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Comparison · 3 models · Updated Oct 4, 2026

Inkling vs Qwen3.6 Max Preview vs Qwen3.8 27B

Qwen3.8 27B comes out ahead, 67 to 59 and 54 on our weighted score, and it is the cheaper option too.

  1. Thinking Machines

    Inkling

    Released Jul 15, 2026

    59/100
    • ECI148.6
    • Price$3.74 / $9.36
    • Context1.05M
  2. Alibaba (Qwen)

    Qwen3.6 Max Preview

    Released Apr 20, 2026

    54/100
    • ECI149.2
    • Price$1.30 / $7.80
    • Context262K
  3. Our pick

    Alibaba (Qwen)

    Qwen3.8 27B

    Released Aug 14, 2026

    67/100
    • ECI149.4
    • Price$0.40 / $2.50
    • Context262K
01 — Verdict

Qwen3.8 27B is our pick

Qwen3.8 27B is the better all-round choice, scoring 67/100 against Inkling (59) and Qwen3.6 Max Preview (54). It leads on price and inputs & features. Inkling wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.8 27BCapabilities Index (ECI): Qwen3.8 27B 149.4 · Qwen3.6 Max Preview 149.2 · Inkling 148.6
  • Lowest priceQwen3.8 27BQwen3.8 27B $0.925 · Qwen3.6 Max Preview $2.92 · Inkling $5.14 per 1M tokens (3:1 blend)
  • Longest contextInklingInkling 1,048,576 · Qwen3.6 Max Preview 262,144 · Qwen3.8 27B 262,144 tokens
  • Widest inputsInkling and Qwen3.8 27BInkling: Text, Images, Audio · Qwen3.6 Max Preview: Text · Qwen3.8 27B: Text, Images, Video
  • Self-hostingInkling and Qwen3.8 27BPublishes downloadable weights (Apache-2.0)
How the score is built
MeasureWeightInklingQwen3.6 Max PreviewQwen3.8 27B
CapabilityCapabilities Index (ECI)50%767777
Price25%162851
Inputs & features15%703580
Context window10%613737
Overall100%59/10054/10067/100
02 — Side by side

Every spec in one table

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

Inkling vs Qwen3.6 Max Preview vs Qwen3.8 27B specifications side by side
SpecificationInklingThinking MachinesQwen3.6 Max PreviewAlibaba (Qwen)Qwen3.8 27BAlibaba (Qwen)
Capability
Capabilities Index (ECI)148.6149.2149.4 (best)
ECI rank#57 of 148#54 of 148#53 of 148 (best)
GPQA DiamondGraduate-level science questions88.3% (best)87.4%—
FrontierMath Tiers 1–3Research-level mathematics33.3%——
OTIS Mock AIME 2024–2025Competition mathematics88.9%91.1% (best)—
SWE-bench VerifiedFixing real GitHub issues—76.7%—
SimpleQA VerifiedShort factual questions40.3%52.0% (best)—
Price per million tokens
Input$3.74$1.30$0.40 (best)
Output$9.36$7.80$2.50 (best)
Cached input$0.748$0.13 (best)—
Blended (3:1)$5.14$2.92$0.925 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Thinking Machines APIOfficial Alibaba APIMedian of 39 providers
Limits
Context window1,048,576 tokens (best)262,144 tokens262,144 tokens
Max output1,048,576 tokens (best)65,536 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoNo
AudioYesNoNo
VideoNoNoYes
ReasoningYeslow · medium · high · xhigh · maxYesYes
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenApache-2.0ProprietaryOpen
API model IDthinkingmachines/Inkling:peft:262144qwen3.6-max-preview—
API providers231041 (best)
ReleasedJul 15, 2026Apr 20, 2026Aug 14, 2026
Knowledge cutoff—Apr 2025—
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.

  • Inkling$56.12
  • Qwen3.6 Max Preview$28.60
  • Qwen3.8 27B$9.00
04 — Questions

Which should you choose?

Which is better: Inkling, Qwen3.6 Max Preview or Qwen3.8 27B?

Qwen3.8 27B is the better all-round choice, scoring 67/100 against Inkling (59) and Qwen3.6 Max Preview (54). It leads on price and inputs & features. Inkling wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Inkling, Qwen3.6 Max Preview or Qwen3.8 27B?

Qwen3.8 27B is cheaper at $0.40 input / $2.50 output per million tokens (median across 39 API providers). Qwen3.6 Max Preview costs $1.30 input / $7.80 output per million tokens (official Alibaba API price); Inkling costs $3.74 input / $9.36 output per million tokens (official Thinking Machines API price). At a typical mix of three input tokens to one output token, that is $0.925 per million tokens for Qwen3.8 27B versus $2.92 for Qwen3.6 Max Preview (3.2× as much) and $5.14 for Inkling (5.6× as much).

Which scores higher on benchmarks?

Qwen3.8 27B scores higher on the Capabilities Index (ECI): Qwen3.8 27B 149.4 (#53 of 148), Qwen3.6 Max Preview 149.2 (#54 of 148) and Inkling 148.6 (#57 of 148). The confidence ranges of the top two overlap (147.5–151.6 vs 147.6–152.0), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Inkling and Qwen3.8 27B yet, so there is no like-for-like coding score. On overall capability, Qwen3.8 27B 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?

Inkling has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.6 Max Preview and 262,144 for Qwen3.8 27B. Maximum output per response: Inkling up to 1,048,576, Qwen3.6 Max Preview up to 65,536, Qwen3.8 27B up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Inkling accepts text, images and audio; Qwen3.6 Max Preview accepts text; Qwen3.8 27B accepts text, images and video. Inkling handles the widest range of inputs.

Are any of these open source?

Inkling and Qwen3.8 27B publishes its weights (Apache-2.0) and can be self-hosted; Qwen3.6 Max Preview is proprietary.

Which is newer?

Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling came out Jul 15, 2026; Qwen3.6 Max Preview came out Apr 20, 2026. Knowledge cutoff: Qwen3.6 Max Preview Apr 2025.

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.