ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GLM-5.3-Flash vs GPT-5.6 Luna

Too close to call on our weighted score (GLM-5.3-Flash 80, GPT-5.6 Luna 78). The right pick depends on what you value most.

  1. Z.ai (Zhipu)

    GLM-5.3-Flash

    Released Aug 26, 2026

    80/100
    • ECI151.9
    • Price$0.15 / $0.50
    • Context1M
    Full specs Remove GLM-5.3-Flash

  2. OpenAI

    GPT-5.6 Luna

    Released Jul 9, 2026

    78/100
    • ECI156.5
    • Price$0.20 / $1.20
    • Context1.05M
    Full specs Remove GPT-5.6 Luna

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GLM-5.3-Flash 80/100, GPT-5.6 Luna 78/100), so choose by what matters most for your work: GPT-5.6 Luna for raw capability and GLM-5.3-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5.6 LunaCapabilities Index (ECI): GPT-5.6 Luna 156.5 · GLM-5.3-Flash 151.9
  • Lowest priceGLM-5.3-FlashGLM-5.3-Flash $0.237 · GPT-5.6 Luna $0.45 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.6 LunaGPT-5.6 Luna 1,050,000 · GLM-5.3-Flash 1,000,000 tokens
  • Widest inputsGLM-5.3-FlashGLM-5.3-Flash: Text, Images, PDFs, Video · GPT-5.6 Luna: Text, Images, PDFs
  • Self-hostingGLM-5.3-FlashPublishes downloadable weights
How the score is built
MeasureWeightGLM-5.3-FlashGPT-5.6 Luna
CapabilityCapabilities Index (ECI)50%8186
Price25%7966
Inputs & features15%9080
Context window10%6061
Overall100%80/10078/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

GLM-5.3-Flash vs GPT-5.6 Luna specifications side by side
SpecificationGLM-5.3-FlashZ.ai (Zhipu)GPT-5.6 LunaOpenAI
Capability
Capabilities Index (ECI)151.9156.5 (best)
ECI rank#42 of 148#21 of 148 (best)
GPQA DiamondGraduate-level science questions90.2%91.6% (best)
FrontierMath Tiers 1–3Research-level mathematics55.8%82.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics93.9%98.3% (best)
SimpleQA VerifiedShort factual questions—41.0%
Price per million tokens
Input$0.15 (best)$0.20
Output$0.50 (best)$1.20
Cached input$0.03$0.02 (best)
Blended (3:1)$0.237 (best)$0.45
Long-context rateSame rateOver 272K: $0.40 / $1.80
Price sourceOfficial Z.AI APIOfficial OpenAI API
Limits
Context window1,000,000 tokens1,050,000 tokens (best)
Max output131,072 tokens (best)128,000 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsYesYes
AudioNoNo
VideoYesNo
ReasoningYeslow · high · maxYeslow · medium · high · xhigh · max
Tool callingYesYes
Structured outputYesYes
Availability
WeightsOpenProprietary
API model IDglm-5.3-flashgpt-5.6-luna
API providers65 (best)38
ReleasedAug 26, 2026Jul 9, 2026
Knowledge cutoff—Feb 16, 2026
03 — Cost

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-5.6 Luna$4.40
04 — Questions

Which should you choose?

Which is better: GLM-5.3-Flash or GPT-5.6 Luna?

It is close. Our weighted score puts them within 2 points (GLM-5.3-Flash 80/100, GPT-5.6 Luna 78/100), so choose by what matters most for your work: GPT-5.6 Luna for raw capability and GLM-5.3-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GLM-5.3-Flash or GPT-5.6 Luna?

GLM-5.3-Flash is cheaper at $0.15 input / $0.50 output per million tokens (official Z.AI API price). GPT-5.6 Luna costs $0.20 input / $1.20 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.237 per million tokens for GLM-5.3-Flash versus $0.45 for GPT-5.6 Luna (1.9× as much).

Which scores higher on benchmarks?

GPT-5.6 Luna scores higher on the Capabilities Index (ECI): GPT-5.6 Luna 156.5 (#21 of 148) and GLM-5.3-Flash 151.9 (#42 of 148). The confidence ranges of the top two overlap (154.1–158.6 vs 149.4–154.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-5.6 Luna 91.6%, GLM-5.3-Flash 90.2%; FrontierMath Tiers 1–3 — GPT-5.6 Luna 82.1%, GLM-5.3-Flash 55.8%; OTIS Mock AIME 2024–2025 — GPT-5.6 Luna 98.3%, GLM-5.3-Flash 93.9%.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-5.3-Flash and GPT-5.6 Luna yet, so there is no like-for-like coding score. On overall capability, GPT-5.6 Luna leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

GPT-5.6 Luna has the largest context window at 1,050,000 tokens, against 1,000,000 for GLM-5.3-Flash. Maximum output per response: GLM-5.3-Flash up to 131,072, GPT-5.6 Luna up to 128,000 tokens.

Which can read images, PDFs, audio or video?

GLM-5.3-Flash accepts text, images, PDFs and video; GPT-5.6 Luna 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-5.6 Luna is proprietary.

Which is newer?

GLM-5.3-Flash is the newest, released Aug 26, 2026. GPT-5.6 Luna came out Jul 9, 2026. Knowledge cutoff: GPT-5.6 Luna Feb 16, 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.

05 — Keep comparing

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