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Comparison

OneCompression vs headroom

Verdict

Pick OneCompression if oneCompression is a Python package for compressing large language models using techniques such as quantization, with support for CUDA and MPS for different environments; pick headroom if headroom compresses data for LLMs, reducing token usage by 20% for coding agents and 60-95% for JSON, without altering answers. It offers a library, proxy, and MCP server.

Markdown twin · OneCompression alternatives · headroom alternatives

GraphCanon updated Sep 20, 2026

5views this month

OneCompression logo

OneCompression

FujitsuResearch/OneCompression

★ 426pushed Sep 14, 2026
vs
headroom logo

headroom

headroomlabs-ai/headroom

★ 73kpushed Sep 17, 2026

Trust & integrity

SignalOneCompressionheadroom
Maintenance
Very active (3d since push)
As of Sep 18, 2026 · github_public_v1
Very active (0d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Sep 18, 2026 · osv@v1
No lockfile (source not queried)
As of Sep 20, 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
OneCompression trust reportheadroom trust reportTrust methodology

Tagline

OneCompression
Python package for LLM compression
headroom
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM.

Stars

OneCompression
426
headroom
73k

Forks

OneCompression
20
headroom
5.6k

Open issues

OneCompression
8
headroom
671

Language

OneCompression
Python
headroom
Python

Adopt for

OneCompression
OneCompression is a Python package for compressing large language models using techniques such as quantization, with support for CUDA and MPS for different environments.
headroom
Headroom compresses data for LLMs, reducing token usage by 20% for coding agents and 60-95% for JSON, without altering answers. It offers a library, proxy, and MCP server.

Persona

OneCompression
-
headroom
-

Runtime

OneCompression
-
headroom
-

License

OneCompression
MIT
headroom
Apache-2.0

Last pushed

OneCompression
Sep 14, 2026
headroom
Sep 17, 2026

Categories

OneCompression
Inference & Serving, LLM Frameworks, Model Training
headroom
Developer Tools, Evaluation & Observability, Inference & Serving, Model Training

Trust and health

Days since push

OneCompression
3d
headroom
0d

Open issues (now)

OneCompression
8
headroom
671

Stars delta

OneCompression
+28 (30d)
headroom
+6.4k (30d)

Open issues delta

OneCompression
+1 (30d)
headroom
+183 (30d)

Full report

OneCompression
Trust report
headroom
Trust report

Shared compatibility

  • Python · OneCompression: Python runtime · headroom: Python runtime

Choose OneCompression if…

  • License: OneCompression is MIT, headroom is Apache-2.0.
  • Tags unique to OneCompression: cuda, llm, mps, pytorch.
  • Also covers LLM Frameworks.
  • Use OneCompression when you need to compress large language models and have access to a Linux system with an NVIDIA GPU, as it supports CUDA for quantization and vLLM serving.

When NOT to use OneCompression

  • Avoid OneCompression if you are working on a macOS system and require vLLM serving, as it is only supported on Linux with an NVIDIA GPU.
  • Do not use OneCompression if you are working with Python 3.13 and CUDA, as the first run with `--extra vllm` may take a long time due to the lack of pre-built `xformers` wheels for this combination.
  • Do not use OneCompression if you need to work with older CUDA versions like `cu118` or `cu121` and require vLLM, as `--extra vllm` is only compatible with `cu130`.
GitHubDetails

Choose headroom if…

  • License: headroom is Apache-2.0, OneCompression is MIT.
  • Requirements: Requires Docker; Requires Python 3.10+.; ONNX-backed features require AVX2 on x86/x86_64 hosts..
  • Tags unique to headroom: agent, ai, anthropic, claude-code.
  • Also covers Developer Tools, Evaluation & Observability.
  • headroom ships Docker support for self-hosted deployment.
  • When you need to reduce token usage for coding agents by 20% and for JSON by 60-95% without changing the answers.

When NOT to use headroom

  • If you are working with environments that do not support Python 3.10+.
  • When your project does not require token optimization or compression for JSON and coding agents.
  • If you are working on a platform that does not support the ONNX-backed features, such as some Docker/QEMU setups or older cloud VMs without AVX2.
GitHubDetails

Explore

OneCompression trust report →headroom trust report →Inference & Serving category →LLM Frameworks category →Model Training category →Developer Tools category →Evaluation & Observability 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: OneCompression 426 · headroom 73k (synced Sep 20, 2026).

Common questions

What is the difference between OneCompression and headroom?
OneCompression: Python package for LLM compression. headroom: Compress tool outputs, logs, files, and RAG chunks before they reach the LLM.. See the comparison table for live GitHub stats and shared categories.
When should I choose OneCompression over headroom?
Choose OneCompression over headroom when License: OneCompression is MIT, headroom is Apache-2.0; Tags unique to OneCompression: cuda, llm, mps, pytorch; Also covers LLM Frameworks; Use OneCompression when you need to compress large language models and have access to a Linux system with an NVIDIA GPU, as it supports CUDA for quantization and vLLM serving.
When should I choose headroom over OneCompression?
Choose headroom over OneCompression when License: headroom is Apache-2.0, OneCompression is MIT; Requirements: Requires Docker; Requires Python 3.10+.; ONNX-backed features require AVX2 on x86/x86_64 hosts.; Tags unique to headroom: agent, ai, anthropic, claude-code; Also covers Developer Tools, Evaluation & Observability; headroom ships Docker support for self-hosted deployment; When you need to reduce token usage for coding agents by 20% and for JSON by 60-95% without changing the answers.
When should I avoid OneCompression?
Avoid OneCompression if you are working on a macOS system and require vLLM serving, as it is only supported on Linux with an NVIDIA GPU. Do not use OneCompression if you are working with Python 3.13 and CUDA, as the first run with --extra vllm may take a long time due to the lack of pre-built xformers wheels for this combination. Do not use OneCompression if you need to work with older CUDA versions like cu118 or cu121 and require vLLM, as --extra vllm is only compatible with cu130.
When should I avoid headroom?
If you are working with environments that do not support Python 3.10+. When your project does not require token optimization or compression for JSON and coding agents. If you are working on a platform that does not support the ONNX-backed features, such as some Docker/QEMU setups or older cloud VMs without AVX2.
Is OneCompression or headroom more popular on GitHub?
headroom has more GitHub stars (72,850 vs 426). Stars measure visibility, not whether either tool fits your constraints.
Are OneCompression and headroom open source?
Yes - both are open-source projects on GitHub (OneCompression: MIT, headroom: Apache-2.0).
Where can I find alternatives to OneCompression or headroom?
GraphCanon lists graph-backed alternatives at OneCompression alternatives and headroom alternatives (OneCompression markdown twin, headroom 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, OneCompression or headroom?
OneCompression: Very active. headroom: 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 OneCompression and headroom?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: OneCompression trust report; headroom trust report.

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