Which is cheaper, GLM-4.5-AirX or GPT-5.6 Luna?
As of August 20, 2026, GPT-5.6 Luna is 75% cheaper on blended LLM API pricing. GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens ($1.40 blended 1M-in + 1M-out). GLM-4.5-AirX costs $1.10 / $4.50 per million tokens ($5.60 blended). Sources: https://docs.z.ai/guides/overview/pricing and https://developers.openai.com/api/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GLM-4.5-AirX vs GPT-5.6 Luna cost per million tokens?
GLM-4.5-AirX Z AI API pricing is $1.10 input and $4.50 output per million tokens via Z AI. GPT-5.6 Luna OpenAI API pricing is $0.20 input and $1.20 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GLM-4.5-AirX or GPT-5.6 Luna?
GPT-5.6 Luna has a published SWE-bench Verified score of 93%. GLM-4.5-AirX does not have that eval on this page yet.
What is the context window for GLM-4.5-AirX vs GPT-5.6 Luna?
GLM-4.5-AirX supports a 131K token context window, while GPT-5.6 Luna supports 1M tokens. GPT-5.6 Luna offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, GLM-4.5-AirX or GPT-5.6 Luna?
Shared benchmark scores for GLM-4.5-AirX and GPT-5.6 Luna are still limited. Check the comparison table for the evals each model has published. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is GLM-4.5-AirX or GPT-5.6 Luna better for production use?
Both GLM-4.5-AirX and GPT-5.6 Luna are production API models. For cost-sensitive production traffic, GPT-5.6 Luna has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between GLM-4.5-AirX and GPT-5.6 Luna in my app?
Yes. Call GLM-4.5-AirX through Z AI and GPT-5.6 Luna through OpenAI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this GLM-4.5-AirX vs GPT-5.6 Luna pricing data?
List rates are the latest published Z AI API pricing and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://docs.z.ai/guides/overview/pricing and https://developers.openai.com/api/docs/pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for GLM-4.5-AirX and GPT-5.6 Luna?
GLM-4.5-AirX supports up to an unspecified number of output tokens per request, while GPT-5.6 Luna supports up to 128K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, GLM-4.5-AirX or GPT-5.6 Luna?
GPT-5.6 Luna has a measured throughput of approximately 48.45216448188169 tokens/second. Throughput data for GLM-4.5-AirX is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this GLM-4.5-AirX vs GPT-5.6 Luna comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GLM-4.5-AirX or GPT-5.6 Luna from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
