TorchServe
model_serving
Overview
Developed byMeta (Facebook)
Maintained byPyTorch team
LicenseApache License 2.0
Open source✓ Open Source
Use casePyTorch model serving and inference
Technical
Protocols
Integrates with
Knowledge graph stats
Claims28
Avg confidence93%
Avg freshness99%
Last updatedUpdated 5 days ago
Trust distribution
100% unverified
Governance
Not assessed
TorchServe
product
PyTorch's flexible and easy-to-use tool for serving machine learning models in production environments.
Compare with...supports model
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| PyTorch models | ○Unverified | High | Fresh | 1 |
open source
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| true | ○Unverified | High | Fresh | 1 |
pricing model
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| free | ○Unverified | High | Fresh | 1 |
license type
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| Apache License 2.0 | ○Unverified | High | Fresh | 1 |
based on
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| PyTorch | ○Unverified | High | Fresh | 1 |
primary use case
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| PyTorch model serving and inference | ○Unverified | High | Fresh | 1 |
| PyTorch model serving and deployment | ○Unverified | High | Fresh | 1 |
| serving PyTorch models in production | ○Unverified | High | Fresh | 1 |
supports protocol
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| REST API | ○Unverified | High | Fresh | 1 |
| HTTP | ○Unverified | High | Fresh | 1 |
| HTTP REST API | ○Unverified | High | Fresh | 1 |
| gRPC | ○Unverified | High | Fresh | 1 |
developed by
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| Meta (Facebook) | ○Unverified | High | Fresh | 1 |
| Meta AI | ○Unverified | High | Fresh | 1 |
| Meta | ○Unverified | High | Fresh | 1 |
requires
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| Python | ○Unverified | High | Fresh | 1 |
| Java 11 | ○Unverified | High | Fresh | 1 |
| Java 11 or later | ○Unverified | Moderate | Fresh | 1 |
| Java 11+ | ○Unverified | Moderate | Fresh | 1 |
integrates with
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| Docker | ○Unverified | High | Fresh | 1 |
| Amazon SageMaker | ○Unverified | High | Fresh | 1 |
| Kubernetes | ○Unverified | High | Fresh | 1 |
maintained by
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| PyTorch team | ○Unverified | High | Fresh | 1 |
competes with
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| TensorFlow Serving | ○Unverified | Moderate | Fresh | 1 |
| MLflow Models | ○Unverified | Moderate | Fresh | 1 |
| MLflow | ○Unverified | Moderate | Fresh | 1 |
alternative to
| Value | Trust | Confidence | Freshness | Sources |
|---|---|---|---|---|
| TensorFlow Serving | ○Unverified | Moderate | Fresh | 1 |