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Project comparison
Mindpipe vs vLLM
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Mindpipe
A powerful model compression framework for LLMs and LVLMs, adapted for NVIDIA GPUs and Huawei Ascend NPUs.
1.0K
Stars
0
Weekly
43/100
Health
vLLM
A high-throughput and memory-efficient inference and serving engine for LLMs
79.7K
Stars
+606
Weekly
93/100
Health
Quick Take
Adoption
vLLM has the larger GitHub footprint with 79.7K stars.
Momentum
vLLM is currently growing faster at +606 stars this week.
Maintenance
vLLM has the stronger health score at 93/100.
Side-by-side Metrics
| Signal | Mindpipe | vLLM |
|---|---|---|
| GitHub stars | 1.0K | 79.7K |
| Weekly growth | 0 | +606 |
| Health score | 43 | 93 |
| Contributors | 8 | 2.6K |
| Commits per week | 16.0 | 208.8 |
| Open issues | 0 | 4.9K |
| Language | Python | Python |
| License | N/A | Apache-2.0 |
| Last commit | 1d ago | 14h ago |
| Last release | N/A | v0.20.2 |
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