Home/Compare/aqueduct vs xllm

Comparison

aqueduct vs xllm

Verdict

Pick aqueduct if aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support; pick xllm if a high-performance inference engine for LLM, VLM, DiT, and REC models by the OpenAtom Foundation.

Markdown twin · aqueduct alternatives · xllm alternatives

GraphCanon updated Sep 29, 2026

7views this month

aqueduct logo

aqueduct

RunLLM/aqueduct

★ 518pushed Jun 7, 2023
vs
xllm logo

xllm

xLLM-AI/xllm

★ 1.6kpushed Sep 19, 2026

Trust & integrity

Signalaqueductxllm
Maintenance
Dormant (1209d since push)
As of Sep 29, 2026 · github_public_v1
Very active (0d since push)
As of Sep 19, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 29, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 19, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 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

aqueduct
Orchestrate LLM and ML workloads on any cloud infrastructure using Go.
xllm
A high-performance inference engine for LLM, VLM, DiT and REC models

Stars

aqueduct
518
xllm
1.6k

Forks

aqueduct
20
xllm
300

Open issues

aqueduct
11
xllm
211

Language

aqueduct
Go
xllm
C++

Adopt for

aqueduct
Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support.
xllm
A high-performance inference engine for LLM, VLM, DiT, and REC models by the OpenAtom Foundation.

Persona

aqueduct
-
xllm
-

Runtime

aqueduct
-
xllm
-

License

aqueduct
Apache-2.0
xllm
Apache-2.0

Last pushed

aqueduct
Jun 7, 2023
xllm
Sep 19, 2026

Categories

aqueduct
Inference & Serving, LLM Frameworks, Model Training
xllm
Inference & Serving

Trust and health

Maintenance

aqueduct
Dormant (18%)
xllm
Very active (96%)

Days since push

aqueduct
1209d
xllm
0d

Open issues (now)

aqueduct
11
xllm
211

Stars delta

aqueduct
+1 (30d)
xllm
+84 (30d)

Open issues delta

aqueduct
0 (30d)
xllm
+20 (30d)

Full report

aqueduct
Trust report

Choose aqueduct if…

  • aqueduct is primarily Go; xllm is C++.
  • Tags unique to aqueduct: ai, data, data-science, kubernetes.
  • Also covers LLM Frameworks, Model Training.
  • When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training.

When NOT to use aqueduct

  • Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained.
  • Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives.

Choose xllm if…

  • xllm is primarily C++; aqueduct is Go.
  • Tags unique to xllm: deepseek, glm, llm-inference.
  • When developing applications that require optimized performance on various AI accelerators

When NOT to use xllm

  • If your project strictly requires Python-based inference engines for backend support
  • In cases preferring proprietary licenses over the Apache-2.0 open-source framework used here

Explore

Sources

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

GitHub stars on cards: aqueduct 518 · xllm 1.6k (synced Sep 29, 2026).

Common questions

What is the difference between aqueduct and xllm?
aqueduct: Orchestrate LLM and ML workloads on any cloud infrastructure using Go.. xllm: A high-performance inference engine for LLM, VLM, DiT and REC models. See the comparison table for live GitHub stats and shared categories.
When should I choose aqueduct over xllm?
Choose aqueduct over xllm when aqueduct is primarily Go; xllm is C++; Tags unique to aqueduct: ai, data, data-science, kubernetes; Also covers LLM Frameworks, Model Training; When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training.
When should I choose xllm over aqueduct?
Choose xllm over aqueduct when xllm is primarily C++; aqueduct is Go; Tags unique to xllm: deepseek, glm, llm-inference; When developing applications that require optimized performance on various AI accelerators.
When should I avoid aqueduct?
Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives.
When should I avoid xllm?
If your project strictly requires Python-based inference engines for backend support In cases preferring proprietary licenses over the Apache-2.0 open-source framework used here
Is aqueduct or xllm more popular on GitHub?
xllm has more GitHub stars (1,577 vs 518). Stars measure visibility, not whether either tool fits your constraints.
Are aqueduct and xllm open source?
Yes - both are open-source projects on GitHub (aqueduct: Apache-2.0, xllm: Apache-2.0).
Where can I find alternatives to aqueduct or xllm?
GraphCanon lists graph-backed alternatives at aqueduct alternatives and xllm alternatives (aqueduct markdown twin, xllm 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, aqueduct or xllm?
aqueduct: Dormant. xllm: 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 aqueduct and xllm?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: aqueduct trust report; xllm trust report.

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