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Comparison · 2 models · Updated Oct 4, 2026

Kimi K2.5 vs Qwen3.5 397B-A17B

Too close to call on our weighted score (Qwen3.5 397B-A17B 65, Kimi K2.5 65). The right pick depends on what you value most.

  1. Moonshot AI

    Kimi K2.5

    Released Jan 27, 2026

    65/100
    • ECI148.0
    • Price$0.60 / $3.00
    • Context262K
  2. Alibaba (Qwen)

    Qwen3.5 397B-A17B

    Released Feb 15, 2026

    65/100
    • ECI146.7
    • Price$0.60 / $3.60
    • Context262K
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01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Qwen3.5 397B-A17B 65/100, Kimi K2.5 65/100), so choose by what matters most for your work: Kimi K2.5 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityKimi K2.5Capabilities Index (ECI): Kimi K2.5 148.0 · Qwen3.5 397B-A17B 146.7
  • Lowest priceKimi K2.5Kimi K2.5 $1.20 · Qwen3.5 397B-A17B $1.35 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameKimi K2.5 262,144 · Qwen3.5 397B-A17B 262,144 tokens
  • Widest inputsQwen3.5 397B-A17BKimi K2.5: Text, Images, Video · 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 K2.5Qwen3.5 397B-A17B
CapabilityCapabilities Index (ECI)50%7674
Price25%4644
Inputs & features15%8090
Context window10%3737
Overall100%65/10065/100
02 — Side by side

Every spec in one table

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

Kimi K2.5 vs Qwen3.5 397B-A17B specifications side by side
SpecificationKimi K2.5Moonshot AIQwen3.5 397B-A17BAlibaba (Qwen)
Capability
Capabilities Index (ECI)148.0 (best)146.7
ECI rank#58 of 148 (best)#67 of 148
GPQA DiamondGraduate-level science questions87.6% (best)86.4%
FrontierMath Tiers 1–3Research-level mathematics—31.2%
OTIS Mock AIME 2024–2025Competition mathematics92.2% (best)88.9%
SWE-bench VerifiedFixing real GitHub issues73.8%—
SimpleQA VerifiedShort factual questions34.3%—
Price per million tokens
Input$0.60$0.60
Output$3.00 (best)$3.60
Cached input——
Blended (3:1)$1.20 (best)$1.35
Long-context rateSame rateSame rate
Price sourceMedian of 21 providersOfficial Alibaba API
Limits
Context window262,144 tokens262,144 tokens
Max output262,144 tokens (best)65,536 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoYes
VideoYesYes
ReasoningYesYes
Tool callingYesYes
Structured outputYesYes
Availability
WeightsOpenOpen
API model ID—qwen3.5-397b-a17b
API providers2123 (best)
ReleasedJan 27, 2026Feb 15, 2026
Knowledge cutoffJan 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.

  • Kimi K2.5$12.00
  • Qwen3.5 397B-A17B$13.20
04 — Questions

Which should you choose?

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

It is close. Our weighted score puts them within a point (Qwen3.5 397B-A17B 65/100, Kimi K2.5 65/100), so choose by what matters most for your work: Kimi K2.5 for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

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

Kimi K2.5 is cheaper at $0.60 input / $3.00 output per million tokens (median across 21 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 $1.20 per million tokens for Kimi K2.5 versus $1.35 for Qwen3.5 397B-A17B (1.1× as much).

Which scores higher on benchmarks?

Kimi K2.5 scores higher on the Capabilities Index (ECI): Kimi K2.5 148.0 (#58 of 148) and Qwen3.5 397B-A17B 146.7 (#67 of 148). The confidence ranges of the top two overlap (146.5–149.3 vs 144.8–148.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Kimi K2.5 87.6%, Qwen3.5 397B-A17B 86.4%; OTIS Mock AIME 2024–2025 — Kimi K2.5 92.2%, Qwen3.5 397B-A17B 88.9%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 397B-A17B yet, so there is no like-for-like coding score. On overall capability, Kimi K2.5 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 K2.5 and Qwen3.5 397B-A17B share the same 262,144-token context window. Maximum output per response: Kimi K2.5 up to 262,144, Qwen3.5 397B-A17B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Kimi K2.5 accepts text, images and video; 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 K2.5 came out Jan 27, 2026. Knowledge cutoff: Kimi K2.5 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.