Interested in running Llama 4 Maverick in production?

Request access to Together Dedicated Endpoints—private and fast Llama 4 Maverick inference at scale.

  • Fastest inference: Industry-leading speeds for multimodal AI
  • Flexible scaling: Deploy via Together Serverless or dedicated endpoints
  • Native multimodality: Text and image understanding with 128K context
  • Secure & reliable: Private, compliant, and built for production

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Llama 4 Maverick on Together AI

Unmatched performance. Cost-effective scaling. Secure infrastructure.

Fastest inference engine

We run Llama 4 Maverick with industry-leading speeds on optimized MoE infrastructure, ensuring low-latency performance for multimodal production workloads.

Scalable infrastructure

Whether you're just starting out or scaling to production workloads, choose from Together Serverless APIs for flexible, pay-per-token usage or dedicated endpoints for predictable, high-volume operations.

Security-first approach

We host all models in our own data centers, with no data sharing back to Meta. Developers retain full control over their data with opt-out privacy settings.

Deployment options

Run models using different deployment options depending on latency needs, traffic patterns, and infrastructure control.

  • Serverless

  • Inference

Serverless Inference

Real-time

A fully managed inference API that automatically scales with request volume.

Best for

Variable or unpredictable traffic

Rapid prototyping and iteration

Cost-sensitive or early-stage production workloads

Batch

Process massive workloads of up to 30 billion tokens asynchronously, at up to 50% less cost.

Best for

Classifying large datasets

Offline summarization

Synthetic data generation

Dedicated Inference

Dedicated Model Inference

An inference endpoint backed by reserved, isolated compute resources and the Together AI inference engine.

Best for

Predictable or steady traffic

Latency-sensitive applications

High-throughput production workloads

Dedicated Container Inference

Run inference with your own engine and model on fully-managed, scalable infrastructure.

Best for

Generative media models

Non-standard runtimes

Custom inference pipelines