Quick Profile

GLM 5.1

Name: GLM 5.1
Brand: Z.ai

GLM 5.1 is a balanced model with long context support, suited to long-horizon coding and agentic workflows for enterprise teams.

Try GLM 5.1 with your team

Last reviewed: 2026-04-07

Context Window

202,752

Input / 1M

$1.26

Output / 1M

$3.96

Why this model

Z.ai lists GLM 5.1 as a long context option with $1.26 per 1M tokens input pricing, $3.96 per 1M tokens output pricing, and text->text modality support for enterprise AI operations.

GLM 5.1 offers long context capacity for enterprise prompts and documents.
Current pricing band is balanced: $1.26 per 1M tokens input and $3.96 per 1M tokens output.
Best-fit workloads include: Long-horizon coding, Agentic workflows, Technical reasoning.
Keep role-based access in place before broad rollout.

At a glance

Model ID: z-ai/glm-5.1
Context Window: 202,752 tokens
Modality: text->text
Input Modalities: text
Output Modalities: text
Input Price: $1.26 per 1M tokens
Output Price: $3.96 per 1M tokens
Provider: Z.ai
Listing Date: 2026-04-07

Strengths

GLM 5.1 is suited for long-horizon coding.
Supports long context for multi-step prompts and larger working sets.
Pricing profile is balanced, enabling predictable workload routing decisions.
Can be paired with policy guardrails for safer deployment at scale.

Tradeoffs

Without workload routing, teams may overuse this model for requests that fit lower-cost tiers.
Long-context prompts can increase spend and latency if prompts are not scoped carefully.
Balanced-price tiers still need policy-based routing to protect monthly budgets.
Text-only modality can limit workflows that rely on image, audio, or document interpretation.

Best for

GLM 5.1 for internal productivity assistants and knowledge workflows.
GLM 5.1 for tool-driven automation with governance checkpoints.
GLM 5.1 for complex analysis and long-form decision support.
GLM 5.1 for governed enterprise assistant workflows across teams.

Rollout checklist

Define where GLM 5.1 is default vs. fallback in your routing policy.
Enable role-based access and policy checks before opening access broadly.
Set spend guardrails by team and monitor weekly token consumption.
Start with one workflow, then expand after you verify quality and spend.
Re-run quality and cost benchmarks monthly as newer releases appear.

Related models

Explore adjacent model profiles for routing and benchmarking decisions.

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Safe AI Use Case Selector

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Tuning notes

max_tokens

Set completion limits to avoid unpredictable long-output spend.

temperature

Lower temperature for deterministic policy and compliance tasks.

top_p

Use tighter sampling for stable outputs in repeatable operations.

response_format

Prefer structured output where responses feed internal systems.

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AI Risk Test

Test what can go wrong before teams start using AI loosely across the company.

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A short risk summary with the main gaps to close.

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Knowledge Hub

GLM 5.1 FAQs

Choose GLM 5.1 when the workload aligns with long-horizon coding, agentic workflows, technical reasoning and quality targets justify its pricing profile.

It depends on workload mix. Most organizations use routing policies so routine traffic stays on lower-cost tiers.

Validate quality on real internal prompts, token efficiency, latency, and policy compliance behavior.

Deploy This Model With Governance

Use policy controls, role-based access, and budget guardrails before enabling advanced model tiers at scale.

Try GLM 5.1 with your team