ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GPT-6 Luna vs Qwen3.8 Max

GPT-6 Luna comes out ahead, 78 to 65 on our weighted score, and it is the cheaper option too.

  1. Our pick

    OpenAI

    GPT-6 Luna

    Released Sep 22, 2026

    78/100
    • ECI—
    • Price$0.10 / $0.50
    • Context1.05M
    Full specs Remove GPT-6 Luna

  2. Alibaba (Qwen)

    Qwen3.8 Max

    Released Aug 3, 2026

    65/100
    • ECI156.6
    • Price$2.00 / $6.00
    • Context1M
    Full specs Remove Qwen3.8 Max

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GPT-6 Luna is our pick

GPT-6 Luna is the better all-round choice, scoring 78/100 against Qwen3.8 Max (65). It leads on price. Qwen3.8 Max wins on inputs & features. 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, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6 Luna has no Capabilities Index score yet.

  • CapabilityQwen3.8 MaxShared benchmarks: Qwen3.8 Max 78.2% · GPT-6 Luna 77.4%
  • Lowest priceGPT-6 LunaGPT-6 Luna $0.20 · Qwen3.8 Max $3.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-6 LunaGPT-6 Luna 1,050,000 · Qwen3.8 Max 1,000,000 tokens
  • Widest inputsQwen3.8 MaxGPT-6 Luna: Text, Images, PDFs · Qwen3.8 Max: Text, Images, PDFs, Video
  • Self-hostingNo open weightsBoth are available only through APIs
How the score is built
MeasureWeightGPT-6 LunaQwen3.8 Max
CapabilityShared benchmarks50%7778
Price25%8327
Inputs & features15%8090
Context window10%6160
Overall100%78/10065/100
02 — Side by side

Every spec in one table

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

GPT-6 Luna vs Qwen3.8 Max specifications side by side
SpecificationGPT-6 LunaOpenAIQwen3.8 MaxAlibaba (Qwen)
Capability
Capabilities Index (ECI)—156.6
ECI rank—#20 of 148
GPQA DiamondGraduate-level science questions90.5%92.7% (best)
FrontierMath Tiers 1–3Research-level mathematics79.0% (best)74.7%
OTIS Mock AIME 2024–2025Competition mathematics98.9%99.4% (best)
SimpleQA VerifiedShort factual questions41.4%45.8% (best)
Price per million tokens
Input$0.10 (best)$2.00
Output$0.50 (best)$6.00
Cached input$0.01 (best)$0.25
Blended (3:1)$0.20 (best)$3.00
Long-context rateOver 272K: $0.20 / $0.75Same rate
Price sourceOfficial OpenAI APIOfficial Alibaba API
Limits
Context window1,050,000 tokens (best)1,000,000 tokens
Max output128,000 tokens131,072 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsYesYes
AudioNoNo
VideoNoYes
ReasoningYeslow · medium · high · xhigh · maxYeslow · medium · xhigh
Tool callingYesYes
Structured outputYesYes
Availability
WeightsProprietaryProprietary
API model IDgpt-6-lunaqwen3.8-max
API providers2425 (best)
ReleasedSep 22, 2026Aug 3, 2026
Knowledge cutoffMay 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.

  • GPT-6 Luna$2.00
  • Qwen3.8 Max$32.00
04 — Questions

Which should you choose?

Which is better: GPT-6 Luna or Qwen3.8 Max?

GPT-6 Luna is the better all-round choice, scoring 78/100 against Qwen3.8 Max (65). It leads on price. Qwen3.8 Max wins on inputs & features. 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, OTIS Mock AIME 2024–2025 and SimpleQA Verified), because GPT-6 Luna has no Capabilities Index score yet.

Which is cheaper, 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). 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 $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, OTIS Mock AIME 2024–2025 and SimpleQA Verified): Qwen3.8 Max 78.2% and GPT-6 Luna 77.4%. On individual benchmarks: GPQA Diamond — Qwen3.8 Max 92.7%, GPT-6 Luna 90.5%; FrontierMath Tiers 1–3 — GPT-6 Luna 79.0%, Qwen3.8 Max 74.7%; OTIS Mock AIME 2024–2025 — Qwen3.8 Max 99.4%, GPT-6 Luna 98.9%; SimpleQA Verified — Qwen3.8 Max 45.8%, GPT-6 Luna 41.4%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-6 Luna and Qwen3.8 Max yet, so there is no like-for-like coding score. On overall capability, Qwen3.8 Max 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-6 Luna has the largest context window at 1,050,000 tokens, against 1,000,000 for Qwen3.8 Max. Maximum output per response: GPT-6 Luna up to 128,000, Qwen3.8 Max up to 131,072 tokens.

Which can read images, PDFs, audio or video?

GPT-6 Luna accepts text, images and PDFs; Qwen3.8 Max accepts text, images, PDFs and video. Qwen3.8 Max handles the widest range of inputs.

Are any of these open source?

No. GPT-6 Luna and Qwen3.8 Max are proprietary and only available through APIs and apps.

Which is newer?

GPT-6 Luna is the newest, released Sep 22, 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.

05 — Keep comparing

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