xLLM — alternative #1 to LMCache
High-performance inference engine optimized for Chinese AI accelerators (Cambricon MLU, Hygon DCU, Huawei Ascend). Features service-engine d...
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Recorded alternatives
Every candidate below sits in AI. What ends up on this page is decided entirely by a recorded score — not by bidding, not by editor taste. Review both records, check current vendor terms, then decide.
High-performance inference engine optimized for Chinese AI accelerators (Cambricon MLU, Hygon DCU, Huawei Ascend). Features service-engine d...
Fast inference engine for Transformer models supporting OpenNMT and Hugging Face models. Optimized for CPU and GPU with batching, quantizati...
High-speed LLM inference for local deployment on consumer GPUs. Achieves up to 11x speedup over llama.cpp on RTX 4090 by exploiting power-la...
Toolkit for compressing, deploying, and serving LLMs from OpenMMLab. 4-bit inference with 2.4x higher performance than FP16, distributed mul...
Minimalist vLLM implementation in ~1,200 lines of Python. Educational yet performant with prefix caching, tensor parallelism, and CUDA graph...
Each candidate is a live catalogue record in the same primary category, picked by a deterministic score that Oryxen records in its catalogue: how many meaningful words the two listings share, whether their pricing classes oppose (a paid product against a free one), whether both are open source, and whether either record is featured. The same catalogue state always produces the same list — no randomness, no manual ranking.
No. Rows are ordered only by the recorded score, highest first, with alphabetical ties — payment never influences the order, nothing here is paid placement, and Oryxen charges no listing or placement fee.
Always verify current terms with LMCache directly — Oryxen records pricing classes, not live quotes.