Side-by-Side Comparison · 2026

Haystack vs LiteLLM: Full Comparison (2026)

Haystack is open-source framework for production nlp and rag pipelines. LiteLLM is open-source python library to call 100+ llms with one unified openai-format interface. Use the breakdown below to find the right fit for your needs.

Haystack

deepset

Free
vs

LiteLLM

BerriAI

Free
This page presents factual information sourced from publicly available vendor documentation and product pages. AIHub does not endorse either product. The right tool depends on your specific use case, team, and requirements — we recommend evaluating both tools directly before making a decision.

Side-by-Side Overview

Pricing Model
Haystack: FreeLiteLLM: Free
API Access
Haystack: Not availableLiteLLM: Available
Platforms
Haystack: WebLiteLLM: Python library, Docker (LiteLLM Proxy), Self-hosted server
Integrations
Haystack: —LiteLLM: 7 integrations
Vendor
Haystack: deepsetLiteLLM: BerriAI
Category
Haystack: FrameworksLiteLLM: Frameworks
Launch
Haystack: —LiteLLM: 2023

About Haystack

Haystack by deepset is an open-source framework for building NLP applications, RAG systems, and LLM pipelines. Features a pipeline architecture with 60+ integrations including all major vector databases and LLM providers.

Designed For

  • Document Q&A
  • RAG pipelines
  • Semantic search
  • LLM application development
Full Haystack details

About LiteLLM

LiteLLM is an open-source Python library and proxy server that provides a unified interface to call 100+ large language models using the OpenAI format. It handles provider-specific parameter translation, streaming, token counting, budget management, fallbacks, and load balancing. LiteLLM Proxy runs as a standalone gateway that can be self-hosted, adding observability and cost controls to any LLM backend.

Designed For

  • Unified LLM API abstraction
  • Self-hosted LLM gateway
  • Cost and budget management
  • Multi-provider fallbacks
Full LiteLLM details

Strengths & Limitations

Haystack

Strengths

  • Production-ready
  • 60+ integrations
  • Pipeline architecture

Limitations

  • Steeper learning curve
  • Less popular than LangChain

LiteLLM

Strengths

  • 100+ providers unified
  • OpenAI SDK drop-in replacement
  • Self-hostable proxy
  • Budget limits and alerting
  • Detailed logging/observability
  • MIT license

Limitations

  • Adds complexity for simple use cases
  • Proxy setup requires DevOps
  • Some model-specific features not abstracted

Frequently Asked Questions

What is the difference between Haystack and LiteLLM?

Haystack is open-source framework for production nlp and rag pipelines, while LiteLLM is open-source python library to call 100+ llms with one unified openai-format interface. Haystack is designed for Frameworks; LiteLLM is designed for ML engineers standardizing LLM access, Platform teams building AI gateways. The right fit depends on your specific requirements.

How do the pricing models compare?

Haystack is available under a Free model. LiteLLM is available under a Free model. LiteLLM's entry tier starts at $0. Always verify pricing on each vendor's official website as it may change.

What integrations does each tool support?

Haystack integrates with various tools. LiteLLM integrates with LangChain, LlamaIndex, OpenAI SDK, Anthropic SDK. Check each vendor's documentation for the full and current list.

How do I choose between Haystack and LiteLLM?

Consider your team's technical requirements, budget, existing tooling, and use case before deciding. We recommend signing up for free trials or demos of both tools where available, and consulting each vendor's documentation. AIHub provides this comparison for informational purposes only.