GLM-5 Turbo
glm-5-turbo
Last refreshed 2026-05-22. Next refresh: weekly.
GLM-5 Turbo is worth evaluating for rag, agents, and long context when its provider route and context window match the workload.
Decision context: RAG task fit, 2 tracked provider routes, and research from 2026-04-19.
Use it for
- Teams evaluating rag, agents, and long context
- Workloads that can use a 200k context window
- Buyers comparing 2 tracked provider routes
Do not use it for
- Vision or document-understanding workloads
Cheapest output
$4.00
OpenRouter per 1M tokens
Provider routes
2
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-04-19
Researched 33d ago
Top use-case fit
RAG
Included by capability and metadata signals in the decision map.
Agents
Included by capability and metadata signals in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Provider price ladder
Compare all 2| Provider | Input / 1M | Output / 1M | Cache | Route |
|---|---|---|---|---|
| OpenRouter | $1.20 | $4.00 | - | Serverless |
| Vercel AI Gateway | $1.20 | $4.00 | read $0.240 | Serverless |
Benchmark peer barsfor RAG
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
Purpose-built variant of GLM-5 optimized for agent orchestration and complex automated workflows. Features native agent-friendly training emphasizing tool use, command following, and persistent task execution. Designed for OpenClaw (Lobster Agent) workflows with ~0.67% tool-call error rate. Achieves 20% higher inference performance vs base GLM-5.
GLM-5 Turbo has a 200K-token context window.
GLM-5 Turbo input tokens at $1.2/1M, output at $4/1M.
