Home/Compare/arthur-engine vs ai-gateway

Comparison

arthur-engine vs ai-gateway

Verdict

Pick arthur-engine if the Arthur Engine monitors AI/ML workloads with a focus on guardrails for LLM applications, evaluation of agentic systems, extensive model monitoring metrics, and extensible API support; pick ai-gateway if ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production.

Markdown twin · arthur-engine alternatives · ai-gateway alternatives

GraphCanon updated Sep 20, 2026

arthur-engine logo

arthur-engine

arthur-ai/arthur-engine

89pushed Sep 12, 2026
vs
ai-gateway logo

ai-gateway

ferro-labs/ai-gateway

256pushed Sep 10, 2026

Trust & integrity

Signalarthur-engineai-gateway
Maintenance
Very active (0d since push)
As of Sep 12, 2026 · github_public_v1
Very active (2d since push)
As of Sep 12, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 12, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 12, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 15, 2026 · osv@v1
Published findings
As of Jul 15, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

arthur-engine
Monitoring and governing for your AI/ML
ai-gateway
Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls

Stars

arthur-engine
89
ai-gateway
256

Forks

arthur-engine
16
ai-gateway
35

Open issues

arthur-engine
16
ai-gateway
68

Language

arthur-engine
Python
ai-gateway
Go

Adopt for

arthur-engine
The Arthur Engine monitors AI/ML workloads with a focus on guardrails for LLM applications, evaluation of agentic systems, extensive model monitoring metrics, and extensible API support.
ai-gateway
ai-gateway from Ferro Labs supports over 30 LLMs with integrated caching, guardrails, A/B testing, and cost controls, making it ideal for managing multiple language models in a production environment.

Persona

arthur-engine
-
ai-gateway
-

Runtime

arthur-engine
-
ai-gateway
-

License

arthur-engine
MIT License, allowing free use and modification of the tool's codebase under the terms of this license.
ai-gateway
Apache-2.0 - a permissive free software license

Last pushed

arthur-engine
Sep 12, 2026
ai-gateway
Sep 10, 2026

Categories

arthur-engine
Evaluation & Observability, Model Training
ai-gateway
Inference & Serving, Model Training

Trust and health

Days since push

arthur-engine
0d
ai-gateway
2d

Open issues (now)

arthur-engine
16
ai-gateway
68

Stars delta

arthur-engine
+3 (30d)
ai-gateway
+37 (30d)

Open issues delta

arthur-engine
-16 (30d)
ai-gateway
+5 (30d)

OSV dependency advisories

arthur-engine
No lockfile (source not queried)
ai-gateway
Published findings

Full report

arthur-engine
Trust report
ai-gateway
Trust report

Choose arthur-engine if…

  • arthur-engine is primarily Python; ai-gateway is Go.
  • License: arthur-engine is MIT, ai-gateway is Apache-2.0.
  • Tags unique to arthur-engine: agentic, benchmarking, evaluation, genai.
  • Also covers Evaluation & Observability.
  • When developing or managing large language models that require real-time detection of sensitive data leakage, hallucination, or prompt injection.

When NOT to use arthur-engine

  • Avoid if the project does not require real-time monitoring and evaluation on live data streams.
  • Not suitable for teams that prefer minimalistic setups over comprehensive services with wide-ranging capabilities.
  • It may be overkill for organizations focused exclusively on model training without subsequent need for ongoing monitoring or governance.

Choose ai-gateway if…

  • ai-gateway is primarily Go; arthur-engine is Python.
  • License: ai-gateway is Apache-2.0, arthur-engine is MIT.
  • Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy.
  • Also covers Inference & Serving.
  • When you need to integrate more than 30 different LLM services including OpenAI and Anthropic

When NOT to use ai-gateway

  • If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features
  • For small-scale projects that do not require comprehensive cost analysis tools
  • When custom integration for specific guardrails is required, as ai-gateway offers generalized settings

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: arthur-engine 89 · ai-gateway 256 (synced Sep 20, 2026).

Common questions

What is the difference between arthur-engine and ai-gateway?
arthur-engine: Monitoring and governing for your AI/ML. ai-gateway: Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls. See the comparison table for live GitHub stats and shared categories.
When should I choose arthur-engine over ai-gateway?
Choose arthur-engine over ai-gateway when arthur-engine is primarily Python; ai-gateway is Go; License: arthur-engine is MIT, ai-gateway is Apache-2.0; Tags unique to arthur-engine: agentic, benchmarking, evaluation, genai; Also covers Evaluation & Observability; When developing or managing large language models that require real-time detection of sensitive data leakage, hallucination, or prompt injection.
When should I choose ai-gateway over arthur-engine?
Choose ai-gateway over arthur-engine when ai-gateway is primarily Go; arthur-engine is Python; License: ai-gateway is Apache-2.0, arthur-engine is MIT; Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy; Also covers Inference & Serving; When you need to integrate more than 30 different LLM services including OpenAI and Anthropic.
When should I avoid arthur-engine?
Avoid if the project does not require real-time monitoring and evaluation on live data streams. Not suitable for teams that prefer minimalistic setups over comprehensive services with wide-ranging capabilities. It may be overkill for organizations focused exclusively on model training without subsequent need for ongoing monitoring or governance.
When should I avoid ai-gateway?
If your project only involves one or two LLMs which does not necessitate the gateway's broad compatibility features For small-scale projects that do not require comprehensive cost analysis tools When custom integration for specific guardrails is required, as ai-gateway offers generalized settings
Is arthur-engine or ai-gateway more popular on GitHub?
ai-gateway has more GitHub stars (256 vs 89). Stars measure visibility, not whether either tool fits your constraints.
Are arthur-engine and ai-gateway open source?
Yes - both are open-source projects on GitHub (arthur-engine: MIT, ai-gateway: Apache-2.0).
Where can I find alternatives to arthur-engine or ai-gateway?
GraphCanon lists graph-backed alternatives at arthur-engine alternatives and ai-gateway alternatives (arthur-engine markdown twin, ai-gateway markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, arthur-engine or ai-gateway?
arthur-engine: Very active. ai-gateway: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for arthur-engine and ai-gateway?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: arthur-engine trust report; ai-gateway trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.