--- title: "JetStream vs xllm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ai-hypercomputer-jetstream-vs-xllm-ai-xllm" tools: ["ai-hypercomputer-jetstream", "xllm-ai-xllm"] --- # JetStream vs xllm *GraphCanon updated Aug 25, 2026* ## Verdict Pick JetStream if jetStream optimises throughput and memory for LLM inference on XLA devices like TPUs, with potential GPU support in future; pick xllm if a high-performance inference engine for LLM, VLM, DiT, and REC models by the OpenAtom Foundation. [JetStream](https://github.com/AI-Hypercomputer/JetStream) reports 455 GitHub stars, 67 forks, and 26 open issues, last pushed Jan 5, 2026. [xllm](https://xllm-ai.com/) has 1.5k stars, 282 forks, and 213 open issues, last pushed Aug 24, 2026. Figures are from public GitHub metadata via [JetStream's repository](https://github.com/AI-Hypercomputer/JetStream) and [xllm's repository](https://github.com/xLLM-AI/xllm). | | [JetStream](/tools/ai-hypercomputer-jetstream.md) | [xllm](/tools/xllm-ai-xllm.md) | | --- | --- | --- | | Tagline | Throughput and memory optimized engine for LLM inference on XLA devices | A high-performance inference engine for LLM, VLM, DiT and REC models | | Stars | 455 | 1,534 | | Forks | 67 | 282 | | Open issues | 26 | 213 | | Language | Python | C++ | | Adopt for | JetStream optimises throughput and memory for LLM inference on XLA devices like TPUs, with potential GPU support in future. | A high-performance inference engine for LLM, VLM, DiT, and REC models by the OpenAtom Foundation. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [JetStream](/tools/ai-hypercomputer-jetstream.md) | [xllm](/tools/xllm-ai-xllm.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 231d | 0d | | Open issues (now) | 26 | 213 | | Stars delta | +4 (30d) | +41 (30d) | | Open issues delta | +1 (30d) | +22 (30d) | | Full report | [trust report](/tools/ai-hypercomputer-jetstream/trust.md) | [trust report](/tools/xllm-ai-xllm/trust.md) | ## Decision facts: JetStream - **Adopt for:** JetStream optimises throughput and memory for LLM inference on XLA devices like TPUs, with potential GPU support in future. ## Decision facts: xllm - **Adopt for:** A high-performance inference engine for LLM, VLM, DiT, and REC models by the OpenAtom Foundation. ## Choose when ### Choose JetStream if… - JetStream is primarily Python; xllm is C++. - Tags unique to JetStream: gemma, gpt, gpu, inference. - * You are working with large language models (LLMs) that require efficient inference on hardware supported by XLA, particularly TPUs. ### Choose xllm if… - xllm is primarily C++; JetStream is Python. - Tags unique to xllm: deepseek, glm, llm-inference. - When developing applications that require optimized performance on various AI accelerators ## When NOT to use JetStream - * If your primary compute platform is not an XLA-compatible device such as TPU; JetStream's current focus is on systems that are supported by XLA. - * When you need immediate support for GPUs, since GPU functionality is marked as a future potential enhancement. ## When NOT to use xllm - If your project strictly requires Python-based inference engines for backend support - In cases preferring proprietary licenses over the Apache-2.0 open-source framework used here ## Common questions ### What is the difference between JetStream and xllm? JetStream: Throughput and memory optimized engine for LLM inference on XLA devices. xllm: A high-performance inference engine for LLM, VLM, DiT and REC models. See the comparison table for live GitHub stats and shared categories. ### When should I choose JetStream over xllm? Choose JetStream over xllm when JetStream is primarily Python; xllm is C++; Tags unique to JetStream: gemma, gpt, gpu, inference; * You are working with large language models (LLMs) that require efficient inference on hardware supported by XLA, particularly TPUs. ### When should I choose xllm over JetStream? Choose xllm over JetStream when xllm is primarily C++; JetStream is Python; Tags unique to xllm: deepseek, glm, llm-inference; When developing applications that require optimized performance on various AI accelerators. ### When should I avoid JetStream? * If your primary compute platform is not an XLA-compatible device such as TPU; JetStream's current focus is on systems that are supported by XLA. * When you need immediate support for GPUs, since GPU functionality is marked as a future potential enhancement. ### When should I avoid xllm? If your project strictly requires Python-based inference engines for backend support In cases preferring proprietary licenses over the Apache-2.0 open-source framework used here ### Is JetStream or xllm more popular on GitHub? xllm has more GitHub stars (1,534 vs 455). Stars measure visibility, not whether either tool fits your constraints. ### Are JetStream and xllm open source? Yes - both are open-source projects on GitHub (JetStream: Apache-2.0, xllm: Apache-2.0). ### Where can I find alternatives to JetStream or xllm? GraphCanon lists graph-backed alternatives at [JetStream alternatives](/tools/ai-hypercomputer-jetstream/alternatives) and [xllm alternatives](/tools/xllm-ai-xllm/alternatives) ([JetStream markdown twin](/tools/ai-hypercomputer-jetstream/alternatives.md), [xllm markdown twin](/tools/xllm-ai-xllm/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/ai-hypercomputer-jetstream-vs-xllm-ai-xllm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, JetStream or xllm? JetStream: Slowing. xllm: 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 JetStream and xllm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [JetStream trust report](/tools/ai-hypercomputer-jetstream/trust); [xllm trust report](/tools/xllm-ai-xllm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ai-hypercomputer-jetstream`](/api/graphcanon/graph?tool=ai-hypercomputer-jetstream) - 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/_