Tensorzero
TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.
Last verified:
What is Tensorzero?
TensorZero is an open-source LLMOps platform for production-grade LLM applications that unifies an LLM gateway, observability, evaluation, optimization, and experimentation. The platform is used by companies ranging from frontier AI startups to Fortune 10 companies and fuels approximately 1% of global LLM API spend today.
The TensorZero Stack includes: a high-performance Gateway with unified API access to every LLM provider (<1ms p99 latency overhead), Observability for monitoring LLM systems programmatically or via UI, Evaluation for benchmarking individual inferences or end-to-end workflows, Optimization for improving prompts/models/inference strategies, and Experimentation with built-in A/B testing, routing, fallbacks, and retries.
TensorZero Autopilot is an automated AI engineer that analyzes LLM observability data, sets up evals, optimizes prompts and models, and runs A/B tests. It can analyze millions of inferences to surface error patterns, recommend models and inference strategies, generate and refine prompts based on human feedback, drive fine-tuning/reinforcement learning/distillation workflows, and validate changes through A/B tests.
The platform is designed for ML engineers, AI developers, and teams building industrial-grade LLM applications. It plays nicely with the OpenAI SDK, OpenTelemetry, and every major LLM provider including Anthropic, AWS Bedrock, Azure, Google AI Studio, Groq, Mistral, OpenAI, OpenRouter, Together, vLLM, xAI, and any OpenAI-compatible API like Ollama.
Tensorzero pricing
Pricing model: Freemium
TensorZero is open-source and free to self-host. The website does not disclose specific paid enterprise plans or pricing tiers. The core TensorZero Stack (gateway, observability, optimization, evaluation, experimentation) is available as open-source software. Companies can email [email protected] to set up free Slack or Teams channels for work teams. TensorZero Autopilot appears to be a separate offering but specific pricing is not publicly disclosed on the website.
Tensorzero pros
- Open-source with 11K+ GitHub stars
- Unified API for all major LLM providers
- Sub-millisecond p99 latency overhead (<1ms)
- Written in Rust for high performance
- Built-in observability with your own database
- Supports multi-step LLM workflows with episodes
- Automatic A/B testing and adaptive experimentation
- Built-in fallbacks for provider downtime
- GitOps-friendly configuration orchestration
- Native support for 17+ LLM providers
- OpenAI-compatible API support (e.g., Ollama)
- Structured inferences with schema enforcement
- Supports fine-tuning, RL, and distillation workflows
- TensorZero API key authentication built-in
- Works with OpenAI SDK and OpenTelemetry
- Free tier available for self-hosting
- Supports multimodal inputs (images, PDFs)
- Batch inference for cost savings
Tensorzero cons
- Self-hosted requiring infrastructure setup
- Requires ClickHouse or Postgres for observability
- Learning curve for configuration files
- No managed cloud hosting option mentioned
- Requires Redis/Valkey for rate limiting
- Complex setup for production high-availability
- GitOps workflow may not suit all teams
- Documentation scattered across many pages
Frequently asked questions about Tensorzero
What is TensorZero?
TensorZero is an open-source stack for industrial-grade LLM applications that unifies an LLM gateway, observability, optimization, evaluation, and experimentation. It provides a unified API for all major LLM providers with sub-millisecond latency overhead.
What is TensorZero Autopilot?
TensorZero Autopilot is an automated AI engineer that analyzes LLM observability data, sets up evals, optimizes prompts and models, and runs A/B tests. It acts like Claude Code for LLM engineering, dramatically improving LLM agent performance across diverse tasks.
Which LLM providers does TensorZero support?
TensorZero natively supports Anthropic, AWS Bedrock, AWS SageMaker, Azure, Fireworks, GCP Vertex AI (Anthropic and Gemini), Google AI Studio, Groq, Hyperbolic, Mistral, OpenAI, OpenRouter, Together, vLLM, xAI, and any OpenAI-compatible API like Ollama.
How fast is the TensorZero Gateway?
The TensorZero Gateway achieves less than 1ms p99 latency overhead under extreme load. In benchmarks, LiteLLM at 100 QPS adds 25-100x more latency than TensorZero Gateway at 10,000 QPS.
Do I need to host TensorZero myself?
Yes, TensorZero is open-source and self-hosted. You deploy the gateway yourself and store inference data in your own database (ClickHouse or Postgres optional for observability features).
What databases does TensorZero use?
TensorZero optionally uses ClickHouse for observability and Postgres for observability and advanced features. Valkey/Redis is used for high-performance rate limiting.
Can I do A/B testing with TensorZero?
Yes, TensorZero has built-in experimentation with automatic traffic routing between variants for A/B tests. It supports both static and adaptive A/B tests, ensuring consistent variants within episodes for multi-step workflows.
How does TensorZero handle fallbacks?
The gateway automatically fallbacks failed inferences to different inference providers or completely different variants, ensuring misconfiguration, provider downtime, and edge cases don't affect availability.
What is the quickstart time for TensorZero?
The quickstart shows how to set up a production-ready LLM application with observability and fine-tuning in just 5 minutes.
Who builds TensorZero and who backs them?
TensorZero is built by Aaron Hill, Alan Mishler, Andrew Jesson, Antoine Toussaint, Gabriel Bianconi (CEO), Michelle Hui, and Viraj Mehta (CTO). They are backed by FirstMark, Bessemer, Bedrock, and dozens of angels, with a $7.3M seed round.