Modal

The serverless cloud infra for AI, ML, and data applications

5.0•51 reviews•

333 followers

The serverless cloud infra for AI, ML, and data applications

5.0•51 reviews•

333 followers

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Run or deploy machine learning models, massively parallel compute jobs, task queues, web apps, and much more, without your own infrastructure.

Modal Reviews

The community submitted 51 reviews to tell us what they like about Modal, what Modal can do better, and more.

5.0

Based on 51 reviews

Review Modal?

Reviewers, mostly founders, describe Modal as a practical way to run serious compute without managing infrastructure. Makers of Fathom call it a backbone tool for their AI team, while founders of OpenBrowser-AI and Flitch point to easy GPU jobs, strong sandbox support, and smooth integration. Across reviews, the repeated theme is simple Python-first setup, on-demand containers, and reliable execution for training, inference, and code sandboxes. There is almost no critical feedback in the provided reviews.

+49

Summarized with AI

Pros

inference at scale (4)

training pipelines (3)

cold start management (2)

fine-tuning models (2)

Python hosting (2)

scalable GPU serving (2)

Pros

Cons

Reviews

All Reviews

Most Informative

used Modal to build Flitch

•2 reviews

Modal is used to host sandboxes (ephemeral) when editing dashboards (unpublished). The integration, management and sandbox performance has been excellent, particularly compared to and after trialing other products

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2 views4d ago

used Modal to build Reactive Workflows [LW24]

•8 reviews

Modals VM's power our AI agent environments, allowing them to view pull requests, inspect files, and even execute code! Thanks to the Modal team for prioritizing our feature requests and building a GREAT headless compute environment.

What's great

headless compute environment (1)

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14 views1yr ago

used Modal to build Pioneer

•3 reviews

We use Modal to run all of Pioneer's fine-tuning and inference workloads. We evaluated running our own GPU infra on AWS and tried a few other serverless GPU providers, but Modal was the only one where spinning up an H100 job felt as easy as calling a Python function.

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4 views11d ago

used Modal to build Relace Repos

•1 review

Serverless GPU infrastructure helps us scale to workloads of hundreds of H200s/B200s within seconds to maintain low latency for our retrieval models in a cost-effective way.

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8 views7mo ago

used Modal to build RunLLM

•19 reviews

Modal helps us spin up Python workloads with speed and control. Great for agents that need to run fast, ephemeral jobs. A dream for short-lived compute without DevOps overhead.

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6 views9mo ago

used Modal to build My!hū

•3 reviews

I chose Modal because it made running data-heavy workloads feel effortless. A lot of alternatives required more setup or infrastructure thinking, but with Modal I could just focus on the logic and let it handle the scaling and execution. It’s been especially useful for processing environmental data in the background without worrying about servers. It strikes a really nice balance between power and simplicity, which made building and iterating on My!hū much smoother.

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25d ago

used Modal to build Face Animator

•6 reviews

We run our models on Modal. Amazing DX, brilliantly documented API, and very fast and helpful support on their Slack.

What's great

excellent documentation (1)fast support (1)

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4 views1yr ago

used Modal to build Scoopika

•5 reviews

We use Modal to serve TTS and embedding models with scalable GPU power

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2 views2yr ago

used Modal to build AnythingLLM

•6 reviews

For when you want to quickly spin-off a fine-tuned model from AnythingLLM. There is no easier way to build that pipeline we offer in-app than using Modal Labs for creating fine-tuning jobs on powerful GPUs for a fair price.

What's great

scalable GPU serving (2)training pipelines (3)fine-tuning models (2)

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1 view1yr ago

used Modal to build ScaryStories Live

•7 reviews

Huge shoutout to Modal! The cloud infrastructure made spinning up AI and ML tasks for ScaryStories.Live effortlessly. We couldn’t have scaled our real-time horror experiences without you. We’re truly grateful for your generous support in our early days!

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5 views7mo ago

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