Use the playground
Chat with the base model, add knowledge to memory, and inspect the version behind an answer.
The Playground has one conversation and a memory panel. It uses the same durable jobs, routing, and billing as the API. The current model is GLM 5.3; the hosted preview shows the interface but does not execute model work.
Start with base
The initial mode is Base model. Enter a message in the composer, press Enter to send, or Shift+Enter for a newline. The conversation includes your earlier successful turns. Failed calls do not become invented assistant messages.
Base mode explicitly selects base weights. It does not inherit an adapter from a subject called default. Choose New chat to clear conversation history. That action does not delete learned adapters or cancel a durable request.
Adjust the model
Open Model settings below the memory editor for model mode, temperature, maximum output tokens, and optional system instructions. On smaller screens, open Memory panel in the toolbar. Changing settings starts a fresh conversation to keep experiments from mixing different configurations.
Output limits include hidden reasoning tokens. A small limit can leave little room for a visible answer. Temperature ranges from zero to one; the default is zero. The playground does not display internal reasoning.
Use learned weights
Open Model settings, choose With memory, then use Memory settings to enter a memory ID or select an existing one. This is the subject_id used by the API. The default version choice, Auto · active version, resolves the active adapter for each new call. Choose a retained version to pin an experiment. Missing, foreign, or expired versions fail rather than silently switching to base.
A new subject starts from base. The ID names an assistant or body of knowledge. In Memory settings, optionally choose a customer ID (tenant_id) to keep that customer’s memories separate. The same memory name can exist for multiple customers. These identifiers are not secrets; your application must authorize their selection.
Internalize knowledge
Enter 20–16,000 string-length units of knowledge in What should it remember?, then select Internalize. A memory ID is provided by default; open Memory settings only when you need another identity, customer, or version. Use an example fills a fictional fact and a question so you can try the flow with no setup; it does not make a paid call. The composer’s + opens the same panel, including on mobile.
Submitting requests a validated candidate and automatic activation. The learning status stays next to the knowledge: waiting for a worker, preparing data, updating weights, checking answers, and saving weights reflect the observed worker phase. There is no estimated percentage. Run details exposes the request in Activity, the resulting version, and reported validation counts. A rejected or inactive candidate never appears as ready to test. You can leave the page while the durable job continues. Set the call’s spending limit before submitting. Learning is billed for measured compute and initial hosting, with no flat fee; activation may require review if another version changed during training.
After successful activation, the primary action becomes Test memory. This clears conversation history and system instructions, pins the learned version, and sends only the new question. Each question in this test is independent, even when earlier results remain visible. The fact stays visible in the sidebar for your reference but is never appended to the inference request. Changing model settings exits this test mode and starts a new conversation. This lets you test learned behavior with paraphrases and application questions, rather than testing whether a model can repeat a passage already in context.
Create memory from the Memory tab
Add knowledge opens the same knowledge field and Tinker run details. The dialog remains open after submission so you can follow the job. Closing it leaves View progress on the Memory page while you remain there. Once the version is ready, Test memory opens the playground with the correct customer, memory ID, and exact version already selected for a fresh test. Add more knowledge preserves the memory identity for the next update.
Inspect and integrate
Each response shows its resolved adapter, token count, settled charge, and Inspect request link. A pending job continues to reserve credits. Reconciliation means inspect the existing operation rather than click again to recreate it.
View code generates an OpenAI TypeScript request with your current messages and model settings. The snippet uses an environment variable for the API key and excludes learning-source content. The SDK should run on your server. For a clean test, View code contains only the pending question. See Integrations for other runtimes and a durable internalize tool.
Conversation history in the playground is temporary and is cleared when you leave. Completed job results remain in Activity. Keep canonical knowledge and evaluation records in your own application; the playground is a manual experiment surface, not a replacement for release evaluation.