Open Source AI Showdown 2026: Llama 4 vs Gemma 4 vs DeepSeek V4 vs GLM-5.1
Comparison of four leading open-source large language models (LLMs) - Llama 4, Gemma 4, DeepSeek V4, and GLM-5.1 - in terms of parameters, context, licensing, and use cases.
Why it matters
The rapid progress of open-source AI models is disrupting the paid AI landscape, offering more affordable and accessible options for developers and businesses.
Key Points
- 1Four open-source LLMs are outperforming paid models on benchmarks like SWE-Bench Pro
- 2Llama 4 has the largest context window (1M tokens) but restrictive licensing
- 3Gemma 4 from Google runs locally on 18GB RAM with permissive Apache 2.0 license
- 4DeepSeek V4 offers 1/50th the price of GPT-5.4 with 90% quality
- 5GLM-5.1 tops the SWE-Bench Pro coding benchmark and supports 8-hour autonomous coding
Details
The article compares four prominent open-source large language models (LLMs) - Llama 4 from Meta, Gemma 4 from Google, DeepSeek V4, and GLM-5.1 from Z.ai (formerly Zhipu AI). These models use a Mixture of Experts (MoE) architecture, allowing them to prepare every output but serve each user only what they need. Llama 4 has the largest context window at 1 million tokens, giving it the highest MMLU (Multitask Metric for Language Understanding) score of 85.5% among open models, but its licensing is more restrictive. Gemma 4 can run locally on just 18GB of RAM and has the most permissive Apache 2.0 license. DeepSeek V4, with around 1 trillion parameters, offers API pricing that is 1/50th the cost of GPT-5.4 while maintaining 90% quality. GLM-5.1 is the first open-source model to top the SWE-Bench Pro coding benchmark, and it can work on a single coding task for up to 8 hours without human intervention. The article concludes that there is no single winner, and the right choice depends on the specific use case, with all four models being free or cheap enough to try.
No comments yet
Be the first to comment