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[BEST_IN_NICHE // INFERENCE & SERVING]

Best Inference & Serving in May 2026

If you need a Inference & Serving tool right now, our pick to watch is vllm-project/vllm-ascend (velocity score 5.1/10). Score 5.1/10 — established but flat. Worth watching for the next inflection. Consider alternatives below if velocity matters. Other tools worth a look: sgl-project/sglang, ray-project/ray, gitleaks/gitleaks. Rankings update daily — see the full top 10 below.

Top 3 picks
[RANK · #01]
vllm-project/vllm
acceleratingscore 3.8/10+507 stars/7d
[RANK · #02]
sgl-project/sglang
acceleratingscore 3.4/10+237 stars/7d
[RANK · #03]
ray-project/ray
acceleratingscore 2.1/10+57 stars/7d
Top 10 ranked
Tool
Velocity
Trend 30d
Δ 7d
Stars
Class
  • vllm-project/vllmA high-throughput and memory-efficient inference and serving engine for LLMs
    3.79↑ +50780kAccel
  • sgl-project/sglangSGLang is a high-performance serving framework for large language models and multimodal models.
    3.38↑ +23728kAccel
  • ray-project/rayRay is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
    2.09↑ +5743kAccel
  • gitleaks/gitleaksFind secrets with Gitleaks 🔑
    1.07↑ +17727kAccel
  • GeeeekExplorer/nano-vllmNano vLLM
    1.02↑ +9213kAccel
  • OpenRLHF/OpenRLHFAn Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & VLM & TIS & vLLM & Ray & Async RL)
    0.99↑ +359.5kStable
  • jd-opensource/xllmA high-performance inference engine for LLM, VLM, DiT and REC models, optimized for diverse AI accelerators.
    0.93↑ +71.3kStable
  • NVIDIA/kvpressLLM KV cache compression made easy
    0.78↑ +141.1kStable
  • bentoml/BentoMLThe easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
    0.57↑ +78.6kStable
  • Lightning-AI/litgpt20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
    0.52↑ +1613kStable
Frequently asked

What's the best Inference & Serving right now?

vllm-project/vllm-ascend. Beam ranks Inference & Serving tools at 5.1/10 velocity. Score 5.1/10 — established but flat. Worth watching for the next inflection. Consider alternatives below if velocity matters.

What other Inference & Serving tools should I consider?

Beyond vllm-project/vllm, the next four highest-velocity Inference & Serving tools beam tracks are sgl-project/sglang, ray-project/ray, gitleaks/gitleaks, GeeeekExplorer/nano-vllm. Open any tool's profile for the full signal breakdown.

How does beam rank Inference & Serving tools?

Beam fuses five orthogonal signals into a single velocity score: code activity, package adoption, research citation, sentiment, and production signals. The score multiplies across signals, so any one signal collapsing pulls the whole score down — that's how beam catches stars-up-commits-down decay. Full methodology at /about/methodology.

Is vllm-project/vllm-ascend actively maintained?

See the live status check at /tools/2952/status for the direct-answer verdict, last-commit timestamp, and 90-day velocity chart. Beam refreshes daily.

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