GLM-5.1

GLM-5.1 · Prompts and workflows

Tasks you can hand to GLM-5.1

Browse executable prompts and workflows by task, content type, and runtime. Each card shows inputs, verification status, and the original source.

Runtimes vary by resource and may include an API, CLI, agent framework, or browser coding environment. Check each card for details.

All resources

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4 / 4
UnverifiedZ.AI Developer Document / Z.ai

GLM-5.1: Long-horizon Agent and Claude Code Configuration

GLM-5.1 should be configured as a “long-horizon engineering Agent”: provide ample context and output budget, clarify the role, tech stack, and acceptance criteria first, then let it loop through execution, compilation, testing, and iteration; in Claude Code, you can switch the model name directly to `GLM-5.1`..

Content typeConfiguration
Inputsmodel ID, repository, acceptance checks, output budget
StatusZ.AI API or Claude Code-compatible harness
AgentCodingreasoning
UnverifiedGitHub kvcache-ai/ktransformers

GLM-5.1: SGLang Heterogeneous Deployment and Interleaved Thinking Configuration

Local deployment of GLM-5.1 depends on the exact `transformers==5.3.0` version and SGLang parser configuration; coding Agent workflows must enable `Interleaved + Preserved Thinking` mode to prevent multi-turn forgetting..

Content typeConfiguration
InputsGPU/CPU layout, package versions, parser settings, test task
StatusKTransformers and SGLang local deployment
CodingreasoningAPI configuration
UnverifiedGitHub zai-org/GLM-5

GLM-5.1: Claude Code Tool Discovery and System Role Compatibility Workaround

When using GLM-5.1 in Claude Code or a multi-Agent framework, you must explicitly inject `tool_reference` parsing rules into the system prompt to prevent tool deadlocks, and intercept the `system` role in `messages[]` to avoid HTTP 422 errors..

Content typeWorkflow
Inputstool_reference schema, message roles, error trace, regression task
StatusClaude Code or multi-agent message adapter
AgentAPI configurationCoding
Unverifiedreddit.com

GLM-5.1: OpenCode Multi-Model Orchestration and Anti-Overthinking Prompt

Embedding GLM-5.1 in a multi-model pipeline as a “high-value code executor,” together with a system prompt that enforces action, can effectively resolve overthinking deadlocks in Agents and YAML indentation defects..

Content typeWorkflow
Inputsmodel roles, task slices, action budget, YAML checks
StatusOpenCode multi-model orchestration
AgentCodingcost

GLM-5.1

Use GLM-5.1 in Tabbit

After downloading, check the models and features available to your account. API and local-code steps still require their own runtime.