Can I use multiple GPU types for training?

Yes. FlexAI's hardware-agnostic platform lets you train across NVIDIA H100, H200, A100, and AMD accelerators. Switch GPU types without changing code.

How do checkpoints work on FlexAI?

FlexAI automatically manages checkpointing with self-healing infrastructure. If a node fails, training resumes from the last checkpoint with no manual intervention.

What frameworks are supported for distributed training?

FlexAI supports DeepSpeed, FSDP, Megatron-LM, and native PyTorch DDP out of the box. Flash Attention 2 is enabled by default on compatible hardware.

Intent driven training, end to end

Name: FlexAI Training
Brand: FlexAI

Bring your datasets and code. FlexAI handles orchestration, checkpoints, and workload placement so your team stays in motion.

Launch a run Browse blueprints

<60s

Job launch

>90%

GPU utilization

<10%

DevOps overhead

Two phases. One rhythm.

Pre training prep that ships

Dataset ingest from buckets, volumes, or your existing storage.

Multi node without complexity

Scale from a single GPU to large clusters.

Checkpoints that just happen

Automatic snapshots and fast resume.

Large Scale Support

1 to 1000s of GPUs
Multi-node distributed
Multi-region compute

Performance & Resilience

Parallelized execution
Auto checkpointing
Seamless data pipelines

Built-in Observability

TensorBoard · Visualize metrics and graphs
Weights & Biases · Track experiments at scale
Grafana · Infrastructure monitoring

A calm interface for serious work

A simple control point for end users and admins, with governance and visibility when you need it.

One platform

Web UI, CLI, and API all map to the same mental model. Your workflow stays yours.

Self healing runs

Automatic recovery with managed checkpoints so long runs keep their shape.

Enterprise grade guardrails

RBAC, quota policies, and visibility across teams and workloads.

Start with our Blueprints

View all→

Domain fine tuning playbookpre training

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Multi node training with managed checkpointstraining

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Post training alignment pipelinepost training

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Evaluation and release gateseval

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Proof

Teams keep velocity

A few words from builders using FlexAI for training and deploying models.

>95%

Utilization

>90%

Uptime

0 rewrite

Code changes

"
Compared to other platforms I have used, FlexAI provides a more cost effective and hassle free experience for training and deploying my models.
Legml.ai

"
FlexAI enabled us to prove the value of our model in record time and make it to Y Combinator.
Dollyglot.com

"
The ability to manage compute resources across multiple cloud providers through a unified interface is a game changer.
Pixelcut.ai

Get started

Put pre and post training on rails

Open console Talk to an engineer

90 second path

1Pick a blueprint for your model family and stage
2Set constraints: budget, speed, region, reliability
3Launch. Observe. Promote the winner