Net::HTTP vs Faraday for Ruby LLM API clients

Building a Ruby client for LLM inference APIs means choosing an HTTP layer. The trade-off in net::http vs faraday ruby llm clients is between zero-dependency control and composable middleware. Both can hit an OpenAI-compatible endpoint, but they shape your error handling, retry logic, and streaming code differently.

Capabilities

When evaluating net::http vs faraday ruby llm clients, capability gaps appear mainly in middleware and streaming wrappers. Net::HTTP ships with Ruby. It exposes raw request construction, giving you precise control over headers, body streaming, and socket timeouts. For LLM completions that return token streams, you read the response body incrementally:

require 'net/http'
uri = URI('https://api.example.com/v1/chat/completions')
req = Net::HTTP::Post.new(uri)
req['Content-Type'] = 'application/json'
req['Authorization'] = "Bearer #{ENV['KEY']}"
req.body = { model: 'gpt-4o', messages: [{ role: 'user', content: 'hi' }], stream: true }.to_json
Net::HTTP.start(uri.host, uri.port, use_ssl: true) do |http|
  http.request(req) do |res|
    res.read_body { |chunk| print chunk }
  end
end

Faraday wraps the transport behind a unified interface. It supports the same streaming via on_data callbacks but adds a middleware pipeline. You define adapters (default uses Net::HTTP under the hood) and stack request/response middleware.

require 'faraday'
conn = Faraday.new(url: 'https://api.example.com') do |f|
  f.request :json
  f.response :logger
  f.adapter :net_http
end
conn.post('/v1/chat/completions') do |req|
  req.headers['Authorization'] = "Bearer #{ENV['KEY']}"
  req.body = { model: 'gpt-4o', messages: [{ role: 'user', content: 'hi' }], stream: true }
  req.options.on_data = proc { |chunk, _| print chunk }
end

Faraday’s edge is declarative resilience: retry, circuit breakers, and auth injection become middleware. Net::HTTP forces you to write that logic inline or build your own wrapper.

Price/Cost Model

Neither library costs money; both are open-source. The financial surface is LLM provider billing. Token metering is independent of HTTP client. Some gateways, including n4n.ai, expose an OpenAI-compatible endpoint with per-token usage metering and automatic fallback when a provider is degraded, letting either client benefit without custom code.

Net::HTTP has no built-in telemetry. You must parse usage fields from JSON and ship them to your own metrics. Faraday can extract that via a custom response middleware that logs json['usage'] to StatsD or Prometheus.

Latency/Throughput

Raw Net::HTTP adds minimal per-request overhead. Its default Net::HTTP.start opens a new TCP/TLS connection per block unless you cache the connection object. For high-throughput LLM batch jobs, reuse a persistent connection or use net-http-persistent.

Faraday introduces a thin middleware chain cost—typically sub-millisecond per request—but its default adapter also uses Net::HTTP. You can swap to faraday-net_http_persistent or typhoeus for parallel calls. In practice, LLM inference time dwarfs client overhead; a 200ms token stream is unaffected by a 0.2ms middleware hop.

For streaming throughput, both rely on the underlying socket. Net::HTTP gives the raw read_body loop; Faraday’s on_data proc is equivalent but adds a layer of proc dispatch.

Ergonomics

Net::HTTP reads like verbose Java. You build URI, request, set headers, start connection, handle response. Error classes (Net::ReadTimeout, Net::HTTPBadResponse) are explicit but you must rescue them per call.

Faraday reads like a DSL. conn.get('/models') returns a Faraday::Response with #status, #body, #headers. JSON encoding/decoding is one line via request :json and response :json. For Rails apps where developers expect convention, Faraday reduces cognitive load.

begin
  resp = conn.post('/v1/chat/completions') { |r| r.body = payload }
  resp.success? ? resp.body : raise("API #{resp.status}")
rescue Faraday::TimeoutError => e
  retry unless tries > 3
end

Net::HTTP equivalent needs explicit res.is_a?(Net::HTTPSuccess) and rescue Net::OpenTimeout, Net::ReadTimeout.

Ecosystem

Net::HTTP is part of stdlib. No Gemfile entry, no version conflicts, upgrades with Ruby. That matters in locked-down enterprise environments.

Faraday has a rich gem ecosystem: faraday-retry, faraday-circuit_breaker, and adapter gems for HTTPX, Patron, Curb. If you already use Faraday for other services, standardizing LLM calls on it reduces context switching.

The cost is dependency bloat. Faraday 2.x requires faraday-net_http as separate gem for default adapter. A fresh install pulls 3–4 gems. For a lambda function with size limits, that matters.

Limits

Net::HTTP’s defaults are dangerous: open_timeout is 60s, read_timeout is 60s, but no total timeout. Streaming a slow LLM can hang a thread. You must set http.read_timeout = 30 explicitly.

It also lacks built-in retry or idempotency controls. If a provider returns 429, you write the backoff.

Faraday abstracts the adapter, which can leak. If you rely on response :json but the API returns a 502 with HTML, the middleware raises Faraday::ParsingError instead of giving you the raw body. You must configure response :json, content_type: 'application/json' and handle parse failures.

Version drift is another limit: Faraday 1.x and 2.x have different middleware APIs. Upgrading a large app can break custom middleware.

Comparison Table

Which to Choose

Single-file scripts or AWS Lambda with tight gem limits. Use Net::HTTP. You avoid dependency packaging and control exactly what bytes go out. Wrap it in a small LLMClient class with a post_stream method.

Rails application with multiple external APIs. Use Faraday. Standardize on one connection builder, add faraday-retry with exponential backoff, and log requests via faraday-logger. Your LLM calls inherit the same resilience as your payment gateway calls.

High-throughput batch inference (thousands of prompts). Either works if you enable persistent connections. Net::HTTP with a class-level @http instance is lean. Faraday with faraday-net_http_persistent gives you middleware for free. Benchmark your own workload; the difference is negligible versus provider latency.

Custom middleware needs (e.g., provider cache-control headers, token metering). Faraday wins. Write a RequestCacheHeader middleware that injects cache-control: max-age=300 for eligible models. Net::HTTP would require monkey-patching or repetitive header setting.

Teams new to Ruby or LLM integrations. Faraday’s ergonomics reduce bugs. The explicit failure modes of Net::HTTP punish newcomers with hung threads.

The net::http vs faraday ruby llm decision is not about performance—it is about how much scaffolding you want to write versus inherit. Pick the one that matches your operational maturity.