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Comparison · 2 models · Updated Oct 4, 2026

Kimi K2 Thinking vs Qwen3.5 397B-A17B

Qwen3.5 397B-A17B comes out ahead, 65 to 58 on our weighted score, though Kimi K2 Thinking is 20% cheaper per token.

  1. Moonshot AI

    Kimi K2 Thinking

    Released Nov 6, 2025

    58/100
    • ECI146.0
    • Price$0.60 / $2.50
    • Context262K
    Full specs Remove Kimi K2 Thinking
  2. Our pick

    Alibaba (Qwen)

    Qwen3.5 397B-A17B

    Released Feb 15, 2026

    65/100
    • ECI146.7
    • Price$0.60 / $3.60
    • Context262K
    Full specs Remove Qwen3.5 397B-A17B

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3.5 397B-A17B is our pick

Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against Kimi K2 Thinking (58). It leads on inputs & features. Kimi K2 Thinking wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 397B-A17BCapabilities Index (ECI): Qwen3.5 397B-A17B 146.7 · Kimi K2 Thinking 146.0
  • Lowest priceKimi K2 ThinkingKimi K2 Thinking $1.07 · Qwen3.5 397B-A17B $1.35 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameKimi K2 Thinking 262,144 · Qwen3.5 397B-A17B 262,144 tokens
  • Widest inputsQwen3.5 397B-A17BKimi K2 Thinking: Text · Qwen3.5 397B-A17B: Text, Images, Audio, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightKimi K2 ThinkingQwen3.5 397B-A17B
CapabilityCapabilities Index (ECI)50%7374
Price25%4844
Inputs & features15%3590
Context window10%3737
Overall100%58/10065/100
02 — Side by side

Every spec in one table

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

Kimi K2 Thinking vs Qwen3.5 397B-A17B specifications side by side
SpecificationKimi K2 ThinkingMoonshot AIQwen3.5 397B-A17BAlibaba (Qwen)
Capability
Capabilities Index (ECI)146.0146.7 (best)
ECI rank#72 of 148#67 of 148 (best)
GPQA DiamondGraduate-level science questions84.2%86.4% (best)
FrontierMath Tiers 1–3Research-level mathematics—31.2%
OTIS Mock AIME 2024–2025Competition mathematics83.1%88.9% (best)
Price per million tokens
Input$0.60$0.60
Output$2.50 (best)$3.60
Cached input——
Blended (3:1)$1.07 (best)$1.35
Long-context rateSame rateSame rate
Price sourceMedian of 10 providersOfficial Alibaba API
Limits
Context window262,144 tokens262,144 tokens
Max output262,144 tokens (best)65,536 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoYes
VideoNoYes
ReasoningYesYes
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenOpen
API model ID—qwen3.5-397b-a17b
API providers1023 (best)
ReleasedNov 6, 2025Feb 15, 2026
Knowledge cutoffAug 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.

  • Kimi K2 Thinking$11.00
  • Qwen3.5 397B-A17B$13.20
04 — Questions

Which should you choose?

Which is better: Kimi K2 Thinking or Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against Kimi K2 Thinking (58). It leads on inputs & features. Kimi K2 Thinking wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Kimi K2 Thinking or Qwen3.5 397B-A17B?

Kimi K2 Thinking is cheaper at $0.60 input / $2.50 output per million tokens (median across 10 API providers). Qwen3.5 397B-A17B costs $0.60 input / $3.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.07 per million tokens for Kimi K2 Thinking versus $1.35 for Qwen3.5 397B-A17B (1.3× as much).

Which scores higher on benchmarks?

Qwen3.5 397B-A17B scores higher on the Capabilities Index (ECI): Qwen3.5 397B-A17B 146.7 (#67 of 148) and Kimi K2 Thinking 146.0 (#72 of 148). The confidence ranges of the top two overlap (144.8–148.2 vs 143.4–147.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 397B-A17B 86.4%, Kimi K2 Thinking 84.2%; OTIS Mock AIME 2024–2025 — Qwen3.5 397B-A17B 88.9%, Kimi K2 Thinking 83.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2 Thinking and Qwen3.5 397B-A17B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 397B-A17B 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?

Kimi K2 Thinking and Qwen3.5 397B-A17B share the same 262,144-token context window. Maximum output per response: Kimi K2 Thinking up to 262,144, Qwen3.5 397B-A17B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Kimi K2 Thinking accepts text; Qwen3.5 397B-A17B accepts text, images, audio and video. Qwen3.5 397B-A17B 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 397B-A17B is the newest, released Feb 15, 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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