GLM-5.3-Flash vs Gemini 2.5 Flash-Lite vs GPT-6 Luna
Gemini 2.5 Flash-Lite comes out ahead, 85 to 79 and 78 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
GoogleGemini 2.5 Flash-Lite
85/100- ECI133.9
- Price$0.10 / $0.40
- Context1.05M
OpenAIGPT-6 Luna
78/100- ECI—
- Price$0.10 / $0.50
- Context1.05M
Gemini 2.5 Flash-Lite is our pick
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against GLM-5.3-Flash (79) and GPT-6 Luna (78). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite $0.175 · GPT-6 Luna $0.20 · GLM-5.3-Flash $0.237 per 1M tokens (3:1 blend)
- Longest contextGPT-6 Luna and Gemini 2.5 Flash-LiteGPT-6 Luna 1,050,000 · Gemini 2.5 Flash-Lite 1,048,576 · GLM-5.3-Flash 1,000,000 tokens
- Widest inputsGemini 2.5 Flash-LiteGLM-5.3-Flash: Text, Images, PDFs, Video · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · GPT-6 Luna: Text, Images, PDFs
- Self-hostingGLM-5.3-FlashPublishes downloadable weights
| Measure | Weight | GLM-5.3-Flash | Gemini 2.5 Flash-Lite | GPT-6 Luna |
|---|---|---|---|---|
| Price | 50% | 79 | 86 | 83 |
| Inputs & features | 30% | 90 | 100 | 80 |
| Context window | 20% | 60 | 61 | 61 |
| Overall | 100% | 79/100 | 85/100 | 78/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.3-FlashZ.ai (Zhipu) | Gemini 2.5 Flash-LiteGoogle | GPT-6 LunaOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 151.9 (best) | 133.9 | — |
| ECI rank | #42 of 148 (best) | #118 of 148 | — |
| GPQA DiamondGraduate-level science questions | 90.2% | — | 90.5% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 55.8% | — | 79.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.9% | — | 98.9% (best) |
| SimpleQA VerifiedShort factual questions | — | — | 41.4% |
| Price per million tokens | |||
| Input | $0.15 | $0.10 (best) | $0.10 (best) |
| Output | $0.50 | $0.40 (best) | $0.50 |
| Cached input | $0.03 | $0.01 (best) | $0.01 (best) |
| Blended (3:1) | $0.237 | $0.175 (best) | $0.20 |
| Long-context rate | Same rate | Same rate | Over 272K: $0.20 / $0.75 |
| Price source | Official Z.AI API | Official Google API | Official OpenAI API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,048,576 tokens | 1,050,000 tokens (best) |
| Max output | 131,072 tokens (best) | 65,536 tokens | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | Yes |
| Audio | No | Yes | No |
| Video | Yes | Yes | No |
| Reasoning | Yeslow · high · max | Yes | 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 | gemini-2.5-flash-lite | gpt-6-luna |
| API providers | 65 (best) | 20 | 24 |
| Released | Aug 26, 2026 | Jun 17, 2025 | Sep 22, 2026 |
| Knowledge cutoff | — | Jan 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-5.3-Flash$2.50
- Gemini 2.5 Flash-Lite$1.80
- GPT-6 Luna$2.00
Which should you choose?
Which is better: GLM-5.3-Flash, Gemini 2.5 Flash-Lite or GPT-6 Luna?
Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against GLM-5.3-Flash (79) and GPT-6 Luna (78). It leads on price and inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-5.3-Flash, Gemini 2.5 Flash-Lite or GPT-6 Luna?
Gemini 2.5 Flash-Lite is cheaper at $0.10 input / $0.40 output per million tokens (official Google API price). 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 $0.175 per million tokens for Gemini 2.5 Flash-Lite versus $0.20 for GPT-6 Luna (1.1× as much) and $0.237 for GLM-5.3-Flash (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-5.3-Flash has an ECI of 151.9, Gemini 2.5 Flash-Lite has an ECI of 133.9 and GPT-6 Luna has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3-Flash, Gemini 2.5 Flash-Lite and GPT-6 Luna yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-6 Luna and Gemini 2.5 Flash-Lite have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for GLM-5.3-Flash. Maximum output per response: GLM-5.3-Flash up to 131,072, Gemini 2.5 Flash-Lite up to 65,536, GPT-6 Luna up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3-Flash accepts text, images, PDFs and video; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; GPT-6 Luna accepts text, images and PDFs. Gemini 2.5 Flash-Lite handles the widest range of inputs.
Are any of these open source?
GLM-5.3-Flash publishes its weights and can be self-hosted; Gemini 2.5 Flash-Lite and 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; Gemini 2.5 Flash-Lite came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Flash-Lite Jan 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.
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