environment and hardware requirements in sync.
Built for performance
Launch and scale containers in seconds to keep feedback loops tight and latency low.
Elastic GPU scaling
Elastic GPU capacity and access to thousands of GPUs across clouds. No quotas or reservations. Scale back to zero when not in use.
Unified observability
Integrated logging and full visibility into every function, container, and workload.
PRODUCTS
Powering any ML workload
Inference \
\
Deploy and scale inference for LLMs, audio, image/video generation.\
\
Learn more Training \
\
Fine-tune open-source models on single or multi-node clusters instantly.\
\
Learn more Sandboxes \
\
Programmatically scale secure, ephemeral environments for running untrusted code.\
\
Learn more Batch \
\
Scale to thousands of containers for batch workloads on-demand.\
\
Learn more Notebooks \
\
Collaborate on code and data in real-time with shareable notebooks.\
\
Learn more
PLATFORM
Build on a powerful foundation
From filesystem to runtime, every layer of Modal’s platform is
engineered to give you the tools to build robust, scalable data
applications.
AI-native runtime
Engineered from the ground up for heavy AI workloads, built for super-fast autoscaling and model initialization and 100x faster than Docker.
Built-in storage layer
A globally distributed storage system built for high throughput and low latency. Designed for fast model loading, training data, or other datasets.
First-party integrations
Mount your existing cloud buckets, connect to MLOps tools, and send data to your existing telemetry vendors.
Multi-cloud capacity pool
Deep multi-cloud capacity with intelligent scheduling ensures you always have the CPUs and GPUs you need without managing input orchestration.
Built with Modal
Audio Transcription
LLM Inference
Coding Agents
Computational Biology
Image and Video Inference
Transcribe speech in batches with Whisper \
\
Turn audio bytes into text at scale
Voice chat with LLMs \
\
Build an interactive voice chat app
Transcribe speech with Kyutai STT \
\
Stream transcripts at the speed of speech
Make music \
\
Turn prompts into music with ACE-Step
Security and governance
Team controls
Battle-tested isolation
SOC2 & HIPAA
Data residency controls
Team controls
Battle-tested isolation
SOC2 & HIPAA
Data residency controls
“We use Modal to run edge inference with <10ms overhead and batch jobs at large scale. Our team loves the platform for the power and flexibility it gives us.”
Brian Ichter, Co-founder
“Modal makes it easy to write code that runs on 100s of GPUs in parallel, transcribing podcasts in a fraction of the time.”
Mike Cohen, Head of Data
“Everyone here loves Modal because it helps us move so much faster. We rely on it to handle massive spikes in volume for evals, RL environments, and MCP servers. Whenever a team asks about compute, we tell them to use Modal.”
Aakash Sabharwal, VP of Engineering
“We've previously managed to break services like GitHub because of our load, so Modal handling our massive scale so smoothly means a lot. We trust Modal to keep up with our growth, and we're excited to build together in the long term.”
Anton Osika, CEO & Founder
Join Modal's developer community
Igor Kotua\
\
Engineer, The Linux Foundation
If you building AI stuff with Python and haven't tried @modal you are missing out big time
Caleb\
\
ML Engineer, Hugging Face
Bullish on @modal
- Great Docs + Examples
- Healthy Free Plan (30$ free compute / month)
- Never have to worry about infra / just Python
Daniel Rothenberg\
\
Co-founder, Brightband
@modal continues to be magical... 10 minutes of effort and the `joblib`-based parallelism I use to test on my local machine can trivially scale out on the cloud. Makes life so easy!
@mattzcarey.com on blsky\
\
AI Engineer, StackOne
@modal has got a bunch of stuff just worked out
this should be how you deploy python apps. wow
Erin Boyle\
\
ML Engineer, Tesla
This tool is awesome. So empowering to have your infra needs met with just a couple decorators. Good people, too!
Aman Kishore\
\
Research Engineer, Harvey
If you are still using AWS Lambda instead of @modal you're not moving fast enough
Jai Chopra\
\
Product, LanceDB
Recently built an app on Lambda and just started to use @modal, the difference is insane! Modal is amazing, virtually no cold start time, onboarding experience is great 🚀
special shout out to @modal and @_hex_tech for providing the crucial infrastructure to run this! Modal is the coolest tool I’ve tried in a really long time— cannnot say enough good things.
