ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Qwen3.5 27B vs Kimi K2 Thinking

Qwen3.5 27B comes out ahead, 61 to 42 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen3.5 27B

    Released Feb 23, 2026

    61/100
    • ECI—
    • Price$0.30 / $2.40
    • Context262K
    Full specs Remove Qwen3.5 27B

  2. Moonshot AI

    Kimi K2 Thinking

    Released Nov 6, 2025

    42/100
    • ECI146.0
    • Price$0.60 / $2.50
    • Context262K
    Full specs Remove Kimi K2 Thinking

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3.5 27B is our pick

Qwen3.5 27B is the better all-round choice, scoring 61/100 against Kimi K2 Thinking (42). It leads on price and inputs & features. 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 priceQwen3.5 27BQwen3.5 27B $0.825 · Kimi K2 Thinking $1.07 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameQwen3.5 27B 262,144 · Kimi K2 Thinking 262,144 tokens
  • Widest inputsQwen3.5 27BQwen3.5 27B: Text, Images, Audio, Video · Kimi K2 Thinking: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3.5 27BKimi K2 Thinking
Price50%5448
Inputs & features30%9035
Context window20%3737
Overall100%61/10042/100

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.

Qwen3.5 27B vs Kimi K2 Thinking specifications side by side
SpecificationQwen3.5 27BAlibaba (Qwen)Kimi K2 ThinkingMoonshot AI
Capability
Capabilities Index (ECI)—146.0
ECI rank—#72 of 148
GPQA DiamondGraduate-level science questions—84.2%
OTIS Mock AIME 2024–2025Competition mathematics—83.1%
Price per million tokens
Input$0.30 (best)$0.60
Output$2.40 (best)$2.50
Cached input——
Blended (3:1)$0.825 (best)$1.07
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 10 providers
Limits
Context window262,144 tokens262,144 tokens
Max output65,536 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioYesNo
VideoYesNo
ReasoningYesYes
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenOpen
API model IDqwen3.5-27b—
API providers16 (best)10
ReleasedFeb 23, 2026Nov 6, 2025
Knowledge cutoff—Aug 2024
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.

  • Qwen3.5 27B$7.80
  • Kimi K2 Thinking$11.00
04 — Questions

Which should you choose?

Which is better: Qwen3.5 27B or Kimi K2 Thinking?

Qwen3.5 27B is the better all-round choice, scoring 61/100 against Kimi K2 Thinking (42). It leads on price and inputs & features. 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, Qwen3.5 27B or Kimi K2 Thinking?

Qwen3.5 27B is cheaper at $0.30 input / $2.40 output per million tokens (official Alibaba API price). Kimi K2 Thinking costs $0.60 input / $2.50 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.825 per million tokens for Qwen3.5 27B versus $1.07 for Kimi K2 Thinking (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen3.5 27B has not been scored yet and Kimi K2 Thinking has an ECI of 146.0.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 27B and Kimi K2 Thinking yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Qwen3.5 27B and Kimi K2 Thinking share the same 262,144-token context window. Maximum output per response: Qwen3.5 27B up to 65,536, Kimi K2 Thinking up to 262,144 tokens.

Which can read images, PDFs, audio or video?

Qwen3.5 27B accepts text, images, audio and video; Kimi K2 Thinking accepts text. Qwen3.5 27B handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Qwen3.5 27B is the newest, released Feb 23, 2026. Kimi K2 Thinking came out Nov 6, 2025. Knowledge cutoff: Kimi K2 Thinking Aug 2024.

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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