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AI infrastructure · Tool
Modal
ResearchedModal is a serverless cloud platform for AI and data teams offering sub-second cold starts, instant GPU autoscaling, and pay-per-use compute for inference, training, batch processing, and sandboxes.
Official site snapshots
Visit live site See the official site at a glance
Read-only public captures of Modal’s homepage and verified pricing page. Screenshots are dated, never live embeds, and open full-screen.
In one minute
Start here for the decision-making essentials: what Modal does, who it is for, how it is accessed, and the first-party sources behind this profile.
Pricing5 options
Pay-per-use compute billed by the CPU cycle
customers never pay for idle resources.
Nvidia H100 GPU tasks are priced at $0.001097 per second.
Starter plan is $0/month plus compute, with $30/month in free credits, up to 3 workspace s
Team plan is $250/month plus compute, with $100/month in free credits, unlimited seats, 10
Platforms
Cloud computing serviceCore Platform
API accessNot public
FoundedNot disclosed by source
AvailabilityWeb / remote
LicenseProprietary
Best suited to
Source-backed fit AI and data teams building compute-intensive applications Engineers and researchers deploying and serving large language models Startups and organizations scaling GPU workloads Developers who prefer infrastructure-free cloud compute Graduate students, labs, and early-stage startups eligible for free… AI and data teams
Decision support
6 sourced answersCommon questions and adoption checks
Short answers to the questions buyers and builders commonly ask about Modal. Each answer cites the shared ledger below, where every source is listed once.
01What does Modal say it can do?
Run inference, training, batch processing, and sandboxes with sub-second cold starts and i · Autoscale from 0 to 1000+ GPUs instantly · Run any model or inference engine on H100s, A100s, A10Gs and more, with scale-to-zero · SFT, LoRA, and full fine-tunes on B200s, H100s, A100s and more
Run inference, training, batch processing, and sandboxes with sub-second cold starts, instant autoscaling, and a developer experience that feels local.
02Who is Modal intended for?
AI and data teams · Graduate students, labs, and researchers are eligible to apply for up to $10,000 in free M · Early-stage startups can apply for free Modal compute credits. · Engineers and researchers building compute-intensive applications
The serverless platform for AI and data teams.
03What use cases does Modal describe?
Deploy and scale inference for LLMs, audio, and image/video generation · Fine-tune open-source models on single or multi-node clusters · Programmatically scale secure, ephemeral environments for running untrusted code · Language Models
Inference Deploy and scale inference for LLMs, audio, image/video generation.
04What should teams verify before adopting Modal?
Refusing cookies may prevent use of some portions of the Service
If you choose to refuse our cookies, you may not be able to use some portions of our Service
Ledger citation[9] modal.com/legal/privacy-policy
05What pricing information is available for Modal?
Pay-per-use compute billed by the CPU cycle; customers never pay for idle resources. · Nvidia H100 GPU tasks are priced at $0.001097 per second. · Starter plan is $0/month plus compute, with $30/month in free credits, up to 3 workspace s · Team plan is $250/month plus compute, with $100/month in free credits, unlimited seats, 10
you always pay for what you use and nothing more. You never pay for idle resources — just actual compute time, by the CPU cycle.
06Does Modal document API access?
Modal offers a gRPC API as the primary well-described interface for interactions.
Most interactions with Modal are well-described in a gRPC API
Ledger citation[10] modal.com/docs/guide/security
Decision guide
AI infrastructureCapabilities and operating fit
This profile connects the jobs Modal is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
Common use cases
- Deploy and scale inference for LLMs, audio, and image/video generation
- Fine-tune open-source models on single or multi-node GPU clusters
- Programmatically scale secure, ephemeral sandboxes for running untrusted code
- Run large-scale batch workflows and job queues
- Serve models with hundreds of billions of parameters
- Deploy OpenAI-compatible LLM services and OpenCode coding agents at scale
Topics mapped
Verified capabilities
- Run inference, training, batch processing, and sandboxes with sub-second cold starts and i
- Autoscale from 0 to 1000+ GPUs instantly
- Run any model or inference engine on H100s, A100s, A10Gs and more, with scale-to-zero
- SFT, LoRA, and full fine-tunes on B200s, H100s, A100s and more
- Multi-node training up to 128 B200s with 3200 Gbps Infiniband networking
- Sub-10ms overhead latency from globally distributed compute
- Serverless compute that instantly autoscales up and down based on request volume.
- Modal Sandbox + Notebooks lets users burst CPU and memory as needed without over-allocatin
Recorded integrations
Out-of-the-box support for token streaming, WebRTC, and WebSocketPrimitives include Storage (Volumes, Buckets), Data Structures (Queues, Dicts), and NetworOIDC authentication for external servicesDiscord Bot deploymentGoogle Sheets data syncOpenAI RAG chatbot integrationTailscale VPN integration for Modal AppsMount S3 buckets in Modal appsDuckDB and DBT for building data warehousesvLLM
Intended audiences
Access signals
- Pricing model
- Pay-per-use compute billed by the CPU cycle; customers never pay for idle resources. · Nvidia H100 GPU tasks are priced at $0.001097 per second. · Starter plan is $0/month plus compute, with $30/month in free credits, up to 3 workspace s · Team plan is $250/month plus compute, with $100/month in free credits, unlimited seats, 10
- API
- Not publicly listed
- Source links
- 17 recorded
Source-backed
Updated July 22, 2026Verified facts
Each fact points to a recorded source, making it easy to distinguish verified product information from claims that need checking.
Modal: High-performance AI infrastructure
Serverless platform for AI and data teams (modal.com/) · Sub-second cold starts and instant autoscaling (modal.com/) · Autoscale from 0 to 1000+ GPUs, instantly (modal.com/)
Run inference, training, batch processing, and sandboxes with sub-second cold starts and instant autoscaling
Serverless platform for AI and data teams
AI and data teams
Deploy and scale inference for LLMs, audio, and image/video generation
Fine-tune open-source models on single or multi-node clusters
View 32 more verified facts
Programmatically scale secure, ephemeral environments for running untrusted code
Autoscale from 0 to 1000+ GPUs instantly
Run any model or inference engine on H100s, A100s, A10Gs and more, with scale-to-zero
SFT, LoRA, and full fine-tunes on B200s, H100s, A100s and more
Multi-node training up to 128 B200s with 3200 Gbps Infiniband networking
Sub-10ms overhead latency from globally distributed compute
Out-of-the-box support for token streaming, WebRTC, and WebSocket
Pay-per-use compute billed by the CPU cycle; customers never pay for idle resources.
Nvidia H100 GPU tasks are priced at $0.001097 per second.
Starter plan is $0/month plus compute, with $30/month in free credits, up to 3 workspace seats, 100 containers, 10 GPU concurrency, limited Scheduled and Web Functions, real-time metrics and logs, and region selection.
Team plan is $250/month plus compute, with $100/month in free credits, unlimited seats, 1000 containers, 50 GPU concurrency, unlimited Scheduled Functions, custom domains, static IP proxy, and deployment rollbacks.
Enterprise plan pricing is custom with volume-based discounts, unlimited seats, higher GPU concurrency, and embedded ML engineering services.
Serverless compute that instantly autoscales up and down based on request volume.
Modal Sandbox + Notebooks lets users burst CPU and memory as needed without over-allocating in advance, paying only for what they use.
Enterprise plan customers receive support via a private Slack channel.
Enterprise plan includes audit logs, Okta SSO, and HIPAA support.
Modal can be transacted through the AWS and GCP marketplaces so customers can use committed spend.
Graduate students, labs, and researchers are eligible to apply for up to $10,000 in free Modal compute credits.
Early-stage startups can apply for free Modal compute credits.
Serverless cloud platform
Engineers and researchers building compute-intensive applications
Runs generative AI models, large-scale batch workflows, and job queues
Run serverless cloud functions from the browser
Deploy an OpenAI-compatible LLM service with a drop-in replacement for the OpenAI API
Deploy OpenCode agents at scale in secure Sandboxes
Design protein binders with ESMFold2, proposing and evaluating thousands of binders in parallel
Transcribe speech in batches with Whisper, turning audio bytes into text at scale
Serve language models with hundreds of billions of parameters
Fold proteins with Boltz-2 to predict molecular structures and binding affinities using state-of-the-art open-source models
Low-latency serving of interactive LLM applications via SGLang
Serverless WebRTC streaming of YOLO detections on webcam footage in real time
Modal Labs
Practical capabilities
8 documented areasWhat it helps with
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
Deploy and scale inference for LLMs, audio, and image/video generation
Fine-tune open-source models on single or multi-node GPU clusters
Programmatically scale secure, ephemeral sandboxes for running untrusted code
Run large-scale batch workflows and job queues
Serve models with hundreds of billions of parameters
Deploy OpenAI-compatible LLM services and OpenCode coding agents at scale
Transcribe speech at scale with Whisper and design protein binders with ESMFold2
Fine-tune open-source models on single or multi-node clusters
Availability
Source checkedWhere it runs and where to get it
Documented product formats, platforms and official distribution destinations. Availability can vary by region and plan.
