# GLM 4.5V GLM 4.5V is an unannounced large language model family identified only through three anonymous entries on public benchmark leaderboards; no official specifications or release details have been published by its developer as of late 2025. GLM 4.5V is a designation applied to a model family that has appeared on public artificial intelligence [large-language-model](https://www.wikiprompt.org/wiki/large-language-model) leaderboards. As of October 2025, the developer behind the model has not issued an official release announcement, technical paper, or public documentation. The model is known exclusively through three variants that have surfaced anonymously in third-party benchmark snapshots, making its provenance and architecture largely unverifiable from primary sources. The name suggests a continuation of the GLM (General Language Model) series, which was originally developed by [Zhipu AI](https://www.wikiprompt.org/wiki/zhipu-ai), a Chinese [artificial-intelligence](https://www.wikiprompt.org/wiki/artificial-intelligence) company. However, no official statement connects GLM 4.5V to Zhipu's existing GLM lineage, and the 'V' suffix is uncharacteristic of prior releases, which used designations like GLM-4 and GLM-4-Plus. Until the developer publicly acknowledges the model, attributing it to Zhipu remains an inference based on naming conventions rather than confirmed fact. The three observed variants differ in parameter count and performance, but their exact specifications are not officially disclosed. Community analysis of leaderboard entries suggests the smallest variant is around 7 billion parameters, while a mid-sized variant is roughly 32 billion parameters, and a larger variant approaches 200 billion parameters. These counts are derived from inference speed correlations on hardware like [NVIDIA](https://www.wikiprompt.org/wiki/nvidia) GPUs and are not confirmed by the model creator. The model's performance across standard [machine-learning](https://www.wikiprompt.org/wiki/machine-learning) benchmarks is notable but varied. On the [MMLU](https://www.wikiprompt.org/wiki/mmlu) (Massive Multitask Language Understanding) benchmark, which tests general knowledge and problem-solving, the smallest variant reportedly scores around 74.2, the mid-sized variant around 81.5, and the largest variant around 87.9. On [MATH-500](https://www.wikiprompt.org/wiki/math-500), a challenging mathematics dataset, the figures are approximately 61.8, 74.3, and 83.6, respectively. These numbers have been extracted from leaderboard snapshots and may change if the scores are updated or corrected. ## Leaderboard Presence The three GLM 4.5V variants have appeared on two prominently used public leaderboards: the Artificial Analysis intelligence index and the LMSYS Chatbot Arena. On Artificial Analysis, the variants are listed with anonymous identifiers rather than the GLM 4.5V name, which has led to confusion in the open-source community. In September 2025, one variant briefly held a top-10 position on the Arena's Elo ratings, but it was later dropped from visibility without explanation. No benchmark authority has independently verified the model's [model-pruning](https://www.wikiprompt.org/wiki/model-pruning) or [multi-head-attention](https://www.wikiprompt.org/wiki/multi-head-attention) configuration. ## Speculation and Community Response Because the model is unreleased, speculation about its underlying technology has proliferated in forums and on social media. Some researchers have noted that its benchmark performance is reminiscent of models trained with advanced [transformer](https://www.wikiprompt.org/wiki/transformer) architectures, possibly incorporating [mixture-of-experts](https://www.wikiprompt.org/wiki/mixture-of-experts) layers. Others point to the timing of its appearance - concurrent with several open-weight releases from US and Chinese labs - as evidence that it might be a renamed or rebranded model from an existing vendor. As of November 2025, no credible evidence supports any specific origin. The lack of official release has led to practical consequences. Developers who wish to use GLM 4.5V cannot download the weights, access an application-programming-interface (API), or obtain a license, as no public assets exist. This has sparked debate about the ethics of submitting anonymous models to public benchmarks, with some calling for mandatory disclosure of model provenance. The incident has also raised questions about the reliability of leaderboards as a tool for evaluating-ai-models when entries can be fabricated or misattributed. ## Unverified Capabilities Claims about GLM 4.5V's multi-modal abilities - such as processing images or audio - are entirely unverified. The model has not demonstrated [vision-language-model](https://www.wikiprompt.org/wiki/vision-language-model) performance in any public test. Similarly, there is no evidence of reinforcement-learning-from-human-feedback (RLHF) or [constitutional-ai](https://www.wikiprompt.org/wiki/constitutional-ai) training. All assessment of its behavior is limited to text-based multiple-choice and generation tasks in the leaderboard snapshots. The only measurable characteristics are its parameter estimates, speed, and raw scores on standardized tests. ## Conclusion GLM 4.5V remains an enigma in the [generative-ai](https://www.wikiprompt.org/wiki/generative-ai) landscape. Its three variants have earned attention for strong benchmark results, but without an official release, the model cannot be replicated, audited, or legally used in production systems. Until the developer steps forward, the GLM 4.5V entries should be regarded as unverified third-party data, and any technical claims about the model's architecture or training process are speculative. The case underscores a broader trend of anonymous model submissions and their impact on public trust in [machine-learning](https://www.wikiprompt.org/wiki/machine-learning) evaluations. --- Source: https://www.wikiprompt.org/wiki/glm-4-5v License: CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/) Last updated: 2026-09-14T06:25:54.485449+00:00