ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GLM-5.3-Flash vs GPT-6 Luna vs Qwen3.8 Max

GPT-6 Luna comes out ahead, 84 to 79 and 71 on our weighted score, and it is the cheaper option too.

  1. Z.ai (Zhipu)

    GLM-5.3-Flash

    Released Aug 26, 2026

    79/100
    • ECI151.9
    • Price$0.15 / $0.50
    • Context1M
  2. Our pick

    OpenAI

    GPT-6 Luna

    Released Sep 22, 2026

    84/100
    • ECI—
    • Price$0.10 / $0.50
    • Context1.05M
  3. Alibaba (Qwen)

    Qwen3.8 Max

    Released Aug 3, 2026

    71/100
    • ECI156.6
    • Price$2.00 / $6.00
    • Context1M
01 — Verdict

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 Qwen3.8 Max (71). It leads on price. 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.

  • CapabilityGPT-6 LunaShared benchmarks: GPT-6 Luna 89.4% · Qwen3.8 Max 89.0% · GLM-5.3-Flash 79.9%
  • Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · GLM-5.3-Flash $0.237 · Qwen3.8 Max $3.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · GLM-5.3-Flash 1,000,000 · Qwen3.8 Max 1,000,000 tokens
  • Widest inputsGLM-5.3-Flash and Qwen3.8 MaxGLM-5.3-Flash: Text, Images, PDFs, Video · GPT-6 Luna: Text, Images, PDFs · Qwen3.8 Max: Text, Images, PDFs, Video
  • Self-hostingGLM-5.3-FlashPublishes downloadable weights
How the score is built
MeasureWeightGLM-5.3-FlashGPT-6 LunaQwen3.8 Max
CapabilityShared benchmarks50%808989
Price25%798327
Inputs & features15%908090
Context window10%606160
Overall100%79/10084/10071/100
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-6 Luna vs Qwen3.8 Max specifications side by side
SpecificationGLM-5.3-FlashZ.ai (Zhipu)GPT-6 LunaOpenAIQwen3.8 MaxAlibaba (Qwen)
Capability
Capabilities Index (ECI)151.9—156.6 (best)
ECI rank#42 of 148—#20 of 148 (best)
GPQA DiamondGraduate-level science questions90.2%90.5%92.7% (best)
FrontierMath Tiers 1–3Research-level mathematics55.8%79.0% (best)74.7%
OTIS Mock AIME 2024–2025Competition mathematics93.9%98.9%99.4% (best)
SimpleQA VerifiedShort factual questions—41.4%45.8% (best)
Price per million tokens
Input$0.15$0.10 (best)$2.00
Output$0.50 (best)$0.50 (best)$6.00
Cached input$0.03$0.01 (best)$0.25
Blended (3:1)$0.237$0.20 (best)$3.00
Long-context rateSame rateOver 272K: $0.20 / $0.75Same rate
Price sourceOfficial Z.AI APIOfficial OpenAI APIOfficial Alibaba API
Limits
Context window1,000,000 tokens1,050,000 tokens (best)1,000,000 tokens
Max output131,072 tokens (best)128,000 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesYesYes
AudioNoNoNo
VideoYesNoYes
ReasoningYeslow · high · maxYeslow · medium · high · xhigh · maxYeslow · medium · xhigh
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsOpenProprietaryProprietary
API model IDglm-5.3-flashgpt-6-lunaqwen3.8-max
API providers65 (best)2425
ReleasedAug 26, 2026Sep 22, 2026Aug 3, 2026
Knowledge cutoff—May 18, 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-6 Luna$2.00
  • Qwen3.8 Max$32.00
04 — Questions

Which should you choose?

Which is better: GLM-5.3-Flash, GPT-6 Luna or Qwen3.8 Max?

GPT-6 Luna is the better all-round choice, scoring 84/100 against GLM-5.3-Flash (79) and Qwen3.8 Max (71). It leads on price. 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 Qwen3.8 Max?

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); Qwen3.8 Max costs $2.00 input / $6.00 output per million tokens (official Alibaba 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 $3.00 for Qwen3.8 Max (15× 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): GPT-6 Luna 89.4%, Qwen3.8 Max 89.0% and GLM-5.3-Flash 79.9%. On individual benchmarks: GPQA Diamond — Qwen3.8 Max 92.7%, GPT-6 Luna 90.5%, GLM-5.3-Flash 90.2%; FrontierMath Tiers 1–3 — GPT-6 Luna 79.0%, Qwen3.8 Max 74.7%, GLM-5.3-Flash 55.8%; OTIS Mock AIME 2024–2025 — Qwen3.8 Max 99.4%, 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 Qwen3.8 Max 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 1,000,000 for Qwen3.8 Max. Maximum output per response: GLM-5.3-Flash up to 131,072, GPT-6 Luna up to 128,000, Qwen3.8 Max up to 131,072 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; Qwen3.8 Max accepts text, images, PDFs and video. 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 Qwen3.8 Max is proprietary.

Which is newer?

GPT-6 Luna is the newest, released Sep 22, 2026. GLM-5.3-Flash came out Aug 26, 2026; Qwen3.8 Max came out Aug 3, 2026. Knowledge cutoff: 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.