Langfuse vs Google Gemini API
Open-source LLM engineering platform — observability, prompts, evals
vs. Gemini 2.5 Pro, Flash, Flash-Lite — multimodal + 2M context
Pricing tiers
Langfuse
Hobby (Cloud Free)
Free. 50k units/month included. 30 days data access. 2 users. Community support.
Free
Self-Hosted (OSS)
MIT-licensed. Docker Compose or Kubernetes deployment. Unlimited.
$0 base (usage-based)
Core
$29/month. 100k units included ($8 per 100k overage). 90 days retention. Unlimited users. In-app support.
$29/mo
Pro
$199/month. 100k units included + same overage. 3 YEARS retention. Unlimited annotation queues. High rate limits.
$199/mo
Teams Add-on
+$300/month. Adds Enterprise SSO + fine-grained RBAC + dedicated Slack support to Pro.
$300/mo
Enterprise
$2,499/month. Everything + custom rate limits, uptime SLA, dedicated support engineer. Yearly options.
$2499/mo
Google Gemini API
Free Tier (AI Studio)
Generous free tier with rate limits. Good for dev + prototyping. Data may be used to improve Google products.
Free
Paid API (Gemini API)
Pay-as-you-go per-token. Data NOT used for training.
$0 base (usage-based)
Vertex AI (GCP)
Enterprise deployment via Google Cloud. Same pricing structure + GCP features (IAM, VPC-SC, CMEK).
$0 base (usage-based)
Gemini Enterprise
Custom. Gemini 2.5 Deep Think model access + Google Workspace + Agentspace.
Custom
Free-tier quotas head-to-head
Comparing hobby on Langfuse vs free-tier on Google Gemini API.
| Metric | Langfuse | Google Gemini API |
|---|---|---|
| No overlapping quota metrics for these tiers. | ||
Features
Langfuse · 16 features
- Annotation Queues — Human reviewers rate traces. Unlimited on Pro+.
- Dashboards — Aggregate metrics, cost, quality across projects.
- Datasets — Curate test sets from production traces. Run experiments.
- EU Cloud Region — GDPR-compliant hosting in EU.
- Evaluations — LLM-as-judge, manual scores, custom model-graded evaluators.
- LLM Cost Tracking — Automatic cost calculation per provider/model.
- OpenTelemetry Native — OTel SDK → Langfuse endpoint works out of box.
- Playground — Test prompts + models + variables live.
- Prompt Management — Version, tag, label prompts. Reference from code by label.
- Public API — Full REST API for ingest, query, prompt management.
- Python @observe decorator — One-line decorator to trace any function.
- Self-Hosting — Docker Compose + k8s Helm chart.
- Sessions — Group related traces (conversations, agent runs).
- Tracing — Capture every LLM call, tool call, nested span with inputs/outputs/cost.
- Users Tracking — Segment traces by user ID, track per-user cost.
- Webhooks — Subscribe to trace completion events.
Google Gemini API · 11 features
- Batch API — 50% discount for async processing.
- Code Execution — Python code interpreter tool (sandboxed).
- Context Caching — Cache system instructions + tools for up to 90% savings.
- File API — Upload large files (up to 2 GB) for multimodal prompts.
- Function Calling — JSON schema-based tool calling. Parallel supported.
- generateContent API — Core generation endpoint.
- Grounding with Search — Augment answers with Google Search results. Fact-checked citations returned.
- Model Tuning — Supervised fine-tuning via AI Studio.
- Multimodal Live API — Bidirectional streaming voice + video (WebSocket).
- Safety Settings — Configurable thresholds for harm categories.
- streamGenerateContent — Streaming variant with SSE.
Developer interfaces
| Kind | Langfuse | Google Gemini API |
|---|---|---|
| SDK | langfuse-js, langfuse-python | @google/genai, google-genai-go, google-genai (Python) |
| REST | Langfuse REST API | Gemini REST API, Vertex AI Endpoint |
| MCP | Langfuse MCP Server | Gemini MCP |
| OTHER | Langfuse Dashboard, OpenTelemetry endpoint | — |
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