Tavily Reliability 2026: When to Stay, When to Switch

A post simply titled "Tavily" surfaced alongside threads about Tavily's Nebius acquisition and API reliability. The community's question is practical: should you stay on Tavily or switch? The answer depends on your workload shape.

What changed after the Nebius acquisition

Nebius acquired Tavily in early 2026. Tavily's pricing remains at $30/month for 4,000 API credits on the Basic plan, with a free tier of 1,000 credits/month. The API surface has not changed post-acquisition. The concern is not current pricing but future direction under Nebius ownership.

When to stay on Tavily

• You use Tavily's built-in content extraction (search + extract in one call)
• Your LangChain codebase uses TavilySearchResults and switching is expensive
• You need the "answer" field (LLM-generated summary alongside results)
• Your volume fits within the free tier (1,000 credits/month)

When to switch

• You need multi-platform search (Reddit, YouTube, Amazon, Walmart) not just Google
• You want raw SERP data without bundled LLM inference
• Your volume exceeds 4K/month and cost per query matters ($0.0075 vs $0.005)
• You want MCP support for Claude Code, Cursor, or other IDE agents

Migration path

# Tavily → Scavio: minimal code change
# Before:
# from tavily import TavilyClient
# client = TavilyClient(api_key="tvly-xxx")
# results = client.search("query")

# After:
import requests
resp = requests.post("https://api.scavio.dev/api/v1/search",
    headers={"x-api-key": "scavio-xxx"},
    json={"query": "query", "platform": "google", "limit": 5})
results = resp.json().get("results", [])

The honest take

Tavily is a solid product. The Nebius acquisition adds uncertainty but has not degraded the service. If Tavily works for you today, switching purely on acquisition anxiety is premature. Switch when you hit a concrete limitation: platform coverage, pricing at scale, or MCP support.