Lists / llm observability / Head to head
LangSmith vs Langfuse (2026): What ChatGPT, Claude & Gemini Say
LangSmith is named in 50 of 50 AI answers. Langfuse is named in 48 and put first in 25. Model-by-model counts from a 50-answer, 10-model panel.
AI models name LangSmith a little more often, and they put Langfuse first far more often. LangSmith appears in 50 of 50 recorded answers and comes first in 8. Langfuse appears in 48 of 50 and comes first in 25. Both sit on nearly every shortlist, so the real split is which one an answer leads with. These counts measure what AI answers name. They say nothing about which product is better.
TL;DR
- Pick by first mention and Langfuse leads: 25 of 50 answers open with it, against 8 for LangSmith.
- Pick by coverage and LangSmith leads: every one of the ten models names it in all 5 of its answers.
- ChatGPT is the one model that drops Langfuse. It names Langfuse in 3 of 5 answers and LangSmith in 5 of 5.
- The answers attach a condition to LangSmith (a LangChain or LangGraph stack) and offer Langfuse as the default, open-source or self-hosted pick.
- On the captured directory pages, Langfuse shows a free tier, paid plans and self-hosting. No price is shown for LangSmith.
How often do AI models recommend LangSmith and Langfuse?
LangSmith is named more often and Langfuse is named first more often. The table holds both products’ full measured line for the 2026-09 edition.
| Product | Named | Answer share | Named first | First share | Average position | Category rank |
|---|---|---|---|---|---|---|
| LangSmith | 50/50 | 100% | 8/50 | 16% | 2.56 | 1 of 13 |
| Langfuse | 48/50 | 96% | 25/50 | 50% | 1.96 | 2 of 13 |
Answer share is the share of the 50 answers that named the product. First share is the share where it appeared before any other tracked product. LangSmith is the category leader on named count, so the table needs no separate reference row.
The gap between the two sits in the lead slot. LangSmith’s named share runs 84 points above its first share. Langfuse’s gap is 46 points. LangSmith is the product an answer almost never leaves out, and its average position of 2.56 puts it between second and third place. Langfuse is the product an answer most often opens with. A buyer who reads only the top line of each answer meets Langfuse far more often. A buyer who reads the whole list meets LangSmith every time.
Which models prefer LangSmith, and which prefer Langfuse?
On counts, no model names Langfuse more than LangSmith. Every model names LangSmith in all 5 of its answers, and nine of the ten do the same for Langfuse. The preference shows in which product each model leads with, and that varies sharply by model.
| Model | LangSmith named | Langfuse named | What its answers lead with |
|---|---|---|---|
| GPT-5.6 Sol | 5/5 | 5/5 | Braintrust as the default, with LangSmith first in its comparison shortlist |
| ChatGPT | 5/5 | 3/5 | Split: LangSmith on some prompts, Langfuse on others |
| GPT-5.6 Luna | 5/5 | 5/5 | Braintrust, Arize Phoenix or LangSmith, depending on the prompt |
| Claude Opus 5 | 5/5 | 5/5 | A warning about vendor-written lists, then Langfuse for teams starting out |
| Claude | 5/5 | 5/5 | Langfuse as the general default |
| Claude Fable 5 | 5/5 | 5/5 | Langfuse as the default for most engineers |
| Gemini | 5/5 | 5/5 | Categories, with Langfuse heading its open-source pick |
| Gemini 3.5 Flash | 5/5 | 5/5 | Categories, with no single default |
| Perplexity | 5/5 | 5/5 | Langfuse or Confident AI, with LangSmith for LangChain stacks |
| Sonar Reasoning Pro | 5/5 | 5/5 | Langfuse or Confident AI, with LangSmith for LangChain stacks |
ChatGPT is the sharpest case. It is the only model below 5 of 5 for Langfuse (Langfuse 60% of ChatGPT answers). The ChatGPT answers that leave Langfuse out are the same answers that name LangSmith as the default. Asked what it would recommend, or what an AI engineer should use, ChatGPT opens with Langfuse. The wording of the question moves ChatGPT’s lead from one product to the other.
