Comparison
JetStream vs vllm
Verdict
Pick JetStream if jetStream optimises throughput and memory for LLM inference on XLA devices like TPUs, with potential GPU support in future; pick vllm if vLLM is a Python-based engine for efficient inference and serving of large language models, offering high throughput and memory efficiency.
Markdown twin · JetStream alternatives · vllm alternatives
GraphCanon updated Sep 20, 2026
14views this month
Trust & integrity
| Signal | JetStream | vllm |
|---|---|---|
| Maintenance | Slowing (257d since push) As of Sep 20, 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 20, 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 Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 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 |
Tagline
- JetStream
- Throughput and memory optimized engine for LLM inference on XLA devices
- vllm
- A high-throughput and memory-efficient inference and serving engine for LLMs
Stars
- JetStream
- 458
- vllm
- 92k
Forks
- JetStream
- 67
- vllm
- 22k
Open issues
- JetStream
- 26
- vllm
- 8.1k
Language
- JetStream
- Python
- vllm
- Python
Adopt for
- JetStream
- JetStream optimises throughput and memory for LLM inference on XLA devices like TPUs, with potential GPU support in future.
- vllm
- vLLM is a Python-based engine for efficient inference and serving of large language models, offering high throughput and memory efficiency.
Persona
- JetStream
- -
- vllm
- -
Runtime
- JetStream
- -
- vllm
- -
License
- JetStream
- Apache-2.0
- vllm
- vLLM is licensed under the Apache-2.0 license, allowing for broad use in both open-source and commercial projects.
Last pushed
- JetStream
- Jan 5, 2026
- vllm
- Sep 18, 2026
Categories
- JetStream
- Inference & Serving
- vllm
- Inference & Serving
Trust and health
Maintenance
- JetStream
- Slowing (36%)
- vllm
- Very active (96%)
Days since push
- JetStream
- 257d
- vllm
- 0d
Open issues (now)
- JetStream
- 26
- vllm
- 8.1k
Stars delta
- JetStream
- +7 (30d)
- vllm
- +4.2k (30d)
Open issues delta
- JetStream
- +1 (30d)
- vllm
- +1872 (30d)
Full report
- JetStream
- Trust report
- vllm
- Trust report
Shared compatibility
- Python · JetStream: Python runtime · vllm: Python runtime
Choose JetStream if…
- Tags unique to JetStream: gemma, gpu, jax, large-language-models.
- * You are working with large language models (LLMs) that require efficient inference on hardware supported by XLA, particularly TPUs.
- Leaner open-issue backlog (26).
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.
Choose vllm if…
- Requirements: Min 8 GB RAM; Installation can be done via `uv pip install vllm` or building from source for development purposes..
- Tags unique to vllm: amd, blackwell, cuda, deepseek.
- When you need a high-throughput and memory-efficient inference engine for large language models, especially if you are working with a variety of hardware configurations including AMD, CUDA, and TPU.
When NOT to use vllm
- If your project strictly requires a specific competitor's ecosystem or features that are not covered by vLLM, such as specialized model serving capabilities not supported by vLLM.
- When the project's hardware setup is incompatible with the supported hardware configurations of vLLM, such as certain non-supported GPU models or configurations.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (AI-Hypercomputer/JetStream) · observed Sep 20, 2026
- GitHub forks (AI-Hypercomputer/JetStream) · observed Sep 20, 2026
- Last push (AI-Hypercomputer/JetStream) · observed Jan 5, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (vllm-project/vllm) · observed Sep 20, 2026
- GitHub forks (vllm-project/vllm) · observed Sep 20, 2026
- Last push (vllm-project/vllm) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: JetStream 458 · vllm 92k (synced Sep 20, 2026).
Common questions
- What is the difference between JetStream and vllm?
- JetStream: Throughput and memory optimized engine for LLM inference on XLA devices. vllm: A high-throughput and memory-efficient inference and serving engine for LLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose JetStream over vllm?
- Choose JetStream over vllm when Tags unique to JetStream: gemma, gpu, jax, large-language-models; * You are working with large language models (LLMs) that require efficient inference on hardware supported by XLA, particularly TPUs; Leaner open-issue backlog (26).
- When should I choose vllm over JetStream?
- Choose vllm over JetStream when Requirements: Min 8 GB RAM; Installation can be done via
uv pip install vllmor building from source for development purposes.; Tags unique to vllm: amd, blackwell, cuda, deepseek; When you need a high-throughput and memory-efficient inference engine for large language models, especially if you are working with a variety of hardware configurations including AMD, CUDA, and TPU. - 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 vllm?
- If your project strictly requires a specific competitor's ecosystem or features that are not covered by vLLM, such as specialized model serving capabilities not supported by vLLM. When the project's hardware setup is incompatible with the supported hardware configurations of vLLM, such as certain non-supported GPU models or configurations.
- Is JetStream or vllm more popular on GitHub?
- vllm has more GitHub stars (92,075 vs 458). Stars measure visibility, not whether either tool fits your constraints.
- Are JetStream and vllm open source?
- Yes - both are open-source projects on GitHub (JetStream: Apache-2.0, vllm: Apache-2.0).
- Where can I find alternatives to JetStream or vllm?
- GraphCanon lists graph-backed alternatives at JetStream alternatives and vllm alternatives (JetStream markdown twin, vllm 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, JetStream or vllm?
- JetStream: Slowing. vllm: 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 vllm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: JetStream trust report; vllm trust report.