ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Qwen3.8 Max vs GPT-6.1 Sol

GPT-6.1 Sol comes out ahead, 69 to 65 on our weighted score, though Qwen3.8 Max is 25% cheaper per token.

  1. 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
  2. Our pick

    OpenAI

    GPT-6.1 Sol

    Released Sep 29, 2026

    69/100
    • ECI—
    • Price$2.00 / $10.00
    • Context1.05M
    Full specs Remove GPT-6.1 Sol

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GPT-6.1 Sol is our pick

GPT-6.1 Sol is the better all-round choice, scoring 69/100 against Qwen3.8 Max (65). It leads on capability. Qwen3.8 Max wins on price and 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-6.1 Sol has no Capabilities Index score yet.

  • CapabilityGPT-6.1 SolShared benchmarks: GPT-6.1 Sol 90.7% · Qwen3.8 Max 78.2%
  • Lowest priceQwen3.8 MaxQwen3.8 Max $3.00 · GPT-6.1 Sol $4.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-6.1 SolGPT-6.1 Sol 1,050,000 · Qwen3.8 Max 1,000,000 tokens
  • Widest inputsQwen3.8 MaxQwen3.8 Max: Text, Images, PDFs, Video · GPT-6.1 Sol: Text, Images, PDFs
  • Self-hostingNo open weightsBoth are available only through APIs
How the score is built
MeasureWeightQwen3.8 MaxGPT-6.1 Sol
CapabilityShared benchmarks50%7891
Price25%2721
Inputs & features15%9080
Context window10%6061
Overall100%65/10069/100
02 — Side by side

Every spec in one table

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

Qwen3.8 Max vs GPT-6.1 Sol specifications side by side
SpecificationQwen3.8 MaxAlibaba (Qwen)GPT-6.1 SolOpenAI
Capability
Capabilities Index (ECI)156.6—
ECI rank#20 of 148—
GPQA DiamondGraduate-level science questions92.7%95.4% (best)
FrontierMath Tiers 1–3Research-level mathematics74.7%93.7% (best)
OTIS Mock AIME 2024–2025Competition mathematics99.4%100% (best)
SimpleQA VerifiedShort factual questions45.8%73.9% (best)
Price per million tokens
Input$2.00$2.00
Output$6.00 (best)$10.00
Cached input$0.25$0.10 (best)
Blended (3:1)$3.00 (best)$4.00
Long-context rateSame rateOver 272K: $4.00 / $15.00
Price sourceOfficial Alibaba 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 · medium · xhighYeslow · medium · high · xhigh · max
Tool callingYesYes
Structured outputYesYes
Availability
WeightsProprietaryProprietary
API model IDqwen3.8-maxgpt-6.1-sol
API providers25 (best)21
ReleasedAug 3, 2026Sep 29, 2026
Knowledge cutoff—Apr 30, 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.

  • Qwen3.8 Max$32.00
  • GPT-6.1 Sol$40.00
04 — Questions

Which should you choose?

Which is better: Qwen3.8 Max or GPT-6.1 Sol?

GPT-6.1 Sol is the better all-round choice, scoring 69/100 against Qwen3.8 Max (65). It leads on capability. Qwen3.8 Max wins on price and 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-6.1 Sol has no Capabilities Index score yet.

Which is cheaper, Qwen3.8 Max or GPT-6.1 Sol?

Qwen3.8 Max is cheaper at $2.00 input / $6.00 output per million tokens (official Alibaba API price). GPT-6.1 Sol costs $2.00 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Qwen3.8 Max versus $4.00 for GPT-6.1 Sol (1.3× 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): GPT-6.1 Sol 90.7% and Qwen3.8 Max 78.2%. On individual benchmarks: GPQA Diamond — GPT-6.1 Sol 95.4%, Qwen3.8 Max 92.7%; FrontierMath Tiers 1–3 — GPT-6.1 Sol 93.7%, Qwen3.8 Max 74.7%; OTIS Mock AIME 2024–2025 — GPT-6.1 Sol 100%, Qwen3.8 Max 99.4%; SimpleQA Verified — GPT-6.1 Sol 73.9%, Qwen3.8 Max 45.8%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.8 Max and GPT-6.1 Sol yet, so there is no like-for-like coding score. On overall capability, GPT-6.1 Sol 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-6.1 Sol has the largest context window at 1,050,000 tokens, against 1,000,000 for Qwen3.8 Max. Maximum output per response: Qwen3.8 Max up to 131,072, GPT-6.1 Sol up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Qwen3.8 Max accepts text, images, PDFs and video; GPT-6.1 Sol accepts text, images and PDFs. Qwen3.8 Max handles the widest range of inputs.

Are any of these open source?

No. Qwen3.8 Max and GPT-6.1 Sol are proprietary and only available through APIs and apps.

Which is newer?

GPT-6.1 Sol is the newest, released Sep 29, 2026. Qwen3.8 Max came out Aug 3, 2026. Knowledge cutoff: GPT-6.1 Sol Apr 30, 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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