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Comparison · 2 models · Updated Oct 4, 2026

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

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. Alibaba (Qwen)

    Qwen3.5 397B-A17B

    Released Feb 15, 2026

    65/100
    • ECI146.7
    • Price$0.60 / $3.60
    • Context262K
  2. Moonshot AI

    Kimi K2.5

    Released Jan 27, 2026

    65/100
    • ECI148.0
    • Price$0.60 / $3.00
    • 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 sameQwen3.5 397B-A17B 262,144 · Kimi K2.5 262,144 tokens
  • Widest inputsQwen3.5 397B-A17BQwen3.5 397B-A17B: Text, Images, Audio, Video · Kimi K2.5: Text, Images, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3.5 397B-A17BKimi K2.5
CapabilityCapabilities Index (ECI)50%7476
Price25%4446
Inputs & features15%9080
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.

Qwen3.5 397B-A17B vs Kimi K2.5 specifications side by side
SpecificationQwen3.5 397B-A17BAlibaba (Qwen)Kimi K2.5Moonshot AI
Capability
Capabilities Index (ECI)146.7148.0 (best)
ECI rank#67 of 148#58 of 148 (best)
GPQA DiamondGraduate-level science questions86.4%87.6% (best)
FrontierMath Tiers 1–3Research-level mathematics31.2%—
OTIS Mock AIME 2024–2025Competition mathematics88.9%92.2% (best)
SWE-bench VerifiedFixing real GitHub issues—73.8%
SimpleQA VerifiedShort factual questions—34.3%
Price per million tokens
Input$0.60$0.60
Output$3.60$3.00 (best)
Cached input——
Blended (3:1)$1.35$1.20 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 21 providers
Limits
Context window262,144 tokens262,144 tokens
Max output65,536 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioYesNo
VideoYesYes
ReasoningYesYes
Tool callingYesYes
Structured outputYesYes
Availability
WeightsOpenOpen
API model IDqwen3.5-397b-a17b—
API providers23 (best)21
ReleasedFeb 15, 2026Jan 27, 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.

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

Which should you choose?

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

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

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?

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

Which can read images, PDFs, audio or video?

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