Choosing an open-weight model: DeepSeek, Qwen, Mistral and GLM compared
Open-weight models let you host your own AI. Choosing between them is about licence, language, size, support and the evidence on your own tasks.
By the Halden editorial team
Start with constraints
Licence, location, hardware.
Read each model's licence for commercial use and conditions, decide where it will run, and check your hardware. These filter the shortlist more than benchmarks do.
The families
What each is known for.
DeepSeek is known for strong reasoning and coding at low cost. Qwen offers a very wide range of sizes and strong multilingual coverage. Mistral emphasises European deployment and flexible licensing. GLM models from Z.ai focus on long coding and agent tasks. Each family changes quickly, so check current versions.
Test on your work
A small evaluation beats opinion.
Collect twenty real tasks, run each model on them with the same prompts, and have a domain expert score the results for accuracy, completeness and tone. Include cost and speed.
- Use real tasks.
- Blind-score outputs.
- Record cost and latency.
Plan for change
Versioning and exit.
Pin the version you use, keep your prompts portable and review the landscape each quarter. Avoid designs that tie you to one model.
A next step
Turn this into a decision for your organization.
Explore how AI Advisory works with leaders and teams, or start with a short reflection on where you are today.