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Comparison · 3 models · Updated Oct 4, 2026

Qwen3.8 Max Preview vs Qwen3.8 27B vs Kimi K2.7 Code Highspeed

Qwen3.8 27B comes out ahead, 57 to 47 and 44 on our weighted score, and it is the cheaper option too.

  1. Alibaba (Qwen)

    Qwen3.8 Max Preview

    Released Jul 19, 2026

    47/100
    • ECI—
    • Price$2.00 / $6.00
    • Context1M
  2. Our pick

    Alibaba (Qwen)

    Qwen3.8 27B

    Released Aug 14, 2026

    57/100
    • ECI149.4
    • Price$0.40 / $2.50
    • Context262K
  3. Moonshot AI

    Kimi K2.7 Code Highspeed

    Released Jun 12, 2026

    44/100
    • ECI—
    • Price$1.90 / $8.00
    • Context262K
01 — Verdict

Qwen3.8 27B is our pick

Qwen3.8 27B is the better all-round choice, scoring 57/100 against Qwen3.8 Max Preview (47) and Kimi K2.7 Code Highspeed (44). It leads on price. Qwen3.8 Max Preview wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceQwen3.8 27BQwen3.8 27B $0.925 · Qwen3.8 Max Preview $3.00 · Kimi K2.7 Code Highspeed $3.42 per 1M tokens (3:1 blend)
  • Longest contextQwen3.8 Max PreviewQwen3.8 Max Preview 1,000,000 · Qwen3.8 27B 262,144 · Kimi K2.7 Code Highspeed 262,144 tokens
  • Widest inputsSame inputsQwen3.8 Max Preview: Text, Images, Video · Qwen3.8 27B: Text, Images, Video · Kimi K2.7 Code Highspeed: Text, Images, Video
  • Self-hostingQwen3.8 27B and Kimi K2.7 Code HighspeedPublishes downloadable weights
How the score is built
MeasureWeightQwen3.8 Max PreviewQwen3.8 27BKimi K2.7 Code Highspeed
Price50%275125
Inputs & features30%708080
Context window20%603737
Overall100%47/10057/10044/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Qwen3.8 Max Preview vs Qwen3.8 27B vs Kimi K2.7 Code Highspeed specifications side by side
SpecificationQwen3.8 Max PreviewAlibaba (Qwen)Qwen3.8 27BAlibaba (Qwen)Kimi K2.7 Code HighspeedMoonshot AI
Capability
Capabilities Index (ECI)—149.4—
ECI rank—#53 of 148—
Price per million tokens
Input$2.00$0.40 (best)$1.90
Output$6.00$2.50 (best)$8.00
Cached input———
Blended (3:1)$3.00$0.925 (best)$3.42
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 6 providersMedian of 39 providersMedian of 11 providers
Limits
Context window1,000,000 tokens (best)262,144 tokens262,144 tokens
Max output131,072 tokens32,768 tokens262,144 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoYesYesYes
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsProprietaryOpenOpen
API model ID———
API providers641 (best)11
ReleasedJul 19, 2026Aug 14, 2026Jun 12, 2026
Knowledge cutoff——Jan 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.

  • Qwen3.8 Max Preview$32.00
  • Qwen3.8 27B$9.00
  • Kimi K2.7 Code Highspeed$35.00
04 — Questions

Which should you choose?

Which is better: Qwen3.8 Max Preview, Qwen3.8 27B or Kimi K2.7 Code Highspeed?

Qwen3.8 27B is the better all-round choice, scoring 57/100 against Qwen3.8 Max Preview (47) and Kimi K2.7 Code Highspeed (44). It leads on price. Qwen3.8 Max Preview wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Qwen3.8 Max Preview, Qwen3.8 27B or Kimi K2.7 Code Highspeed?

Qwen3.8 27B is cheaper at $0.40 input / $2.50 output per million tokens (median across 39 API providers). Qwen3.8 Max Preview costs $2.00 input / $6.00 output per million tokens (median across 6 API providers); Kimi K2.7 Code Highspeed costs $1.90 input / $8.00 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.925 per million tokens for Qwen3.8 27B versus $3.00 for Qwen3.8 Max Preview (3.2× as much) and $3.42 for Kimi K2.7 Code Highspeed (3.7× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Qwen3.8 Max Preview has not been scored yet, Qwen3.8 27B has an ECI of 149.4 and Kimi K2.7 Code Highspeed has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.8 Max Preview, Qwen3.8 27B and Kimi K2.7 Code Highspeed yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen3.8 Max Preview has the largest context window at 1,000,000 tokens, against 262,144 for Qwen3.8 27B and 262,144 for Kimi K2.7 Code Highspeed. Maximum output per response: Qwen3.8 Max Preview up to 131,072, Qwen3.8 27B up to 32,768, Kimi K2.7 Code Highspeed up to 262,144 tokens.

Which can read images, PDFs, audio or video?

Qwen3.8 Max Preview accepts text, images and video; Qwen3.8 27B accepts text, images and video; Kimi K2.7 Code Highspeed accepts text, images and video. They handle the same number of input types.

Are any of these open source?

Qwen3.8 27B and Kimi K2.7 Code Highspeed publishes its weights and can be self-hosted; Qwen3.8 Max Preview is proprietary.

Which is newer?

Qwen3.8 27B is the newest, released Aug 14, 2026. Qwen3.8 Max Preview came out Jul 19, 2026; Kimi K2.7 Code Highspeed came out Jun 12, 2026. Knowledge cutoff: Kimi K2.7 Code Highspeed Jan 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.