Baseten vs Langfuse
A detailed comparison to help you choose between Baseten and Langfuse.
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Verdict: Langfuse wins
Langfuse scores 4.3/5, edging out Baseten at 4.1/5. Engineering teams running LLM apps or agents in production who want framework-agnostic tracing and evaluation with either a cheap managed cloud or a free self-hosted stack.
Baseten Model inference infrastructure for developers | Langfuse Open-source LLM observability and evaluation | |
|---|---|---|
| Rating | 4.1 (1 review) | 4.3 (1 review) |
| Pricing Model | freemium | freemium |
| Starting Price | Free tier available | Free tier available |
| Best For | ML engineers and platform teams deploying custom or fine-tuned models to production who want autoscaling GPUs and code-owned deployment artifacts. | Engineering teams running LLM apps or agents in production who want framework-agnostic tracing and evaluation with either a cheap managed cloud or a free self-hosted stack. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | free tierapi access | free tieropen sourceapi access |
| Visit Baseten → | Visit Langfuse → |
Baseten
Pros
- + Truss packaging (weights + model.py + config.yaml) gave me a deployable endpoint I could version in git like any other service
- + Scale-to-zero is real: my idle test endpoint stopped billing entirely between requests
- + Rolling deployments kept the old replica serving during promotion — zero dropped requests in my test
- + SOC 2 Type II and HIPAA compliance included on the base tier (baseten.co/pricing)
- + Per-minute GPU pricing is published: H100 80GB at $0.10833/min, T4 from $0.63/hr at time of writing (inferencehub.org)
Cons
- - An always-on H100 replica at list computes to roughly $4,680/month — min_replica choices dominate your bill
- - Model APIs cover open-weight models only (17 as of October 2026); no GPT or Claude access
- - Dedicated compute, priority GPU access, and higher rate limits require the Pro tier
- - Self-hosting, data residency, and custom SLAs are Enterprise-only
- - No path for non-engineers: everything assumes you can package a model and reason about replicas
Langfuse
Pros
- + MIT-licensed core with free, unrestricted self-hosting — only named enterprise features like audit logs and SCIM need a licence key
- + A 5-seat team at 100k traces runs roughly $69/month versus about $420/month for the main closed alternative (Panoply's independent estimate, consistent with my bills)
- + OpenTelemetry-native tracing across OpenAI SDK, LangChain, LlamaIndex, Pydantic AI, Vercel AI SDK, CrewAI and raw OTLP
- + Graduated usage pricing is transparent and cheap: worked examples on the pricing page match my own invoices (200k units on Core = $37/month)
- + Dataset-backed evaluation with the langfuse/experiment-action GitHub step let me gate prompt changes in CI on a real test set
Cons
- - v3 self-hosting needs Postgres, ClickHouse, Redis and S3 where v2 ran on one container — a four-service system to operate
- - Heavy agent traces render slowly in the UI (issue threads #10391 and #9933 match the multi-second loads I measured)
- - Online evaluations score a sample of traffic rather than everything, so rare failure modes can go unscored
- - UI-configured evaluators cannot be triggered programmatically for scheduled pipelines in my setup
- - Owned by ClickHouse, Inc. since January 2026 — licence unchanged so far, but the vendor-independence profile shifted
Frequently Asked Questions
Which is better, Baseten or Langfuse?▼
Langfuse scores higher at 4.3/5 vs 4.1/5 for Baseten, making it the better-rated option in our comparison.
What is the difference between Baseten and Langfuse?▼
Baseten: Baseten hosts and scales machine learning models in production, serving open-source and custom models behind an API. Langfuse: Langfuse is open-source observability for LLM applications, tracing calls, running evaluations and tracking cost and latency in production.
Is Baseten or Langfuse more affordable?▼
Baseten starts at €0/mo, Langfuse starts at €0/mo. Check the comparison table above for current pricing.
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