Model comparison - Similar price, same tier
GLM-5.3-Flash vs GPT-6 Luna
GLM-5.3-Flash is from Z.ai and GPT-6 Luna is from OpenAI. On list price, GPT-6 Luna charges 33% less than GLM-5.3-Flash for input ($0.10 vs $0.15 per 1M tokens), and both charge $0.50 per 1M output tokens. GLM-5.3-Flash has a 1,000,000-token context window and GPT-6 Luna 1,050,000 tokens, and both return up to 128,000 output tokens per response. GLM-5.3-Flash was released on August 26, 2026 and GPT-6 Luna on September 22, 2026. GLM-5.3-Flash publishes open weights (MIT); GPT-6 Luna is closed-weights.
Last verified from each provider's pricing page. All sources
Side-by-side specs
| Spec | GLM-5.3-Flash | GPT-6 Luna |
|---|---|---|
| Provider | Z.ai | OpenAI |
| Input / 1M tokens | $0.15 | $0.10 |
| Output / 1M tokens | $0.50 | $0.50 |
| Cache read / 1M | $0.03 | $0.01 |
| Cache write / 1M | - | $0.125 |
| Batch input / 1M | - | $0.05 |
| Batch output / 1M | - | $0.25 |
| Long-context rates above | - | 272,000 tokens |
| Context window | 1,000,000 | 1,050,000 |
| Max output | 128,000 | 128,000 |
| Release date | ||
| Weights | Open | Closed |
| License | MIT | - |
| API model id | glm-5.3-flash | gpt-6-luna |
| AI Gateway id | zai/glm-5.3-flash | openai/gpt-6-luna |
| Last verified |
Prices in USD per 1M tokens at each provider's standard first-party rate. A dash means the provider does not bill that item separately or no primary page states it.
What each costs in practice
The same three workloads every model page uses, worked from each model's standard list rates. Swap in your own token counts with the math on each model's page.
| Workload | GLM-5.3-Flash | GPT-6 Luna |
|---|---|---|
| One agent session1M input tokens and 100K output tokens, no caching. | $0.20 | $0.15 |
| A chat app10,000 requests a day at 2K input and 500 output tokens each. | $5.50$165.00 per 30-day month | $4.50$135.00 per 30-day month |
| The same session at a 90% cache hit90% of the input is read from the prompt cache. The one-time cache write premium is not included. | $0.092 | $0.069 |
Show the math
GLM-5.3-Flash
- One agent sessionInput: 1M x $0.15 = $0.15Output: 0.1M x $0.50 = $0.05
- A chat appInput: 20M x $0.15 = $3.00Output: 5M x $0.50 = $2.50
- The same session at a 90% cache hitCached input: 0.9M x $0.03 = $0.027Uncached input: 0.1M x $0.15 = $0.015Output: 0.1M x $0.50 = $0.05
GPT-6 Luna
- One agent sessionInput: 1M x $0.10 = $0.10Output: 0.1M x $0.50 = $0.05
- A chat appInput: 20M x $0.10 = $2.00Output: 5M x $0.50 = $2.50
- The same session at a 90% cache hitCached input: 0.9M x $0.01 = $0.009Uncached input: 0.1M x $0.10 = $0.01Output: 0.1M x $0.50 = $0.05
Benchmarks under the same setting
No board in the benchmark directory lists both GLM-5.3-Flash and GPT-6 Luna under the same setting, so there is no like-for-like score to show here.
Set them up in your tools
Step-by-step guides whose official docs list GLM-5.3-Flash or GPT-6 Luna by model id.
- Use GLM in AiderLists GLM-5.3-Flash
- Use GLM in Claude CodeLists GLM-5.3-Flash
- Use GLM in ClineLists GLM-5.3-Flash
- Use GLM in ContinueLists GLM-5.3-Flash
- Use GLM in GooseLists GLM-5.3-Flash
- Use GLM in Kilo CodeLists GLM-5.3-Flash
- Use GLM in OpenCodeLists GLM-5.3-Flash
- Use GLM in Roo CodeLists GLM-5.3-Flash
- Use GLM in ZedLists GLM-5.3-Flash
- Use Ollama in Claude CodeLists GLM-5.3-Flash
- Use OpenAI in AiderLists GPT-6 Luna
- Use OpenAI in ClineLists GPT-6 Luna
- Use OpenAI in Codex CLILists GPT-6 Luna
- Use OpenAI in ContinueLists GPT-6 Luna
- Use OpenAI in GooseLists GPT-6 Luna
- Use OpenAI in OpenCodeLists GPT-6 Luna
- Use OpenAI in Roo CodeLists GPT-6 Luna
- Use OpenAI in ZedLists GPT-6 Luna
Model pages
FAQ
How do GLM-5.3-Flash and GPT-6 Luna compare on price?
On list price, GPT-6 Luna charges 33% less than GLM-5.3-Flash for input ($0.10 vs $0.15 per 1M tokens), and both charge $0.50 per 1M output tokens. For one agent session of 1M input and 100K output tokens with no caching, that is $0.20 on GLM-5.3-Flash and $0.15 on GPT-6 Luna. Prices are each provider's first-party list rates, verified October 17, 2026 and October 17, 2026.
What are the context windows of GLM-5.3-Flash and GPT-6 Luna?
GLM-5.3-Flash has a 1,000,000-token context window and GPT-6 Luna 1,050,000 tokens, and both return up to 128,000 output tokens per response.
Are GLM-5.3-Flash and GPT-6 Luna open weights?
GLM-5.3-Flash's weights are published at huggingface.co under the MIT. GPT-6 Luna is closed-weights and is called through OpenAI's API as gpt-6-luna.
More comparisons
- Claude Haiku 5.5 vs GLM-5.3-FlashSimilar price, same tier
- Claude Haiku 5.5 vs GPT-6 LunaSimilar price, same tier
- DeepSeek V4.1 Flash vs GPT-6 LunaOpen weights vs closed
- DeepSeek V4.1 Flash vs GLM-5.3-FlashSimilar price, same tier
- GLM-5.3-Flash vs Qwen3.8-FlashSimilar price, same tier
- GPT-6 Luna vs Qwen3.8-FlashSimilar price, same tier
- Gemini 3.5 Flash-Lite vs GLM-5.3-FlashSimilar price, same tier
- GPT-5.6 Luna vs GPT-6 LunaSame provider, successor
Sources
GLM-5.3-Flash verified from docs.z.ai; GPT-6 Luna verified from developers.openai.com. This page is as current as the older of the two: .
- https://docs.z.ai/guides/overview/pricing
- https://developers.openai.com/api/docs/pricing
- https://docs.z.ai/guides/vlm/glm-5.3-flash
- https://docs.z.ai/guides/overview/overview
- https://docs.z.ai/release-notes/new-released
- https://docs.z.ai/openapi.json
- https://huggingface.co/zai-org/GLM-5.3-Flash
- https://ai-gateway.vercel.sh/v1/models
- https://developers.openai.com/api/docs/models/gpt-6-luna
- https://developers.openai.com/api/docs/changelog
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