Cost / license
Pay-per-use compute billed by the CPU cycle; customers never pay for idle resources. · Nvidia H100 GPU tasks are priced at $0.001097 per second. · Starter plan is $0/month plus compute, with $30/month in free credits, up to 3 workspace s · Team plan is $250/month plus compute, with $100/month in free credits, unlimited seats, 10
Application types
Products include Inference, Training, Sandboxes, Batch, and NotebooksModal Sandboxes for executing code in secure environments
Platforms
Serverless platform for AI and data teamsCloud computing serviceCloud infrastructure designed for AI workloadsCore Platform
Adoption notes
DeploymentServerless cloud platform · Burst to thousands of GPUs on demand and scale back down to zero · Fully serverless: Modal hosts everything and charges per second of usage · Serverless WebRTC support
LicenseNot disclosed by source
Model supportwhisper-tiny.en
Data controlEnterprise plan includes audit logs, Okta SSO, and HIPAA support. · No transmission or electronic storage method is 100% secure or reliable · Customer-supplied encryption keys supported · Modal builds software using memory-safe programming languages, including Rust (for worker · Modal makes decisions to minimize its attack surface, with most interactions well-describe
Learning curveIntermediate
Primary use casesDeploy and scale inference for LLMs, audio, and image/video generation, Fine-tune open-source models on single or multi-node GPU clusters, Programmatically scale secure, ephemeral sandboxes for running untrusted code, Run large-scale batch workflows and job queues, Serve models with hundreds of billions of parameters, Deploy OpenAI-compatible LLM services and OpenCode coding agents at scale, Transcribe speech at scale with Whisper and design protein binders with ESMFold2, Fine-tune open-source models on single or multi-node clusters, Programmatically scale secure, ephemeral environments for running untrusted code, Language Models, Image, Video, 3D Processing, Audio Processing, Batch Processing, Sandboxed Code, Computational Bio, Coding Agents
What to verify before adopting
- Refusing cookies may prevent use of some portions of the Service
Evolution and major updates
2 dated updatesModal timeline
A concise history of software releases and material product changes. Events appear only when a dated source supports what changed.
Latest first · exact dates
Showing the newest updates and meaningful milestones. Open an entry for its summary and source.
Modal published case study on Decagon shipping real-time voice AI on Modal
Open detailsModal published a customer story co-authored with Decagon's technical staff describing how Decagon built and launched Decagon Voice 2.0 on Modal's infrastructure, pairing supervised fine-tuning and reinforcement learning with Modal's specialized LLM inference…
View source [11]Modal publishes case study on Decagon voice AI collaboration
Open detailsModal jointly published a customer story with Decagon detailing how Decagon shipped real-time voice AI agents on Modal's infrastructure. The case study describes how Decagon Voice 2.0 achieved a 65% reduction in latency through a partnership combining…
View source [11]
Citation ledger
18 unique pagesRecorded sources
Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
- 1modal.com 16 facts · 3 answers · Official site
- 2modal.com/pricing 12 facts · 3 answers · Pricing
- 3modal.com/docs 12 facts · 2 answers · Documentation
- 4modal.com/docs/examples 14 facts · Documentation
- 5modal.com/customers 11 facts · 2 answers · Official site
- 6modal.com/products/platform 12 facts · 1 answer · Official site
- 7modal.com/docs/guide 10 facts · 1 answer · Documentation
- 8modal.com/blog 7 facts · 2 answers · Official site
- 9modal.com/legal/privacy-policy 6 facts · 3 answers · Security
- 10modal.com/docs/guide/security 4 facts · 1 answer · Documentation
- 11modal.com/blog/decagon-case-study 2 milestones
- 12modal.com/docs/examples/batched_whisper Documentation
- 13modal.com/docs/examples/chatterbox_tts Documentation
- 14modal.com/docs/examples/fine_tune_asr Documentation
- 15modal.com/docs/examples/generate_music Documentation
- 16modal.com/docs/examples/llm-finetuning Documentation
- 17modal.com/docs/examples/llm-voice-chat Documentation
- 18modal.com/docs/examples/vllm_inference Documentation
Research status120 substantive facts · 17 source pages · quality score 100/100
Connected directory
Semantic matchesExplore related solutions
These tools share a workflow, capability or audience with Modal. They may complement it rather than replace it, and are not presented as integrations or endorsements.
