Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • LM-Kit.NET Reviews & Ratings
    23 Ratings
    Company Website
  • RunPod Reviews & Ratings
    180 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    10 Ratings
    Company Website
  • Vertex AI Reviews & Ratings
    783 Ratings
    Company Website
  • Convesio Reviews & Ratings
    53 Ratings
    Company Website
  • KrakenD Reviews & Ratings
    71 Ratings
    Company Website
  • Gr4vy Reviews & Ratings
    5 Ratings
    Company Website
  • Paligo Reviews & Ratings
    99 Ratings
    Company Website
  • Zengo Wallet Reviews & Ratings
    414 Ratings
    Company Website
  • eMembership for Labor Unions Reviews & Ratings
    12 Ratings
    Company Website

What is Tensormesh?

Tensormesh is a groundbreaking caching solution tailored for inference processes with large language models, enabling businesses to leverage intermediate computations and significantly reduce GPU usage while improving time-to-first-token and overall responsiveness. By retaining and reusing vital key-value cache states that are often discarded after each inference, it effectively cuts down on redundant computations, achieving inference speeds that can be "up to 10x faster," while also alleviating the pressure on GPU resources. The platform is adaptable, supporting both public cloud and on-premises implementations, and includes features like extensive observability, enterprise-grade control, as well as SDKs/APIs and dashboards that facilitate smooth integration with existing inference systems, offering out-of-the-box compatibility with inference engines such as vLLM. Tensormesh places a strong emphasis on performance at scale, enabling repeated queries to be executed in sub-millisecond times and optimizing every element of the inference process, from caching strategies to computational efficiency, which empowers organizations to enhance the effectiveness and agility of their applications. In a rapidly evolving market, these improvements furnish companies with a vital advantage in their pursuit of effectively utilizing sophisticated language models, fostering innovation and operational excellence. Additionally, the ongoing development of Tensormesh promises to further refine its capabilities, ensuring that users remain at the forefront of technological advancements.

What is NVIDIA TensorRT?

NVIDIA TensorRT is a powerful collection of APIs focused on optimizing deep learning inference, providing a runtime for efficient model execution and offering tools that minimize latency while maximizing throughput in real-world applications. By harnessing the capabilities of the CUDA parallel programming model, TensorRT improves neural network architectures from major frameworks, optimizing them for lower precision without sacrificing accuracy, and enabling their use across diverse environments such as hyperscale data centers, workstations, laptops, and edge devices. It employs sophisticated methods like quantization, layer and tensor fusion, and meticulous kernel tuning, which are compatible with all NVIDIA GPU models, from compact edge devices to high-performance data centers. Furthermore, the TensorRT ecosystem includes TensorRT-LLM, an open-source initiative aimed at enhancing the inference performance of state-of-the-art large language models on the NVIDIA AI platform, which empowers developers to experiment and adapt new LLMs seamlessly through an intuitive Python API. This cutting-edge strategy not only boosts overall efficiency but also fosters rapid innovation and flexibility in the fast-changing field of AI technologies. Moreover, the integration of these tools into various workflows allows developers to streamline their processes, ultimately driving advancements in machine learning applications.

Media

Media

Integrations Supported

CUDA
Dataoorts GPU Cloud
Hugging Face
Kimi K2
LaunchX
MATLAB
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DeepStream SDK
NVIDIA Merlin
NVIDIA Morpheus
NVIDIA NIM
NVIDIA Riva Studio
NVIDIA virtual GPU
PyTorch
Python
RankGPT
RankLLM
TensorFlow
Ultralytics

Integrations Supported

CUDA
Dataoorts GPU Cloud
Hugging Face
Kimi K2
LaunchX
MATLAB
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DeepStream SDK
NVIDIA Merlin
NVIDIA Morpheus
NVIDIA NIM
NVIDIA Riva Studio
NVIDIA virtual GPU
PyTorch
Python
RankGPT
RankLLM
TensorFlow
Ultralytics

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Tensormesh

Date Founded

2025

Company Location

United States

Company Website

www.tensormesh.ai/

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/tensorrt

Categories and Features

Categories and Features

Popular Alternatives

Popular Alternatives

OpenVINO Reviews & Ratings

OpenVINO

Intel