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Comparison

KVarN vs exllama

Verdict

Pick KVarN when license: KVarN is Apache-2.0, exllama is MIT; pick exllama when license: exllama is MIT, KVarN is Apache-2.0.

Markdown twin · KVarN alternatives · exllama alternatives

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KVarN logo

KVarN

huawei-csl/KVarN

★ 435pushed Jun 22, 2026
vs
exllama logo

exllama

turboderp/exllama

★ 2.9kpushed Sep 30, 2023

Trust & integrity

SignalKVarNexllama
Maintenance
Active (19d since push)
As of 1d · github_public_v1
Dormant (1014d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of 1d · github_public_v1
Not a fork · Personal account
As of 1d · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
29 low (29 low)
As of 1d · osv@v1
KVarN trust reportexllama trust reportTrust methodology

Tagline

KVarN
KVarN is a native vLLM KV-cache quantization backend for your agents: 3-5x more context, throughput above FP16, and FP16-level accuracy. Calibration-free, one flag.
exllama
More memory-efficient rewrite of HF transformers for Llama with quantized weights

Stars

KVarN
435
exllama
2.9k

Forks

KVarN
28
exllama
223

Open issues

KVarN
7
exllama
65

Language

KVarN
Python
exllama
Python

Adopt for

KVarN
-
exllama
-

Persona

KVarN
-
exllama
-

Runtime

KVarN
-
exllama
-

License

KVarN
Apache-2.0
exllama
MIT

Last pushed

KVarN
Jun 22, 2026
exllama
Sep 30, 2023

Categories

KVarN
AI Agents, Inference & Serving, LLM Frameworks
exllama
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

KVarN
Active (82%)
exllama
Dormant (18%)

Days since push

KVarN
19d
exllama
1014d

Open issues (now)

KVarN
7
exllama
65

Owner type

KVarN
Organization
exllama
User

Security scan

KVarN
No lockfile
exllama
29 low (29 low)

Full report

KVarN
Trust report
exllama
Trust report

Choose KVarN if…

  • License: KVarN is Apache-2.0, exllama is MIT.
  • Tags unique to KVarN: agentic-ai, kv-cache, llm, llm-inference.
  • Also covers AI Agents.

When NOT to use KVarN

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Choose exllama if…

  • License: exllama is MIT, KVarN is Apache-2.0.
  • Tags unique to exllama: docker container support, gpu optimization, memory efficiency, nvidia support.
  • exllama ships Docker support for self-hosted deployment.

When NOT to use exllama

  • Last GitHub push was 1015 days ago (dormant maintenance, Sep 30, 2023). Validate activity before betting a new project on exllama.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Explore

KVarN trust report →exllama trust report →AI Agents category →Inference & Serving category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: KVarN 435 · exllama 2.9k (synced Jul 11, 2026).

Common questions

What is the difference between KVarN and exllama?
KVarN: KVarN is a native vLLM KV-cache quantization backend for your agents: 3-5x more context, throughput above FP16, and FP16-level accuracy. Calibration-free, one flag.. exllama: More memory-efficient rewrite of HF transformers for Llama with quantized weights. See the comparison table for live GitHub stats and shared categories.
When should I choose KVarN over exllama?
Choose KVarN over exllama when License: KVarN is Apache-2.0, exllama is MIT; Tags unique to KVarN: agentic-ai, kv-cache, llm, llm-inference; Also covers AI Agents.
When should I choose exllama over KVarN?
Choose exllama over KVarN when License: exllama is MIT, KVarN is Apache-2.0; Tags unique to exllama: docker container support, gpu optimization, memory efficiency, nvidia support; exllama ships Docker support for self-hosted deployment.
When should I avoid KVarN?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
When should I avoid exllama?
Last GitHub push was 1015 days ago (dormant maintenance, Sep 30, 2023). Validate activity before betting a new project on exllama. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is KVarN or exllama more popular on GitHub?
exllama has more GitHub stars (2,930 vs 435). Stars measure visibility, not whether either tool fits your constraints.
Are KVarN and exllama open source?
Yes - both are open-source projects on GitHub (KVarN: Apache-2.0, exllama: MIT).
Where can I find alternatives to KVarN or exllama?
GraphCanon lists graph-backed alternatives at KVarN alternatives and exllama alternatives (KVarN markdown twin, exllama 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, KVarN or exllama?
KVarN: Active. exllama: Dormant. 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 KVarN and exllama?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: KVarN trust report; exllama trust report.