Comparison
flash-linear-attention vs accelerate
Verdict
Pick flash-linear-attention if flash-linear-attention accelerates linear attention mechanisms in large language models, using CUDA for optimal performance; pick accelerate if tool: accelerate.
Markdown twin · flash-linear-attention alternatives · accelerate alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | flash-linear-attention | accelerate |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3d · github_public_v1 | Very active (3d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3d · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) 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
- flash-linear-attention
- 🚀 Efficient implementations for emerging model architectures
- accelerate
- A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.
Stars
- flash-linear-attention
- 5.6k
- accelerate
- 9.8k
Forks
- flash-linear-attention
- 661
- accelerate
- 1.4k
Open issues
- flash-linear-attention
- 98
- accelerate
- 105
Language
- flash-linear-attention
- Python
- accelerate
- Python
Adopt for
- flash-linear-attention
- Flash-linear-attention accelerates linear attention mechanisms in large language models, using CUDA for optimal performance.
- accelerate
- Tool: accelerate
Persona
- flash-linear-attention
- -
- accelerate
- -
Runtime
- flash-linear-attention
- -
- accelerate
- -
License
- flash-linear-attention
- MIT
- accelerate
- Apache-2.0
Last pushed
- flash-linear-attention
- Aug 17, 2026
- accelerate
- Jul 30, 2026
Categories
- flash-linear-attention
- Model Training
- accelerate
- Inference & Serving, Model Training
Trust and health
Days since push
- flash-linear-attention
- 0d
- accelerate
- 3d
Open issues (now)
- flash-linear-attention
- 98
- accelerate
- 105
Stars delta
- flash-linear-attention
- +208 (30d)
- accelerate
- Unknown
Open issues delta
- flash-linear-attention
- +21 (30d)
- accelerate
- Unknown
Full report
- flash-linear-attention
- Trust report
- accelerate
- Trust report
Shared compatibility
- Python · flash-linear-attention: Python runtime · accelerate: Python runtime
Choose flash-linear-attention if…
- License: flash-linear-attention is MIT, accelerate is Apache-2.0.
- Tags unique to flash-linear-attention: large language models, machine-learning-systems, natural-language-processing, sequence-modeling.
- High-performance requirements with Nvidia GPUs where CUDA can offer significant speed-ups
When NOT to use flash-linear-attention
- Limited GPU hardware or no support for backend flavors like CUDA, ROCM, XPU, NPU, or CPU
- Do not require linear attention mechanism in modeling large language models or sequence data
Choose accelerate if…
- License: accelerate is Apache-2.0, flash-linear-attention is MIT.
- Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch.
- Also covers Inference & Serving.
- Easy mixed-precision support for PyTorch models
When NOT to use accelerate
- Non-PyTorch projects do not benefit from this tool
- Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow
- Limited to Python environments compatible with PyTorch 1.10.0+
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (fla-org/flash-linear-attention) · observed Aug 17, 2026
- GitHub forks (fla-org/flash-linear-attention) · observed Aug 17, 2026
- Last push (fla-org/flash-linear-attention) · observed Aug 17, 2026
- License file (MIT) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (huggingface/accelerate) · observed Aug 3, 2026
- GitHub forks (huggingface/accelerate) · observed Aug 3, 2026
- Last push (huggingface/accelerate) · observed Jul 30, 2026
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: flash-linear-attention 5.6k · accelerate 9.8k (synced Aug 17, 2026).
Common questions
- What is the difference between flash-linear-attention and accelerate?
- flash-linear-attention: 🚀 Efficient implementations for emerging model architectures. accelerate: A tool for launching, training, and using PyTorch models with ease on various devices, configurations, including mixed precision support.. See the comparison table for live GitHub stats and shared categories.
- When should I choose flash-linear-attention over accelerate?
- Choose flash-linear-attention over accelerate when License: flash-linear-attention is MIT, accelerate is Apache-2.0; Tags unique to flash-linear-attention: large language models, machine-learning-systems, natural-language-processing, sequence-modeling; High-performance requirements with Nvidia GPUs where CUDA can offer significant speed-ups.
- When should I choose accelerate over flash-linear-attention?
- Choose accelerate over flash-linear-attention when License: accelerate is Apache-2.0, flash-linear-attention is MIT; Tags unique to accelerate: deepspeed, fsdp, mixed precision, pytorch; Also covers Inference & Serving; Easy mixed-precision support for PyTorch models.
- When should I avoid flash-linear-attention?
- Limited GPU hardware or no support for backend flavors like CUDA, ROCM, XPU, NPU, or CPU Do not require linear attention mechanism in modeling large language models or sequence data
- When should I avoid accelerate?
- Non-PyTorch projects do not benefit from this tool Doesnt offer advanced auto-tuning features for other frameworks like TensorFlow Limited to Python environments compatible with PyTorch 1.10.0+
- Is flash-linear-attention or accelerate more popular on GitHub?
- accelerate has more GitHub stars (9,803 vs 5,568). Stars measure visibility, not whether either tool fits your constraints.
- Are flash-linear-attention and accelerate open source?
- Yes - both are open-source projects on GitHub (flash-linear-attention: MIT, accelerate: Apache-2.0).
- Where can I find alternatives to flash-linear-attention or accelerate?
- GraphCanon lists graph-backed alternatives at flash-linear-attention alternatives and accelerate alternatives (flash-linear-attention markdown twin, accelerate 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, flash-linear-attention or accelerate?
- flash-linear-attention: Very active. accelerate: 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 flash-linear-attention and accelerate?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: flash-linear-attention trust report; accelerate trust report.