Home/Compare/JetStream vs DeepSeek-R1

Comparison

JetStream vs DeepSeek-R1

Verdict

Pick JetStream when license: JetStream is Apache-2.0, DeepSeek-R1 is MIT; pick DeepSeek-R1 when license: DeepSeek-R1 is MIT, JetStream is Apache-2.0.

Markdown twin · JetStream alternatives · DeepSeek-R1 alternatives

GraphCanon updated today

JetStream logo

JetStream

AI-Hypercomputer/JetStream

451pushed Jan 5, 2026
vs
DeepSeek-R1 logo

DeepSeek-R1

deepseek-ai/DeepSeek-R1

92kpushed Jun 27, 2025

Trust & integrity

SignalJetStreamDeepSeek-R1
Maintenance
Slowing (186d since push)
As of today · github_public_v1
Dormant (379d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of 1d · none

Tagline

JetStream
JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome).
DeepSeek-R1
Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.

Stars

JetStream
451
DeepSeek-R1
92k

Forks

JetStream
66
DeepSeek-R1
12k

Open issues

JetStream
25
DeepSeek-R1
45

Language

JetStream
Python
DeepSeek-R1
-

Adopt for

JetStream
-
DeepSeek-R1
DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.

Persona

JetStream
-
DeepSeek-R1
-

Runtime

JetStream
-
DeepSeek-R1
-

License

JetStream
Apache-2.0
DeepSeek-R1
MIT

Last pushed

JetStream
Jan 5, 2026
DeepSeek-R1
Jun 27, 2025

Categories

JetStream
Inference & Serving, LLM Frameworks, Model Training
DeepSeek-R1
LLM Frameworks, Model Training

Trust and health

Maintenance

JetStream
Slowing (36%)
DeepSeek-R1
Dormant (18%)

Days since push

JetStream
186d
DeepSeek-R1
379d

Open issues (now)

JetStream
25
DeepSeek-R1
45

Full report

JetStream
Trust report
DeepSeek-R1
Trust report

Choose JetStream if…

  • License: JetStream is Apache-2.0, DeepSeek-R1 is MIT.
  • Tags unique to JetStream: gemma, gpt, gpu, inference.
  • Also covers Inference & Serving.

When NOT to use JetStream

  • Last GitHub push was 187 days ago (slowing maintenance, Jan 5, 2026). Validate activity before betting a new project on JetStream.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • 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.

Choose DeepSeek-R1 if…

  • License: DeepSeek-R1 is MIT, JetStream is Apache-2.0.
  • Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository..
  • Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs..
  • Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license.
  • When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.

When NOT to use DeepSeek-R1

  • Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments.
  • If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: JetStream 451 · DeepSeek-R1 92k (synced Jul 11, 2026).

Common questions

What is the difference between JetStream and DeepSeek-R1?
JetStream: JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome).. DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. See the comparison table for live GitHub stats and shared categories.
When should I choose JetStream over DeepSeek-R1?
Choose JetStream over DeepSeek-R1 when License: JetStream is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to JetStream: gemma, gpt, gpu, inference; Also covers Inference & Serving.
When should I choose DeepSeek-R1 over JetStream?
Choose DeepSeek-R1 over JetStream when License: DeepSeek-R1 is MIT, JetStream is Apache-2.0; Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.; Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.; Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license; When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.
When should I avoid JetStream?
Last GitHub push was 187 days ago (slowing maintenance, Jan 5, 2026). Validate activity before betting a new project on JetStream. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. 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.
When should I avoid DeepSeek-R1?
Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.
Is JetStream or DeepSeek-R1 more popular on GitHub?
DeepSeek-R1 has more GitHub stars (91,991 vs 451). Stars measure visibility, not whether either tool fits your constraints.
Are JetStream and DeepSeek-R1 open source?
Yes - both are open-source projects on GitHub (JetStream: Apache-2.0, DeepSeek-R1: MIT).
Where can I find alternatives to JetStream or DeepSeek-R1?
GraphCanon lists graph-backed alternatives at JetStream alternatives and DeepSeek-R1 alternatives (JetStream markdown twin, DeepSeek-R1 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 DeepSeek-R1?
JetStream: Slowing. DeepSeek-R1: Dormant. 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 DeepSeek-R1?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: JetStream trust report; DeepSeek-R1 trust report.