The Anthropic models lean the other way. Claude and Claude Fable 5 open with Langfuse as the default. Claude Opus 5 opens most answers with a warning that many ranked lists are published by vendors, and names Langfuse as the common default for teams starting out.
Two OpenAI models point past both products. GPT-5.6 Sol leads with Braintrust on most prompts, and GPT-5.6 Luna spreads its default across Braintrust, Arize Phoenix and LangSmith. Both still name LangSmith and Langfuse in every answer.
By family, the pattern holds. Langfuse (86.7% of OpenAI-family answers) is the only gap in either product’s coverage. Langfuse (100% of Anthropic, Google and Perplexity answers) matches LangSmith everywhere else.
What do the answers say about each?
The answers praise LangSmith with a condition attached and offer Langfuse as a default. Four short quotes from the recorded answers show both sides.
- ChatGPT, asked for the best platform by name: “Best default for most AI engineers: LangSmith.”
- ChatGPT again, asked what it would recommend in 2026: “My default recommendation in 2026: Langfuse.”
- GPT-5.6 Luna, after naming another default: “Choose LangSmith instead if your stack is heavily based on LangChain/LangGraph and you want the smoothest integrated development workflow.”
- Claude, in its recommendation matrix: “If you want the safest default for most teams: Langfuse.”
The first pair comes from one model on neighbouring prompts, so one ChatGPT answer is weak evidence for either product. The Luna quote shows the usual LangSmith framing: named, then tied to a LangChain or LangGraph stack.
How do LangSmith and Langfuse differ?
The captured directory pages separate them on maker, price and deployment. The AI answers separate them on stack.
Maker. SourceForge lists LangSmith under LangChain, based in the United States. SourceForge lists Langfuse as its own company, based in Germany.
Pricing model. Slashdot shows no price information for LangSmith. SourceForge marks LangSmith’s free version and free trial as not supported. Slashdot’s Langfuse listing describes a free tier and paid Pro plans. The same listing says Langfuse is open source and can be self-hosted at no cost. Neither captured page records a LangSmith price.
Deployment. SourceForge marks LangSmith as cloud only, with on-premises not supported. It marks Langfuse as supported in the cloud and on-premises.
Who each is for. SourceForge describes LangSmith’s audience as “Developers seeking a platform to design, build, and test their applications”. It describes Langfuse’s audience as “Software Engineers, AI Engineers, Data Scientists, Product Managers”.
What each is named for. SourceForge’s LangSmith entry compares it to unit testing and says “LangSmith provides that same functionality for LLM applications.” Slashdot calls Langfuse “a free and open-source LLM engineering platform”. The AI answers follow the same line. They name LangSmith for LangChain and LangGraph work and Langfuse for open-source, self-hosted or framework-neutral setups.
When should you pick LangSmith?
Pick LangSmith if your application runs on LangChain or LangGraph. The answers tie it to that stack again and again, and SourceForge lists LangChain and LangGraph as supported LangSmith integrations.
- Every model names it in every answer: 50 of 50, with all ten models at 5 of 5.
- Named count puts it first in the category, so any AI shortlist a colleague pulls up will carry it.
- ChatGPT picks it on the prompts where ChatGPT names one default and leaves Langfuse out.
- SourceForge lists it as a cloud product.
Where LangSmith leads: coverage. Where it trails: the lead slot, with 8 of 50 first mentions and an average position of 2.56.
When should you pick Langfuse?
Pick Langfuse if you need to self-host or want to start free. SourceForge marks it as supported on-premises as well as in the cloud.
- Answers open with it in 25 of 50 cases, against 8 for LangSmith.
- An average position of 1.96 is the lowest of the 13 products named, so it tends to appear earliest.
- Every Anthropic, Google and Perplexity model names it in all 5 of its answers.
- Its Slashdot listing shows a free tier to start on.
- A mixed stack fits the listing’s claim that Langfuse is agnostic to models and frameworks.
Where Langfuse leads: first mentions and average position. Where it trails: ChatGPT, which names it in 3 of 5 answers.
