Comparison · updated 2026-05-17

Synthorai vs LiteLLM

Different categories of tool that solve overlapping problems. LiteLLM is an open-source Python library (and a proxy server) for unifying provider APIs. Synthorai is a managed HTTP gateway with billing, BYOK key vault, and team management built in. Here's when each fits.

TL;DR

• Pick LiteLLM if you're building a Python app, want to read the routing code, need to run inside your own VPC, or care about the largest possible provider catalogue. Free as in beer (just pay providers).
• Pick Synthorai if you want billing + Stripe checkout + audit logs working out of the box, your team isn't Python-only, and you'd rather buy than build the quota / multi-tenant / billing layer.
• Use both — point LiteLLM proxy at Synthorai as one of its model providers. You get LiteLLM's Python ergonomics and Synthorai's managed billing.

Feature-by-feature

Where Synthorai genuinely wins

• Billing layer is included. Stripe checkout, top-up flow, per-workspace quota, BYOK surcharge calculation, refund on crash — all working. With LiteLLM you build this yourself or adopt LiteLLM Cloud (which is the same managed shape).
• Crash-safe billing pattern. The inflight ZSET pattern (post) guarantees quota correctness across crashes. LiteLLM relies on whichever storage backend you wire it to; if you use Postgres, you're responsible for the crash recovery story.
• Workspace management UI for non-engineers — a finance person can see usage breakdown, top up, refund without touching code or Helm charts.
• Less to operate. No proxy server to deploy, no Postgres to maintain, no Redis to size.

Where LiteLLM genuinely wins

• Open source — full audit + customisation. Compliance team can read the code. Want to add a custom provider? Just write a Python class. Want a wildcard callback for every LLM call? litellm.success_callback = [...] and ship.
• VPC / on-prem deployment. Some customers (regulated industries, EU public sector) cannot send prompts to a third-party gateway. LiteLLM runs inside their network. Synthorai is managed-only today; self-hosted is on the roadmap but not shipping.
• Python-first ergonomics. litellm.completion(model="gpt-5", messages=[...]) is the natural call shape for a Python app. Our HTTP API works from Python too but feels foreign compared to importing a library.
• Massive provider catalogue. 200+ providers, including edge cases like Together AI's image models, Replicate, Sagemaker endpoints. We curate to ~50 and cover the major ones well.
• Observability ecosystem. LiteLLM has first-class integrations with Langfuse, Helicone, Datadog, Prometheus, Slack — you can fan out to whatever observability stack you already run. Our story is more opinionated (logs + Prometheus, structured audit log).

Using both together

This is the most common real-world setup. Point LiteLLM at Synthorai as a provider:

# litellm_config.yaml
model_list:
  - model_name: claude-via-synthorai
    litellm_params:
      model: anthropic/claude-sonnet-4-6
      api_base: https://synthorai.io/v1
      api_key: os.environ/SYNTHORAI_KEY

Then call litellm.completion(model="claude-via-synthorai", ...). You get LiteLLM's Python ergonomics + callback ecosystem; Synthorai does the billing, quota, audit trail.

Migration steps (LiteLLM → Synthorai-only)

1. Sign up + top up. $50 launch promo gets you 10% off all models for 30 days.
2. Swap base URL. Most code that uses litellm.completion() via the OpenAI proxy can switch by changing two env vars:

   OPENAI_BASE_URL=https://synthorai.io/v1
   OPENAI_API_KEY=sk-syn-...

3. Move BYOK provider keys from .env / config to the Vault UI. One per provider per workspace.
4. Replace LiteLLM callbacks with whichever subset we cover (Prometheus + audit logs). If you depended on something we don't have (e.g. Helicone), keep LiteLLM in the middle.

Comparison written 2026-05-17. LiteLLM moves fast; if anything here is out of date, email support@synthorai.io.