Google Gemini API vs LangSmith

Google Gemini API

LangSmith

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.

LangSmith · 14 features

• Alerts — Threshold alerts on latency, cost, eval metrics.
• Annotation Queues — Human-review workflows for trace quality rating.
• Custom Dashboards — Aggregate metrics dashboards per project/tag.
• Datasets — Collect examples → use as eval sets or training data.
• Evaluations — LLM-as-judge, embedding similarity, custom Python evaluators, offline batch eval…
• LangChain Integration — Auto-trace any LangChain/LangGraph run with env var.
• LangGraph Integration — First-class trace + eval for LangGraph agents.
• LLM Tracing — Automatic trace every LLM call + tool call + chain step.
• OpenTelemetry Export — Export traces as OTLP to Datadog/Honeycomb/etc.
• Playground — Test prompts + models inline before deploying.
• Prompt Canvas — Visual prompt editor with live test + eval.
• Prompt Hub — Public + private prompt library with versioning.
• Self-Hosted (Enterprise) — Docker + k8s deployment in your infra.
• Threads + Sessions — Group traces into conversational sessions.