Diego Fernandes\
\
Co-founder & CTO, RocketSeat
Probably one of the best piece of software I'm using this year: modal.com
Mark Tenenholtz\
\
Head of AI, PredeloHQ
I use @modal because it brings me joy. There isn't much more to it.
Adam Azzam\
\
Product, Prefect
feels weird at this point to use anything else than @modal for this — absolutely the GOAT of dynamic sandboxes
Mark Neumann\
\
Head of ML, Orbital Materials
Used @modal for the first time today - immediate "oh, this is how backends should work" moment, similar to using Vercel for the first time for frontend deployments.
Rémi 📎\
\
Co-founder & CEO, .txt
Nothing beats @modal when it comes to deploying a quick POC
Moin Nadeem\
\
Co-founder, Phonic
I've realized @modal is actually a great fit for ML training pipelines.
If you're running model-based evals, why not just call a serverless Modal function and have it evaluate your model on a separate worker GPU? This makes evaluation during training really easy.
Late to the party, but finally playing with @modal to run some backend jobs.
DX is sooo nice (compared to Docker, Cloud Run, Lambda, etc). Just decorate a Python function and deploy. And it's fast! Love it.
Igor Kotua\
\
Engineer, The Linux Foundation
If you building AI stuff with Python and haven't tried @modal you are missing out big time
Caleb\
\
ML Engineer, Hugging Face
Bullish on @modal
- Great Docs + Examples
- Healthy Free Plan (30$ free compute / month)
- Never have to worry about infra / just Python
Daniel Rothenberg\
\
Co-founder, Brightband
@modal continues to be magical... 10 minutes of effort and the `joblib`-based parallelism I use to test on my local machine can trivially scale out on the cloud. Makes life so easy!
@mattzcarey.com on blsky\
\
AI Engineer, StackOne
@modal has got a bunch of stuff just worked out
this should be how you deploy python apps. wow
Erin Boyle\
\
ML Engineer, Tesla
This tool is awesome. So empowering to have your infra needs met with just a couple decorators. Good people, too!
Aman Kishore\
\
Research Engineer, Harvey
If you are still using AWS Lambda instead of @modal you're not moving fast enough
Jai Chopra\
\
Product, LanceDB
Recently built an app on Lambda and just started to use @modal, the difference is insane! Modal is amazing, virtually no cold start time, onboarding experience is great 🚀
special shout out to @modal and @_hex_tech for providing the crucial infrastructure to run this! Modal is the coolest tool I’ve tried in a really long time— cannnot say enough good things.
Diego Fernandes\
\
Co-founder & CTO, RocketSeat
Probably one of the best piece of software I'm using this year: modal.com
Mark Tenenholtz\
\
Head of AI, PredeloHQ
I use @modal because it brings me joy. There isn't much more to it.
Adam Azzam\
\
Product, Prefect
feels weird at this point to use anything else than @modal for this — absolutely the GOAT of dynamic sandboxes
Mark Neumann\
\
Head of ML, Orbital Materials
Used @modal for the first time today - immediate "oh, this is how backends should work" moment, similar to using Vercel for the first time for frontend deployments.
Rémi 📎\
\
Co-founder & CEO, .txt
Nothing beats @modal when it comes to deploying a quick POC
Moin Nadeem\
\
Co-founder, Phonic
I've realized @modal is actually a great fit for ML training pipelines.
If you're running model-based evals, why not just call a serverless Modal function and have it evaluate your model on a separate worker GPU? This makes evaluation during training really easy.
Late to the party, but finally playing with @modal to run some backend jobs.
DX is sooo nice (compared to Docker, Cloud Run, Lambda, etc). Just decorate a Python function and deploy. And it's fast! Love it.
Ship your first app in minutes.
$30 / month free compute
© Modal 2025
Products
Resources
Popular Examples
Analyze Parquet files from S3 with DuckDB
Run hundreds of LoRAs from one app
Finetune an LLM to replace your CEO
Company
© Modal 2025