GLM-5.3-Flash vs GPT-6 Luna vs Claude Sonnet 5.5
GPT-6 Luna comes out ahead, 84 to 79 and 71 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-5.3-Flash
79/100- ECI151.9
- Price$0.15 / $0.50
- Context1M
- Our pick
OpenAIGPT-6 Luna
84/100- ECI—
- Price$0.10 / $0.50
- Context1.05M
AnthropicClaude Sonnet 5.5
71/100- ECI165.2
- Price$2.00 / $10.00
- Context1M
GPT-6 Luna is our pick
GPT-6 Luna is the better all-round choice, scoring 84/100 against GLM-5.3-Flash (79) and Claude Sonnet 5.5 (71). It leads on price. GLM-5.3-Flash wins on inputs & features. Claude Sonnet 5.5 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3 and OTIS Mock AIME 2024–2025), because GPT-6 Luna has no Capabilities Index score yet.
- CapabilityClaude Sonnet 5.5Shared benchmarks: Claude Sonnet 5.5 94.8% · GPT-6 Luna 89.4% · GLM-5.3-Flash 79.9%
- Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · GLM-5.3-Flash $0.237 · Claude Sonnet 5.5 $4.00 per 1M tokens (3:1 blend)
- Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · GLM-5.3-Flash 1,000,000 · Claude Sonnet 5.5 1,000,000 tokens
- Widest inputsGLM-5.3-FlashGLM-5.3-Flash: Text, Images, PDFs, Video · GPT-6 Luna: Text, Images, PDFs · Claude Sonnet 5.5: Text, Images, PDFs
- Self-hostingGLM-5.3-FlashPublishes downloadable weights
| Measure | Weight | GLM-5.3-Flash | GPT-6 Luna | Claude Sonnet 5.5 |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 80 | 89 | 95 |
| Price | 25% | 79 | 83 | 21 |
| Inputs & features | 15% | 90 | 80 | 80 |
| Context window | 10% | 60 | 61 | 60 |
| Overall | 100% | 79/100 | 84/100 | 71/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.3-FlashZ.ai (Zhipu) | GPT-6 LunaOpenAI | Claude Sonnet 5.5Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 151.9 | — | 165.2 (best) |
| ECI rank | #42 of 148 | — | #3 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 90.2% | 90.5% | 95.6% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 55.8% | 79.0% | 88.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.9% | 98.9% | 100% (best) |
| SimpleQA VerifiedShort factual questions | — | 41.4% | 46.5% (best) |
| Price per million tokens | |||
| Input | $0.15 | $0.10 (best) | $2.00 |
| Output | $0.50 (best) | $0.50 (best) | $10.00 |
| Cached input | $0.03 | $0.01 (best) | $0.20 |
| Blended (3:1) | $0.237 | $0.20 (best) | $4.00 |
| Long-context rate | Same rate | Over 272K: $0.20 / $0.75 | Same rate |
| Price source | Official Z.AI API | Official OpenAI API | Official Anthropic API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,050,000 tokens (best) | 1,000,000 tokens |
| Max output | 131,072 tokens (best) | 128,000 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | Yes |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yeslow · high · max | Yeslow · medium · high · xhigh · max | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-5.3-flash | gpt-6-luna | claude-sonnet-5-5 |
| API providers | 65 (best) | 24 | 23 |
| Released | Aug 26, 2026 | Sep 22, 2026 | Sep 28, 2026 |
| Knowledge cutoff | — | May 18, 2026 | Jun 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-5.3-Flash$2.50
- GPT-6 Luna$2.00
- Claude Sonnet 5.5$40.00
Which should you choose?
Which is better: GLM-5.3-Flash, GPT-6 Luna or Claude Sonnet 5.5?
GPT-6 Luna is the better all-round choice, scoring 84/100 against GLM-5.3-Flash (79) and Claude Sonnet 5.5 (71). It leads on price. GLM-5.3-Flash wins on inputs & features. Claude Sonnet 5.5 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3 and OTIS Mock AIME 2024–2025), because GPT-6 Luna has no Capabilities Index score yet.
Which is cheaper, GLM-5.3-Flash, GPT-6 Luna or Claude Sonnet 5.5?
GPT-6 Luna is cheaper at $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); Claude Sonnet 5.5 costs $2.00 input / $10.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for GPT-6 Luna versus $0.237 for GLM-5.3-Flash (1.2× as much) and $4.00 for Claude Sonnet 5.5 (20× 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, FrontierMath Tiers 1–3 and OTIS Mock AIME 2024–2025): Claude Sonnet 5.5 94.8%, GPT-6 Luna 89.4% and GLM-5.3-Flash 79.9%. On individual benchmarks: GPQA Diamond — Claude Sonnet 5.5 95.6%, GPT-6 Luna 90.5%, GLM-5.3-Flash 90.2%; FrontierMath Tiers 1–3 — Claude Sonnet 5.5 88.8%, GPT-6 Luna 79.0%, GLM-5.3-Flash 55.8%; OTIS Mock AIME 2024–2025 — Claude Sonnet 5.5 100%, GPT-6 Luna 98.9%, GLM-5.3-Flash 93.9%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3-Flash, GPT-6 Luna and Claude Sonnet 5.5 yet, so there is no like-for-like coding score. On overall capability, Claude Sonnet 5.5 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 1,000,000 for Claude Sonnet 5.5. Maximum output per response: GLM-5.3-Flash up to 131,072, GPT-6 Luna up to 128,000, Claude Sonnet 5.5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3-Flash accepts text, images, PDFs and video; GPT-6 Luna accepts text, images and PDFs; Claude Sonnet 5.5 accepts text, images and PDFs. GLM-5.3-Flash handles the widest range of inputs.
Are any of these open source?
GLM-5.3-Flash publishes its weights and can be self-hosted; GPT-6 Luna and Claude Sonnet 5.5 is proprietary.
Which is newer?
Claude Sonnet 5.5 is the newest, released Sep 28, 2026. GPT-6 Luna came out Sep 22, 2026; GLM-5.3-Flash came out Aug 26, 2026. Knowledge cutoff: GPT-6 Luna May 18, 2026, Claude Sonnet 5.5 Jun 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.
Related comparisons
- GLM-5.3-Flash vs DeepSeek V4.1 FlashDeepSeek · ECI 155.0
- GLM-5.3-Flash vs Inkling SmallThinking Machines · ECI 150.2
- GLM-5.3-Flash vs Qwen3.8 27BAlibaba (Qwen) · ECI 149.4
- GPT-6 Luna vs DeepSeek V4 Flash 0731DeepSeek · ECI 154.5
- GPT-6 Luna vs MiniMax-M3MiniMax · ECI 147.0
- GPT-6 Luna vs Inkling SmallThinking Machines · ECI 150.2
