Serverless inference with pay-per-use token pricing ($0.0015 to $4.50 per 1M tokens for chat/vision models). Provisioned throughput with reserved PTUs for committed capacity. Dedicated GPU endpoints at $5.49-$8.99 per hour. Fine-tuning from $0.34-$40 per 1M tokens. GPU clusters at $1.99-$9.99 per GP
Not given
Key features
GPU clusters at scale with autoscaling
Voice agent infrastructure with sub-second latency
Comprehensive model library with 25+ regions
Hierarchical traces capture every LLM call, tool invocation, and retrieval step
LLM-as-a-judge, heuristic functions, or human review evaluations
Prompt management with one-click deployments and rollbacks
Playground to test prompts on real production inputs and compare models
Experiments with test cases and side-by-side comparison
Human annotation and collaborative human-in-the-loop workflows
Cost and latency monitoring with dashboards and alerts
REST APIs and Query SDK for data access
Langfuse Assistant to automate the AI engineering loop
What makes it different
2x faster inference powered by cutting-edge research optimization
60% lower cost with workload-specific optimization
90% faster pre-training with Together Kernel Collection
Research-optimized infrastructure with proprietary kernels
Single unified API across multiple model providers
MIT licensed open source platform with no data lock-in
Enterprise scale architecture handling billions of monthly events
Works with any language and framework with no framework lock-in
Async by default so tracing never blocks your application