Comparison
OneCompression vs reasoning-from-scratch
Verdict
Pick OneCompression when oneCompression is primarily Python; reasoning-from-scratch is Jupyter Notebook; pick reasoning-from-scratch when reasoning-from-scratch is primarily Jupyter Notebook; OneCompression is Python.
Markdown twin · OneCompression alternatives · reasoning-from-scratch alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | OneCompression | reasoning-from-scratch |
|---|---|---|
| Maintenance | Very active (5d since push) As of today · github_public_v1 | Very active (4d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | 15 low (15 low) As of today · osv@v1 |
Tagline
- OneCompression
- Python package for LLM compression
- reasoning-from-scratch
- Implement a reasoning LLM in PyTorch from scratch, step by step
Stars
- OneCompression
- 396
- reasoning-from-scratch
- 4.7k
Forks
- OneCompression
- 18
- reasoning-from-scratch
- 707
Open issues
- OneCompression
- 6
- reasoning-from-scratch
- 2
Language
- OneCompression
- Python
- reasoning-from-scratch
- Jupyter Notebook
Adopt for
- OneCompression
- -
- reasoning-from-scratch
- Decision-critical facts for 'reasoning-from-scratch' are key to understanding its applicability and limitations.
Persona
- OneCompression
- -
- reasoning-from-scratch
- -
Runtime
- OneCompression
- -
- reasoning-from-scratch
- -
License
- OneCompression
- MIT
- reasoning-from-scratch
- Available under Apache-2.0 license, allowing for both free use and modification in academic and commercial projects.
Last pushed
- OneCompression
- Jul 6, 2026
- reasoning-from-scratch
- Jul 6, 2026
Categories
- OneCompression
- LLM Frameworks, Model Training, Inference & Serving
- reasoning-from-scratch
- LLM Frameworks, Model Training, Inference & Serving
Trust and health
Days since push
- OneCompression
- 5d
- reasoning-from-scratch
- 4d
Open issues (now)
- OneCompression
- 6
- reasoning-from-scratch
- 2
Owner type
- OneCompression
- Organization
- reasoning-from-scratch
- User
Security scan
- OneCompression
- No lockfile
- reasoning-from-scratch
- 15 low (15 low)
Full report
- OneCompression
- Trust report
- reasoning-from-scratch
- Trust report
Shared compatibility
- Python · OneCompression: Python runtime · reasoning-from-scratch: Python runtime
Choose OneCompression if…
- OneCompression is primarily Python; reasoning-from-scratch is Jupyter Notebook.
- License: OneCompression is MIT, reasoning-from-scratch is Apache-2.0.
- Tags unique to OneCompression: qep, llm, vllm, python.
When NOT to use OneCompression
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Choose reasoning-from-scratch if…
- reasoning-from-scratch is primarily Jupyter Notebook; OneCompression is Python.
- License: reasoning-from-scratch is Apache-2.0, OneCompression is MIT.
- Requirements: - The repository is designed to work on consumer-grade hardware and utilizes GPUs if available.; - Chapters 1 through 4 are optimized for CPUs as well as GPUs..
- Tags unique to reasoning-from-scratch: inference-time-scaling, deep-learning, chain-of-thought, ai.
- - You have a solid grasp of PyTorch and want to implement a reasoning-focused large language model from scratch.
When NOT to use reasoning-from-scratch
- - If you require immediate implementation without understanding the underlying principles, as this repository focuses on educational walkthroughs rather than providing ready-to-use models.
- - When your hardware capabilities are limited and you cannot manage even basic computation tasks as required by chapters 5 and 6, particularly without a GPU.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (FujitsuResearch/OneCompression) · observed Jul 11, 2026
- GitHub forks (FujitsuResearch/OneCompression) · observed Jul 11, 2026
- Last push (FujitsuResearch/OneCompression) · observed Jul 6, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (rasbt/reasoning-from-scratch) · observed Jul 11, 2026
- GitHub forks (rasbt/reasoning-from-scratch) · observed Jul 11, 2026
- Last push (rasbt/reasoning-from-scratch) · observed Jul 6, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 9, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: OneCompression 396 · reasoning-from-scratch 4.7k (synced Jul 11, 2026).
Common questions
- What is the difference between OneCompression and reasoning-from-scratch?
- OneCompression: Python package for LLM compression. reasoning-from-scratch: Implement a reasoning LLM in PyTorch from scratch, step by step. See the comparison table for live GitHub stats and shared categories.
- When should I choose OneCompression over reasoning-from-scratch?
- Choose OneCompression over reasoning-from-scratch when OneCompression is primarily Python; reasoning-from-scratch is Jupyter Notebook; License: OneCompression is MIT, reasoning-from-scratch is Apache-2.0; Tags unique to OneCompression: qep, llm, vllm, python.
- When should I choose reasoning-from-scratch over OneCompression?
- Choose reasoning-from-scratch over OneCompression when reasoning-from-scratch is primarily Jupyter Notebook; OneCompression is Python; License: reasoning-from-scratch is Apache-2.0, OneCompression is MIT; Requirements: - The repository is designed to work on consumer-grade hardware and utilizes GPUs if available.; - Chapters 1 through 4 are optimized for CPUs as well as GPUs.; Tags unique to reasoning-from-scratch: inference-time-scaling, deep-learning, chain-of-thought, ai; - You have a solid grasp of PyTorch and want to implement a reasoning-focused large language model from scratch.
- When should I avoid OneCompression?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- When should I avoid reasoning-from-scratch?
- - If you require immediate implementation without understanding the underlying principles, as this repository focuses on educational walkthroughs rather than providing ready-to-use models. - When your hardware capabilities are limited and you cannot manage even basic computation tasks as required by chapters 5 and 6, particularly without a GPU.
- Is OneCompression or reasoning-from-scratch more popular on GitHub?
- reasoning-from-scratch has more GitHub stars (4,717 vs 396). Stars measure visibility, not whether either tool fits your constraints.
- Are OneCompression and reasoning-from-scratch open source?
- Yes - both are open-source projects on GitHub (OneCompression: MIT, reasoning-from-scratch: Apache-2.0).
- Where can I find alternatives to OneCompression or reasoning-from-scratch?
- GraphCanon lists graph-backed alternatives at OneCompression alternatives and reasoning-from-scratch alternatives (OneCompression markdown twin, reasoning-from-scratch 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 reasoning-from-scratch?
- OneCompression: Very active. reasoning-from-scratch: 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 reasoning-from-scratch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: OneCompression trust report; reasoning-from-scratch trust report.