How this sits against the LangSmith vs Langfuse guides
The readable comparison pages for this query are software-directory listings. They compare listing fields. The panel counts what AI answers name.
Slashdot. The page offers to compare the two “by cost, reviews, features, integrations, deployment, target market, support options, trial offers, training options, years in business, region, and more”. It shows no user ratings for LangSmith and a single rating for Langfuse. Its “Similar Products” rail carries “Learn More” links to other vendors’ sites. The site links to its own “Software Advertising Options”. Each product listing invites the vendor to “Claim This Page”. No affiliate disclosure appears in the captured text.
SourceForge. The page is a three-way chart of LangSmith, Langfuse and Portkey. Its LangSmith description reads in the vendor’s own voice: “We’re establishing best practices you can rely on.” Each column invites the vendor to claim the listing and update its features. The only user review on the page is for Langfuse. That reviewer names self-hosting as the weak point: “self hosting was difficult”.
Both directory pages rest on vendor-maintained listings and thin reviews. Neither says how often AI models name either product, and neither reports which model leans which way.
How the sample was built
The panel is 10 models x 5 fixed prompts = 50 recorded answers, for the 2026-09 edition. Each model answered each prompt once. The five prompts, verbatim:
- What is the best LLM observability and evaluation platform for an AI engineer? Name specific products.
- Which LLM observability and evaluation platform would you recommend to an AI engineer in 2026?
- Compare the top LLM observability and evaluation platform options right now.
- I’m an AI engineer and I need a LLM observability and evaluation platform. What should I use and why?
- Best LLM observability and evaluation platform for tracing and evals in production?
The models by family: OpenAI (GPT-5.6 Sol, ChatGPT, GPT-5.6 Luna), 15 answers. Anthropic (Claude Opus 5, Claude, Claude Fable 5), 15 answers. Google (Gemini, Gemini 3.5 Flash), 10 answers. Perplexity (Perplexity, Sonar Reasoning Pro), 10 answers. The category tracks 17 vendors, and 13 were named. The full answer set and per-model split sit on the LLM observability category record. The counting rules are on the method page.
What these counts cannot tell you
The counts measure presence in AI answers. They do not measure product quality, uptime, support, adoption or fit with a particular stack. Being named differs from being recommended, and an answer can name a product only to set it aside. Each model answered each prompt once, so one reworded question can move a lead, as ChatGPT shows. The figures are one dated snapshot from the 2026-09 edition. Names are matched as text, including known aliases. Answers came through model APIs, which can differ from the consumer chat apps. The prompts are in English. The directory facts come from vendor-maintained listings and can lag the vendors’ own pages. No vendor can pay to appear, be reordered or be removed.
Frequently asked questions
Is Langfuse part of LangChain?
No. SourceForge lists Langfuse as its own company, based in Germany. It lists LangSmith under LangChain. The AI answers treat Langfuse as the framework-neutral option and LangSmith as the LangChain-native one.
What are the key differences between LangSmith and LangGraph?
The captured pages list LangGraph without describing what it does. LangGraph is not one of the observability products this panel tracks, so it has no count. In the answers, LangGraph appears as the stack that points a model toward LangSmith.
What are the key differences between LangSmith and MLflow?
On the counts, LangSmith is named in 50 of 50 answers and MLflow in 15 (MLflow 30%). MLflow is named first once and averages position 6.27. No OpenAI model names MLflow. Claude Opus 5 and Sonar Reasoning Pro each name it in 4 of 5 answers. Sonar Reasoning Pro ties each product to its own ecosystem, pointing LangChain users to LangSmith and MLflow users to MLflow.
What are some alternatives to LangSmith for LLMs?
The products the models name most after LangSmith are Langfuse (48 of 50 answers), Arize (47), Braintrust (46) and Confident AI (34). Langfuse is the only one named first in more answers than LangSmith. The full list with every count is on the category record.
Which one does ChatGPT recommend?
ChatGPT splits. It names LangSmith in all 5 answers and Langfuse in 3 of 5. On some prompts it calls LangSmith the best default. On others it opens with Langfuse. The prompt wording decides which one leads.