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Comparison · 2 models · Updated Oct 4, 2026

Qwen3.5 397B-A17B vs Kimi K2 Thinking

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

  1. 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

  2. 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

  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 sameQwen3.5 397B-A17B 262,144 · Kimi K2 Thinking 262,144 tokens
  • Widest inputsQwen3.5 397B-A17BQwen3.5 397B-A17B: 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 397B-A17BKimi K2 Thinking
CapabilityCapabilities Index (ECI)50%7473
Price25%4448
Inputs & features15%9035
Context window10%3737
Overall100%65/10058/100
02 — Side by side

Every spec in one table

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

Qwen3.5 397B-A17B vs Kimi K2 Thinking specifications side by side
SpecificationQwen3.5 397B-A17BAlibaba (Qwen)Kimi K2 ThinkingMoonshot AI
Capability
Capabilities Index (ECI)146.7 (best)146.0
ECI rank#67 of 148 (best)#72 of 148
GPQA DiamondGraduate-level science questions86.4% (best)84.2%
FrontierMath Tiers 1–3Research-level mathematics31.2%—
OTIS Mock AIME 2024–2025Competition mathematics88.9% (best)83.1%
Price per million tokens
Input$0.60$0.60
Output$3.60$2.50 (best)
Cached input——
Blended (3:1)$1.35$1.07 (best)
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 IDqwen3.5-397b-a17b—
API providers23 (best)10
ReleasedFeb 15, 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 397B-A17B$13.20
  • Kimi K2 Thinking$11.00
04 — Questions

Which should you choose?

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

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

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 Qwen3.5 397B-A17B and Kimi K2 Thinking 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?

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

Which can read images, PDFs, audio or video?

Qwen3.5 397B-A17B accepts text, images, audio and video; Kimi K2 Thinking accepts text. 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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