Replicate vs LangSmith

Replicate

LangSmith

Replicate · 11 features

• 10k+ Models — Public catalog of image, video, audio, LLM, embedding, speech models.
• Batch Predictions — Parallel batch execution.
• Cog — OSS tool to containerize ML models. Standard for Replicate.
• Deployments — Private model endpoints with dedicated GPUs.
• File Storage — Temporary output file hosting.
• Fine-Tuning — Fine-tune FLUX, SDXL, Llama 2/3 with your data.
• Per-Second Billing — Pay only while model runs. No idle cost for public models.
• Playground — Interactive UI for every public model.
• Predictions API — Async + sync + streaming predictions.
• Streaming Outputs — SSE streaming for LLMs + audio.
• Webhooks — Notify when predictions complete.

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.