7.6
Intelligence Index
Above 17% of 106 other free models
Z.
GLM 4.5V
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...
- Input
- text
- image
- Output
- text
Providers
Available through 1 free provider. Use the model ID and API settings below to connect.
Vercel AI Gateway
VAVercel AI Gateway
* The provider match may differ from this model. Check its docs for details.
Benchmarks
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Bars show scores from other free models on this site. The marker shows this model’s score. Comparisons include only models with a score for that index.
Scores from Artificial AnalysisFrequently asked questions
Free access, setup, and what to expect.
Free API access for GLM 4.5V is listed through Vercel AI Gateway, but a specific request or token allowance isn’t available in the listed data. Check the GLM 4.5V provider pricing and rate limits for what’s included and any account requirements.
To use GLM 4.5V, choose one of the listed GLM 4.5V API providers and follow the provider’s account and API-key setup guide. Copy the GLM 4.5V model ID and connection settings for your chosen provider into your app or API client. Model IDs can differ between providers. API requests go directly to the provider; Free Models is a comparison site.
GLM 4.5V accepts text and image as listed input formats. Listed output formats include text. Image or audio input support does not imply image or audio generation. Check the chosen provider’s GLM 4.5V documentation for supported file types and request formats.
GLM 4.5V has a listed context window of 66K tokens. Tokens are small pieces of content rather than a word count. Instructions, conversation history, and other inputs use context space, and the response also needs room. The maximum output length for GLM 4.5V may be smaller than the context window and can vary by provider.
GLM 4.5V has both reasoning and tool calling listed as supported capabilities. Reasoning enables additional processing for complex problems. Tool calling allows a model to request functions that your app executes. Check the chosen provider’s documentation for capability availability and setup.
Review the listed GLM 4.5V benchmark results to compare performance on measured tasks. Compare scores within the same benchmark: coding indexes, Elo ratings, and win rates measure different things. The index comparison charts include only scored free models listed on Free Models. Evaluate GLM 4.5V on examples from your own task alongside context size and provider limits.