GPT-5.6 Luna vs GLM-5.2
OpenAI's GPT-5.6 Luna and Z.ai's GLM-5.2 both target production language workloads, but they price and behave differently. Here is the side-by-side.
Pricing checked against provider documentation on . How we verify
The short answer
GPT-5.6 Luna is the cheaper option — roughly 4.8x less on a blended workload, and it suits high-volume work on a tight budget. GLM-5.2 justifies its premium when you need mit-licensed coding agents.
OpenAI • GPT-5.6
$0.20 / $1.20
/ 1M tokens (input / output)
After an 80% price cut in July 2026, Luna became the value outlier among frontier-family models: it outperforms the previous generation's top-end Opus tier on coding evals while costing about a fiftieth of Fable 5 per input token. This is the model to route bulk traffic through in a tiered architecture.
Z.ai • GLM-5
$1.40 / $4.40
/ 1M tokens (input / output)
A 744B-parameter MoE with 40B active, MIT-licensed, and tuned for long-horizon coding work. It sits between DeepSeek and Kimi on price and is the usual challenger when a cheaper model keeps looping or missing repository conventions — enough capability to finish the task without flagship pricing.
Input price
GLM-5.2 is 7.0x the price than GPT-5.6 Luna on input tokens.
Output price
GLM-5.2 is 3.7x the price than GPT-5.6 Luna on output tokens — usually the side that dominates the bill.
Monthly cost at three workload sizes
Standard (non-batch, non-cached) rates. Reasoning models will exceed these figures because thinking tokens bill as output.
| Workload | GPT-5.6 Luna | GLM-5.2 | Difference |
|---|---|---|---|
| Light — 1M in / 200K out | $0 | $2 | $2 |
| Moderate — 10M in / 2M out | $4 | $23 | $18 |
| Heavy — 100M in / 20M out | $44 | $228 | $184 |
Specification comparison
| Attribute | GPT-5.6 Luna | GLM-5.2 |
|---|---|---|
| Input (/ 1M tokens) | $0.20 | $1.40 |
| Output (/ 1M tokens) | $1.20 | $4.40 |
| Cached input | $0.02 | $0.26 |
| Context window | 1,048,576 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens | 131,072 tokens |
| Native reasoning | Yes | Yes |
| Knowledge cutoff | 2026-02 | 2026-02 |
| Relative latency | low | medium |
| Open weights | No | MIT |
| API model ID | gpt-5.6-luna | glm-5.2 |
| Status | stable | stable |
GPT-5.6 Luna: Cut 80% from the $1/$6 launch price on 2026-07-30.
GLM-5.2: Independently measured by Artificial Analysis; the vendor's own pricing page was unreachable at time of checking. Treat as approximate and confirm in the console.
Choose GPT-5.6 Luna if…
- Classification and content moderation
- High-frequency agent subtasks
- Bulk summarization
- Cost-sensitive chat features
Choose GLM-5.2 if…
- Coding agents on large repositories
- Long-horizon refactors
- Self-hosted agent stacks
- Structured output pipelines
Frequently asked
Is GPT-5.6 Luna or GLM-5.2 cheaper?
GPT-5.6 Luna is cheaper. On a blended 3:1 input-to-output workload it costs about 4.8x less than GLM-5.2.
Which has the larger context window, GPT-5.6 Luna or GLM-5.2?
GPT-5.6 Luna has the larger window at 1.05M tokens versus 1M.
Should I use GPT-5.6 Luna or GLM-5.2?
Pick GPT-5.6 Luna for high-volume work on a tight budget. Pick GLM-5.2 for mit-licensed coding agents. If cost dominates the decision, GPT-5.6 Luna wins; if you need the capability ceiling, benchmark both on your own evals before committing.