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Head-to-head · Prompt Engineering Tools

LangSmith vs DSPy

  • Updated Oct 2026
  • Both researched from official sources
  • 1 check side by side
Higher score LangSmith #1 in Prompt Engineering Tools 9.2/10 Free plan Free plan✓ 0 of 4 features Visit LangSmith
DSPy #8 in Prompt Engineering Tools 7.8/10 Open source ✓ 0 of 4 features Visit DSPy

LangSmith leads on 0 checks, DSPy on 0, and 1 is even. Who comes out ahead on the 1 yes/no, price and count check where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreLangSmith · 9.2/10
  • Free planonly LangSmith

LangSmith scores higher on our rubric for prompt engineering tools: 9.2 against 7.8 out of 10; our editors rank them #1 and #8.

LangSmith is the better fit for teams building with LangChain or LangGraph. DSPy is the better fit for developers automating prompt optimization in code.

  • LangSmith fits best

    Teams building with LangChain or LangGraph

  • DSPy fits best

    Developers automating prompt optimization in code

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Side by side

Feature LangSmith 9.2/10 Visit ↗ DSPy 7.8/10 Visit ↗
At a glance
Editor score 9.2 7.8
Ranking #1 in Prompt Engineering Tools #8 in Prompt Engineering Tools
Best for Teams building with LangChain or LangGraph Developers automating prompt optimization in code
Pricing model Free plan + paid Free
Starting price $39/seat/mo Open source
Free plan ✓ (best) Not checked yet
Free trial — —
Deployment Cloud, Self-hosted Self-hosted
Support Community, Email, Tickets, Docs · 24/7 Community, Docs
Integrations 7 integrations 5 integrations
Built for Solo, Small business, Mid-market, Enterprise Solo, Small business, Mid-market, Enterprise
Features LangSmith 0/4 · DSPy 0/4
Prompt versioning Not checked yet Not checked yet
Prompt playground Not checked yet Not checked yet
Automated evaluations Not checked yet Not checked yet
Prompt optimization Not checked yet Not checked yet
Specs
Model providers Not checked yet Not checked yet
Deployment integrations Not checked yet Not checked yet
Our review
Pros
  • Combines tracing, evaluations, prompt versioning, and monitoring.
  • Supports agent and tool-call tracing alongside human feedback workflows.
  • Offers cloud, hybrid, and self-hosted deployment options.
  • Typed task signatures and composable modules structure AI workflows.
  • GEPA and other optimizers automate prompt improvement.
  • Dataset-based evaluation supports custom metrics and LLM judges.
Cons
  • Developer is limited to one seat and includes community support.
  • Trace use beyond plan allowances incurs pay-as-you-go charges.
  • Enterprise pricing is custom.
  • Self-hosted deployment means teams manage their own runtime.
  • Requires Python development rather than a hosted visual workflow.
  • Community and documentation are the listed support channels.
Our verdict

LangSmith brings development, testing, evaluation, monitoring, and deployment workflows for LLM applications and agents into one platform. It is a natural fit for teams using LangChain or LangGraph, while also supporting applications built…

Read the review →

DSPy is an open-source Python framework for building modular AI systems with language models. Developers define tasks with typed input and output signatures, then combine reusable components such as Predict, ChainOfThought, ReAct, and RAG.…

Read the review →
  1. LangSmithPrompt Engineering Tools 9.2Free plan
  2. DSPyPrompt Engineering Tools 7.8Open source

Strengths and trade-offs

  • LangSmith — where it wins

    • Combines tracing, evaluations, prompt versioning, and monitoring.
    • Supports agent and tool-call tracing alongside human feedback workflows.
    • Offers cloud, hybrid, and self-hosted deployment options.

    Where it doesn't

    • Developer is limited to one seat and includes community support.
    • Trace use beyond plan allowances incurs pay-as-you-go charges.
    • Enterprise pricing is custom.

  • DSPy — where it wins

    • Typed task signatures and composable modules structure AI workflows.
    • GEPA and other optimizers automate prompt improvement.
    • Dataset-based evaluation supports custom metrics and LLM judges.

    Where it doesn't

    • Self-hosted deployment means teams manage their own runtime.
    • Requires Python development rather than a hosted visual workflow.
    • Community and documentation are the listed support channels.
  • LangSmith9.2/10 · Free plan

    A broad LLM workflow platform, especially suited to teams using LangChain or LangGraph.

    Visit LangSmithFull verdict →
  • DSPy7.8/10 · Open source

    Automate prompt optimization in code with typed tasks, reusable modules, and evaluation.

    Visit DSPyFull verdict →

More comparisons

All prompt engineering tools comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update