Model comparison

GPT-5.6 Luna vs GLM-5.2

Compare GPT-5.6 Luna vs GLM-5.2 API pricing: input/output token costs, cache pricing, context windows, workload estimates, and routing fit.

GPT-5.6 Luna

openai · gpt-5.6-luna

Input
$1
Output
$6
Context
1.1M

GLM-5.2

zai · glm-5.2

Input
$1.4
Output
$4.4
Context
1M

Quick take

GPT-5.6 Luna has the lower input price at $1 per 1M input tokens. GPT-5.6 Luna is cheaper for the example blended workload below. GPT-5.6 Luna has the larger context window at 1.1M tokens.

Choose GPT-5.6 Luna if...

  • GPT-5.6 Luna is the better default for cost-sensitive traffic and repeated high-volume calls.
  • GPT-5.6 Luna is safer for long documents, repository analysis, and RAG prompts because it has the larger context window.
  • GPT-5.6 Luna is required if images, screenshots, or visual documents are part of the workflow.

Choose GLM-5.2 if...

  • GLM-5.2 is a reasonable pick when its provider, latency, or integration path fits your stack better.

Example workload cost

Estimates use input tokens plus 20% output tokens. They exclude provider discounts, cache hits, and tool/search surcharges.

Workload GPT-5.6 Luna GLM-5.2 Cheaper
1M input + 200K output $2.20 $2.28 GPT-5.6 Luna
10M input + 2M output $22.00 $22.80 GPT-5.6 Luna
100M input + 20M output $220.00 $228.00 GPT-5.6 Luna

Context, output, and capability fit

GPT-5.6 Luna provides the larger context window. Check max output separately when the task needs long reports, code generation, or full-document rewrites.

GPT-5.6 Luna max output
128K
GLM-5.2 max output
128K
GPT-5.6 Luna features
prompt caching, function calling, vision
GLM-5.2 features
prompt caching, function calling

Risk notes for GPT-5.6 Luna

  • No major capability risk is flagged in this snapshot, but provider pages should still be verified before production routing.

Risk notes for GLM-5.2

  • No major capability risk is flagged in this snapshot, but provider pages should still be verified before production routing.

Routing tags

frontierbudgetfastreasoningcodingagentslong-contextmultimodalcache-friendlyragopen-weightlocal-open

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