Best vLLM Alternatives for LLM Serving in 2025
Best vLLM alternatives: TensorRT-LLM, TGI, Triton, SGLang, DeepSpeed-MII. Compare throughput, latency, and ease of use for LLM inference.
vLLM is the most popular open-source LLM serving framework, but it's not always the best choice. Depending on your needs — maximum throughput, lowest latency, enterprise features, or specific model support — there are better alternatives. Here are the top 6 vLLM alternatives for LLM serving in 2025.
TensorRT-LLM (NVIDIA)
Pros
- 3-5x faster than vLLM with FP8
- Best throughput on H100/H200
- NVIDIA optimization
- In-flight batching
Cons
- NVIDIA GPUs only
- Complex setup
- Requires model compilation
- Less flexible than vLLM
TGI (Text Generation Inference)
Pros
- HuggingFace ecosystem
- Easy model loading
- Quantization support
- Good documentation
Cons
- Slower than vLLM
- Less optimized for H100
- Higher memory usage
NVIDIA Triton Inference Server
Pros
- Production-grade
- Multi-model serving
- Kubernetes-native
- Enterprise support
- Model repository
Cons
- Steeper learning curve
- More configuration needed
- Not LLM-specific
SGLang
Pros
- Structured generation
- Latest research innovations
- Fast growing
- Good for complex prompts
Cons
- Newer (less mature)
- Smaller community
- Limited documentation
DeepSpeed-MII
Pros
- Microsoft DeepSpeed ecosystem
- Good for large models
- Optimized for cost
Cons
- Less active development
- Smaller community than vLLM
- Limited model support
vLLM (baseline)
Pros
- Most popular
- PagedAttention (2-4x throughput)
- Continuous batching
- OpenAI-compatible API
- Easy to use
- Active community
Cons
- Not as fast as TensorRT-LLM on H100
- No FP8 support yet
- Memory management can be improved
Verdict
vLLM remains the best default choice for most LLM serving use cases due to its ease of use, community support, and PagedAttention optimization. However, if you need maximum throughput on H100/H200 GPUs, TensorRT-LLM is 3-5x faster with FP8. For enterprise multi-model deployments, Triton is the production-grade choice. For HuggingFace ecosystem users, TGI offers the easiest path. Harch Corp provides pre-configured environments for all these frameworks on our GPU cloud.