--- title: "flash-linear-attention vs Liger-Kernel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/fla-org-flash-linear-attention-vs-linkedin-liger-kernel" tools: ["fla-org-flash-linear-attention", "linkedin-liger-kernel"] --- # flash-linear-attention vs Liger-Kernel *GraphCanon updated Aug 17, 2026* ## Verdict Pick flash-linear-attention if flash-linear-attention accelerates linear attention mechanisms in large language models, using CUDA for optimal performance; pick Liger-Kernel if optimized Triton kernels for accelerating LLM training, especially on ROCm PyTorch installations. [flash-linear-attention](https://github.com/fla-org/flash-linear-attention) reports 5.6k GitHub stars, 661 forks, and 98 open issues, last pushed Aug 17, 2026. [Liger-Kernel](https://linkedin.github.io/Liger-Kernel/) has 6.6k stars, 573 forks, and 190 open issues, last pushed Aug 7, 2026. Figures are from public GitHub metadata via [flash-linear-attention's repository](https://github.com/fla-org/flash-linear-attention) and [Liger-Kernel's repository](https://github.com/linkedin/Liger-Kernel). | | [flash-linear-attention](/tools/fla-org-flash-linear-attention.md) | [Liger-Kernel](/tools/linkedin-liger-kernel.md) | | --- | --- | --- | | Tagline | 🚀 Efficient implementations for emerging model architectures | Efficient Triton Kernels for LLM Training | | Stars | 5,568 | 6,555 | | Forks | 661 | 573 | | Open issues | 98 | 190 | | Language | Python | Python | | Adopt for | Flash-linear-attention accelerates linear attention mechanisms in large language models, using CUDA for optimal performance. | Optimized Triton kernels for accelerating LLM training, especially on ROCm PyTorch installations. | | Persona | - | - | | Runtime | - | - | | License | MIT | BSD-2-Clause | | Categories | Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [flash-linear-attention](/tools/fla-org-flash-linear-attention.md) | [Liger-Kernel](/tools/linkedin-liger-kernel.md) | | --- | --- | --- | | Open issues (now) | 98 | 190 | | Stars delta | +208 (30d) | Unknown | | Open issues delta | +21 (30d) | Unknown | | Full report | [trust report](/tools/fla-org-flash-linear-attention/trust.md) | [trust report](/tools/linkedin-liger-kernel/trust.md) | ## Shared compatibility - **Python**: [flash-linear-attention](/tools/fla-org-flash-linear-attention.md) - Python runtime; [Liger-Kernel](/tools/linkedin-liger-kernel.md) - Python runtime ## Decision facts: flash-linear-attention - **Adopt for:** Flash-linear-attention accelerates linear attention mechanisms in large language models, using CUDA for optimal performance. ## Decision facts: Liger-Kernel - **Adopt for:** Optimized Triton kernels for accelerating LLM training, especially on ROCm PyTorch installations. ## Choose when ### Choose flash-linear-attention if… - License: flash-linear-attention is MIT, Liger-Kernel is BSD-2-Clause. - 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 ### Choose Liger-Kernel if… - License: Liger-Kernel is BSD-2-Clause, flash-linear-attention is MIT. - Tags unique to Liger-Kernel: finetuning, gemma2, llama, mistral. - When enhancing training speed of large language models with ROCm-compatible hardware. ## 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 ## When NOT to use Liger-Kernel - Avoid if only CUDA environments are supported, as Liger-Kernel emphasizes ROCm compatibility. - Skip for simple setup requirements; prefer more streamlined tools without extensive customization options. ## Common questions ### What is the difference between flash-linear-attention and Liger-Kernel? flash-linear-attention: 🚀 Efficient implementations for emerging model architectures. Liger-Kernel: Efficient Triton Kernels for LLM Training. See the comparison table for live GitHub stats and shared categories. ### When should I choose flash-linear-attention over Liger-Kernel? Choose flash-linear-attention over Liger-Kernel when License: flash-linear-attention is MIT, Liger-Kernel is BSD-2-Clause; 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 Liger-Kernel over flash-linear-attention? Choose Liger-Kernel over flash-linear-attention when License: Liger-Kernel is BSD-2-Clause, flash-linear-attention is MIT; Tags unique to Liger-Kernel: finetuning, gemma2, llama, mistral; When enhancing training speed of large language models with ROCm-compatible hardware. ### 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 Liger-Kernel? Avoid if only CUDA environments are supported, as Liger-Kernel emphasizes ROCm compatibility. Skip for simple setup requirements; prefer more streamlined tools without extensive customization options. ### Is flash-linear-attention or Liger-Kernel more popular on GitHub? Liger-Kernel has more GitHub stars (6,555 vs 5,568). Stars measure visibility, not whether either tool fits your constraints. ### Are flash-linear-attention and Liger-Kernel open source? Yes - both are open-source projects on GitHub (flash-linear-attention: MIT, Liger-Kernel: BSD-2-Clause). ### Where can I find alternatives to flash-linear-attention or Liger-Kernel? GraphCanon lists graph-backed alternatives at [flash-linear-attention alternatives](/tools/fla-org-flash-linear-attention/alternatives) and [Liger-Kernel alternatives](/tools/linkedin-liger-kernel/alternatives) ([flash-linear-attention markdown twin](/tools/fla-org-flash-linear-attention/alternatives.md), [Liger-Kernel markdown twin](/tools/linkedin-liger-kernel/alternatives.md)), 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](/compare/fla-org-flash-linear-attention-vs-linkedin-liger-kernel.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, flash-linear-attention or Liger-Kernel? flash-linear-attention: Very active. Liger-Kernel: 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 Liger-Kernel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [flash-linear-attention trust report](/tools/fla-org-flash-linear-attention/trust); [Liger-Kernel trust report](/tools/linkedin-liger-kernel/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=fla-org-flash-linear-attention`](/api/graphcanon/graph?tool=fla-org-flash-linear-attention) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_