Evaluation & Testing

go-ml-benchmarks

Benchmarks for machine learning inference in Go.

Status
UnmaintainedGitHub repository has been archived.
Last checked
Checked · Oct 10, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

Provides benchmarks to measure the performance of machine learning models during inference in Go, helping developers optimize their applications and understand model behavior under different conditions.

go-ml-benchmarks stands out by offering precise performance benchmarks specifically tailored for Go developers working with machine learning models, allowing them to optimize and understand model behavior effectively.

When it fits — and when it doesn’t

A good fit for

  • Go developers who need to measure and optimize the performance of their machine learning models during inference.

  • Data scientists working with Go who want to understand model behavior under different conditions.

Look elsewhere if

  • Developers looking for a full-featured machine learning framework, as go-ml-benchmarks is focused on benchmarking rather than providing comprehensive ML functionality.

  • Teams requiring cloud-based solutions or managed services for their machine learning needs.

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited support for diverse machine learning frameworks

    go-ml-benchmarks primarily supports TensorFlow and PyTorch, limiting its utility for users of other ML libraries.

  2. 02

    Complex setup process

    The tool requires specific Go dependencies and configurations that can be difficult to set up correctly in different environments.

  3. 03

    Performance overhead due to language limitations

    Go's garbage collection and lack of native support for certain low-level optimizations may introduce performance overhead compared to specialized ML languages like Python with optimized libraries.

  4. 04

    Small community and limited documentation

    The open-source project has a small contributor base, leading to less frequent updates and sparse documentation which can hinder user adoption and troubleshooting.

What it does well

  • Performance benchmarks for machine learning inference in Go.

  • Helps developers optimize their applications and understand model behavior under different conditions.

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up go-ml-benchmarks

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →