Comparison
distributed-llama vs ai-gateway
Verdict
Pick distributed-llama if distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license; 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 environment.
Markdown twin · distributed-llama alternatives · ai-gateway alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | distributed-llama | ai-gateway |
|---|---|---|
| Maintenance | Active (19d since push) As of 3w · github_public_v1 | Very active (2d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Organization account As of 1w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · 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
- distributed-llama
- Distributed LLM inference using home devices cluster
- ai-gateway
- Unified AI Gateway for multiple LLMs with caching, guardrails, A/B testing, and cost controls
Stars
- distributed-llama
- 3.0k
- ai-gateway
- 219
Forks
- distributed-llama
- 242
- ai-gateway
- 33
Open issues
- distributed-llama
- 48
- ai-gateway
- 63
Language
- distributed-llama
- C++
- ai-gateway
- Go
Adopt for
- distributed-llama
- distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license.
- 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
- distributed-llama
- -
- ai-gateway
- -
Runtime
- distributed-llama
- -
- ai-gateway
- -
License
- distributed-llama
- MIT
- ai-gateway
- Apache-2.0 - a permissive free software license
Last pushed
- distributed-llama
- Jul 5, 2026
- ai-gateway
- Aug 7, 2026
Categories
- distributed-llama
- Inference & Serving
- ai-gateway
- Inference & Serving, Model Training
Trust and health
Maintenance
- distributed-llama
- Active (82%)
- ai-gateway
- Very active (96%)
Days since push
- distributed-llama
- 19d
- ai-gateway
- 2d
Open issues (now)
- distributed-llama
- 48
- ai-gateway
- 63
Owner type
- distributed-llama
- User
- ai-gateway
- Organization
OSV dependency advisories
- distributed-llama
- No lockfile (source not queried)
- ai-gateway
- Published findings
Full report
- distributed-llama
- Trust report
- ai-gateway
- Trust report
Choose distributed-llama if…
- distributed-llama is primarily C++; ai-gateway is Go.
- License: distributed-llama is MIT, ai-gateway is Apache-2.0.
- Tags unique to distributed-llama: distributed-computing, llm-inference, neural-network.
- When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks.
When NOT to use distributed-llama
- For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited.
- In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices.
Choose ai-gateway if…
- ai-gateway is primarily Go; distributed-llama is C++.
- License: ai-gateway is Apache-2.0, distributed-llama is MIT.
- Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy.
- Also covers Model Training.
- 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 (b4rtaz/distributed-llama) · observed Jul 25, 2026
- GitHub forks (b4rtaz/distributed-llama) · observed Jul 25, 2026
- Last push (b4rtaz/distributed-llama) · observed Jul 5, 2026
- License file (MIT) · observed Jul 25, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ferro-labs/ai-gateway) · observed Aug 9, 2026
- GitHub forks (ferro-labs/ai-gateway) · observed Aug 9, 2026
- Last push (ferro-labs/ai-gateway) · observed Aug 7, 2026
- License file (Apache-2.0) · observed Aug 9, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: distributed-llama 3.0k · ai-gateway 219 (synced Jul 25, 2026).
Common questions
- What is the difference between distributed-llama and ai-gateway?
- distributed-llama: Distributed LLM inference using home devices cluster. 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 distributed-llama over ai-gateway?
- Choose distributed-llama over ai-gateway when distributed-llama is primarily C++; ai-gateway is Go; License: distributed-llama is MIT, ai-gateway is Apache-2.0; Tags unique to distributed-llama: distributed-computing, llm-inference, neural-network; When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks.
- When should I choose ai-gateway over distributed-llama?
- Choose ai-gateway over distributed-llama when ai-gateway is primarily Go; distributed-llama is C++; License: ai-gateway is Apache-2.0, distributed-llama is MIT; Tags unique to ai-gateway: ai-gateway, litellm, llm-cost, llm-proxy; Also covers Model Training; When you need to integrate more than 30 different LLM services including OpenAI and Anthropic.
- When should I avoid distributed-llama?
- For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited. In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices.
- 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 distributed-llama or ai-gateway more popular on GitHub?
- distributed-llama has more GitHub stars (3,012 vs 219). Stars measure visibility, not whether either tool fits your constraints.
- Are distributed-llama and ai-gateway open source?
- Yes - both are open-source projects on GitHub (distributed-llama: MIT, ai-gateway: Apache-2.0).
- Where can I find alternatives to distributed-llama or ai-gateway?
- GraphCanon lists graph-backed alternatives at distributed-llama alternatives and ai-gateway alternatives (distributed-llama 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, distributed-llama or ai-gateway?
- distributed-llama: 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 distributed-llama and ai-gateway?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: distributed-llama trust report; ai-gateway trust report.