DeepInfer

DeepInfer

DeepSeek
+
+

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About

DeepInfer is an open-source inference framework for running DeepSeek language models on Linux systems with supported NVIDIA or Huawei Ascend accelerators. It provides offline inference and runtime components for model execution, optimized kernels, distributed parallelism, asynchronous batch scheduling, speculative decoding, deterministic generation, and structured outputs such as JSON Schema, regular expressions, and EBNF formats. The project documents DeepSeek-V4.1-Flash support and includes build instructions, configuration guidance, examples, and evaluation tools. It is intended for developers and infrastructure teams building or evaluating self-managed inference deployments. Its repository notes that production services may require additional KV-cache, prefill/decode disaggregation, and load-balancing components not included in this release.

About

Tensormesh is a caching layer built specifically for large-language-model inference workloads that enables organizations to reuse intermediate computations, drastically reduce GPU usage, and accelerate time-to-first-token and latency. It works by capturing and reusing key-value cache states that are normally thrown away after each inference, thereby cutting redundant compute and delivering “up to 10x faster inference” while substantially lowering GPU load. It supports deployments in public cloud or on-premises, with full observability and enterprise-grade control, SDKs/APIs, and dashboards for integration into existing inference pipelines, and compatibility with inference engines such as vLLM out of the box. Tensormesh emphasizes performance at scale, including sub-millisecond repeated queries, while optimizing every layer of inference from caching through computation.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Supported
Cloud Not Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers and infrastructure teams deploying or evaluating DeepSeek model inference on supported accelerator hardware.

Audience

Enterprises and AI infrastructure teams wanting a tool to reduce latency and cost while maintaining full control over deployment and data

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Company Information

DeepSeek
Founded: 2023
China
github.com/deepseek-ai/DeepInfer

Company Information

Tensormesh
Founded: 2025
United States
www.tensormesh.ai/

Alternatives

Alternatives

DeepSeek-V2

DeepSeek-V2

DeepSeek
DeepInfer

DeepInfer

DeepSeek
ModelArk

ModelArk

ByteDance
Photon

Photon

Moondream

Categories

AI Inference Supported

Categories

AI Inference Supported

Integrations

No info available.

Integrations

No info available.
Claim DeepInfer and update features and information
Claim DeepInfer and update features and information
Claim Tensormesh and update features and information
Claim Tensormesh and update features and information