The open-source reasoning model market is hot in 2026. DeepSeek, GLM, and Kimi are fiercely competing in terms of performance and cost-effectiveness. I’ve compiled a summary of who offers the best value.
First, DeepSeek-R1 is currently the most notable open-source reasoning model. According to Clarifai’s 2026 analysis of open-source reasoning models, DeepSeek-R1 shows performance close to commercial models in math and coding benchmarks. It adopts a 671B parameter MoE structure, so computational efficiency is high because only some experts are activated during actual inference. A major advantage is that it is released under the MIT license, so there are no restrictions on commercial use.
GLM-Z1 is a model developed by a team at Tsinghua University in China and excels at complex reasoning tasks. SiliconFlow’s guide analyzes that the GLM series is highly rated for multilingual reasoning capabilities. In particular, it shows stable performance in mixed Chinese and English tasks, and a lightweight version is also provided, allowing it to be deployed in various environments.
Kimi k1.5 is a reasoning-specialized model released by Moonshot AI. According to WhatLLM’s January 2026 analysis, Kimi excels at processing long contexts. It can process up to 128K tokens, giving it an advantage in long document-based reasoning. However, it is evaluated to be somewhat behind DeepSeek-R1 in pure mathematical reasoning.
In terms of cost-effectiveness, DeepSeek-R1 is the most balanced choice. Operating costs are low compared to performance, and community support is active. GLM-Z1 has strengths in multilingual environments, and Kimi k1.5 has strengths in long text processing tasks. Ultimately, the optimal model depends on the use case.
Successor versions of all three models are expected in the second half of 2026. The point at which the performance of open-source reasoning models surpasses commercial models is not far off. If you are a developer burdened by tool costs, now is the right time to consider open-source reasoning models. I hope this summary is helpful in choosing a model.
FAQ
Q: Which model is most suitable for coding tasks among DeepSeek-R1, GLM-Z1, and Kimi k1.5?
A: DeepSeek-R1 scores the highest based on coding benchmarks. Thanks to the MoE structure, computational efficiency is also good, making it suitable for coding assistant purposes.
Q: Can all three models be used commercially without restrictions?
A: DeepSeek-R1 has almost no restrictions under the MIT license. GLM-Z1 and Kimi k1.5 each apply their own licenses, so you must check the license conditions before commercial use.
Q: Which model can be run most lightly in a local environment?
A: All three models offer lightweight versions. DeepSeek-R1 has various distilled versions from 1.5B to 70B, and GLM also releases small models, so you can choose according to your local GPU specifications.