GLM-4.7-Flash vs GLM-5.3-Flash vs GPT-6 Luna
Too close to call on our weighted score (GPT-6 Luna 86, GLM-5.3-Flash 85, GLM-4.7-Flash 48). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.7-Flash
48/100- ECI—
- Price$0.06 / $0.40
- Context200K
- Z.ai (Zhipu)
GLM-5.3-Flash
85/100- ECI151.9
- Price$0.15 / $0.50
- Context1M
OpenAIGPT-6 Luna
86/100- ECI—
- Price$0.10 / $0.50
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (GPT-6 Luna 86/100, GLM-5.3-Flash 85/100, GLM-4.7-Flash 48/100), so choose by what matters most for your work: GPT-6 Luna for raw capability and GLM-4.7-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GLM-4.7-Flash and GPT-6 Luna has no Capabilities Index score yet.
- CapabilityGPT-6 LunaShared benchmarks: GPT-6 Luna 94.7% · GLM-5.3-Flash 92.0% · GLM-4.7-Flash 35.1%
- Lowest priceGLM-4.7-FlashGLM-4.7-Flash $0.145 · GPT-6 Luna $0.20 · GLM-5.3-Flash $0.237 per 1M tokens (3:1 blend)
- Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · GLM-5.3-Flash 1,000,000 · GLM-4.7-Flash 200,000 tokens
- Widest inputsGLM-5.3-FlashGLM-4.7-Flash: Text · GLM-5.3-Flash: Text, Images, PDFs, Video · GPT-6 Luna: Text, Images, PDFs
- Self-hostingGLM-4.7-Flash and GLM-5.3-FlashPublishes downloadable weights
| Measure | Weight | GLM-4.7-Flash | GLM-5.3-Flash | GPT-6 Luna |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 35 | 92 | 95 |
| Price | 25% | 90 | 79 | 83 |
| Inputs & features | 15% | 35 | 90 | 80 |
| Context window | 10% | 32 | 60 | 61 |
| Overall | 100% | 48/100 | 85/100 | 86/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-4.7-FlashZ.ai (Zhipu) | GLM-5.3-FlashZ.ai (Zhipu) | GPT-6 LunaOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 151.9 | — |
| ECI rank | — | #42 of 148 | — |
| GPQA DiamondGraduate-level science questions | 45.1% | 90.2% | 90.5% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 55.8% | 79.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 25.0% | 93.9% | 98.9% (best) |
| SimpleQA VerifiedShort factual questions | — | — | 41.4% |
| Price per million tokens | |||
| Input | $0.06 (best) | $0.15 | $0.10 |
| Output | $0.40 (best) | $0.50 | $0.50 |
| Cached input | — | $0.03 | $0.01 (best) |
| Blended (3:1) | $0.145 (best) | $0.237 | $0.20 |
| Long-context rate | Same rate | Same rate | Over 272K: $0.20 / $0.75 |
| Price source | Median of 13 providers | Official Z.AI API | Official OpenAI API |
| Limits | |||
| Context window | 200,000 tokens | 1,000,000 tokens | 1,050,000 tokens (best) |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yeslow · high · max | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.7-flash | glm-5.3-flash | gpt-6-luna |
| API providers | 19 | 65 (best) | 24 |
| Released | Jan 19, 2026 | Aug 26, 2026 | Sep 22, 2026 |
| Knowledge cutoff | Apr 2025 | — | May 18, 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.7-Flash$1.41
- GLM-5.3-Flash$2.50
- GPT-6 Luna$2.00
Which should you choose?
Which is better: GLM-4.7-Flash, GLM-5.3-Flash or GPT-6 Luna?
It is close. Our weighted score puts them within a point (GPT-6 Luna 86/100, GLM-5.3-Flash 85/100, GLM-4.7-Flash 48/100), so choose by what matters most for your work: GPT-6 Luna for raw capability and GLM-4.7-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GLM-4.7-Flash and GPT-6 Luna has no Capabilities Index score yet.
Which is cheaper, GLM-4.7-Flash, GLM-5.3-Flash or GPT-6 Luna?
GLM-4.7-Flash is cheaper at $0.06 input / $0.40 output per million tokens (median across 13 API providers; free on Z.AI). GPT-6 Luna costs $0.10 input / $0.50 output per million tokens (official OpenAI API price); GLM-5.3-Flash costs $0.15 input / $0.50 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.145 per million tokens for GLM-4.7-Flash versus $0.20 for GPT-6 Luna (1.4× as much) and $0.237 for GLM-5.3-Flash (1.6× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): GPT-6 Luna 94.7%, GLM-5.3-Flash 92.0% and GLM-4.7-Flash 35.1%. On individual benchmarks: GPQA Diamond — GPT-6 Luna 90.5%, GLM-5.3-Flash 90.2%, GLM-4.7-Flash 45.1%; OTIS Mock AIME 2024–2025 — GPT-6 Luna 98.9%, GLM-5.3-Flash 93.9%, GLM-4.7-Flash 25.0%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.7-Flash, GLM-5.3-Flash and GPT-6 Luna yet, so there is no like-for-like coding score. On overall capability, GPT-6 Luna leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-6 Luna has the largest context window at 1,050,000 tokens, against 1,000,000 for GLM-5.3-Flash and 200,000 for GLM-4.7-Flash. Maximum output per response: GLM-4.7-Flash up to 131,072, GLM-5.3-Flash up to 131,072, GPT-6 Luna up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.7-Flash accepts text; GLM-5.3-Flash accepts text, images, PDFs and video; GPT-6 Luna accepts text, images and PDFs. GLM-5.3-Flash handles the widest range of inputs.
Are any of these open source?
GLM-4.7-Flash and GLM-5.3-Flash publishes its weights and can be self-hosted; GPT-6 Luna is proprietary.
Which is newer?
GPT-6 Luna is the newest, released Sep 22, 2026. GLM-5.3-Flash came out Aug 26, 2026; GLM-4.7-Flash came out Jan 19, 2026. Knowledge cutoff: GLM-4.7-Flash Apr 2025, GPT-6 Luna May 18, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
