The two big stories of AI in 2026 so far have been the incredible rise in usage and praise for Anthropic’s Claude Code and a similar huge boost in user adoption for Google’s Gemini 3 AI model family released late last year — the latter of which includes Nano Banana Pro (also known as Gemini 3 Pro Image), a powerful, fast, and flexible image generation model that renders complex, text-heavy infographics quickly and accurately, making it an excellent fit for enterprise use (think: collateral, trainings, onboarding, stationary, etc).But of course, both of those are proprietary offerings. And yet, open source rivals have not been far behind. This week, we got a new open source alternative to Nano Banana Pro in the category of precise, text-heavy image generators: GLM-Image, a new 16-billion parameter open-source model from recently public Chinese startup Z.ai.By abandoning the industry-standard “pure diffusion” architecture that powers most leading image generator models in favor of a hybrid auto-regressive (AR) + diffusion design, GLM-Image has achieved what was previously thought to be the domain of closed, proprietary models: state-of-the-art performance in generating text-heavy, information-dense visuals like infographics, slides, and technical diagrams.It even beats Google’s Nano Banana Pro on the shared by z.ai — though in practice, my own quick usage found it to be far less accurate at instruction following and text rendering (and other users seem to agree). But for enterprises seeking cost-effective and customizable, friendly-licensed alternatives to proprietary AI models, z.ai’s GLM-Image may be “good enough” or then some to take over the job of a primary image generator, depending on their specific use cases, needs and requirements.The Benchmark: Toppling the Proprietary GiantThe most compelling argument for GLM-Image is not its aesthetics, but its precision. In the CVTG-2k (Complex Visual Text Generation) benchmark, which evaluates a model’s ability to render accurate text across multiple regions of an image, GLM-Image scored a Word Accuracy average of 0.9116.To put that number in perspective, Nano Banana 2.0 aka Pro—often cited as the benchmark for enterprise reliability—scored 0.7788. This isn’t a marginal gain; it is a generational leap in semantic control.While Nano Banana Pro retains a slight edge in single-stream English long-text generation (0.9808 vs. GLM-Image’s 0.9524), it falters significantl …
