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Comparison · 2 models · Updated Oct 4, 2026

Gemini 2.5 Pro vs Kimi K2.7 Code

Too close to call on our weighted score (Kimi K2.7 Code 64, Gemini 2.5 Pro 63). The right pick depends on what you value most.

  1. Google

    Gemini 2.5 Pro

    Released Jun 17, 2025

    63/100
    • ECI145.3
    • Price$1.25 / $10.00
    • Context1.05M
    Full specs Remove Gemini 2.5 Pro

  2. Moonshot AI

    Kimi K2.7 Code

    Released Jun 12, 2026

    64/100
    • ECI150.0
    • Price$0.95 / $4.00
    • Context262K
    Full specs Remove Kimi K2.7 Code

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Kimi K2.7 Code 64/100, Gemini 2.5 Pro 63/100), so choose by what matters most for your work: Kimi K2.7 Code for raw capability and Gemini 2.5 Pro for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityKimi K2.7 CodeCapabilities Index (ECI): Kimi K2.7 Code 150.0 · Gemini 2.5 Pro 145.3
  • Lowest priceKimi K2.7 CodeKimi K2.7 Code $1.71 · Gemini 2.5 Pro $3.44 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · Kimi K2.7 Code 262,144 tokens
  • Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · Kimi K2.7 Code: Text, Images, Video
  • Self-hostingKimi K2.7 CodePublishes downloadable weights
How the score is built
MeasureWeightGemini 2.5 ProKimi K2.7 Code
CapabilityCapabilities Index (ECI)50%7278
Price25%2439
Inputs & features15%10080
Context window10%6137
Overall100%63/10064/100
02 — Side by side

Every spec in one table

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

Gemini 2.5 Pro vs Kimi K2.7 Code specifications side by side
SpecificationGemini 2.5 ProGoogleKimi K2.7 CodeMoonshot AI
Capability
Capabilities Index (ECI)145.3150.0 (best)
ECI rank#78 of 148#49 of 148 (best)
GPQA DiamondGraduate-level science questions85.3%87.9% (best)
FrontierMath Tiers 1–3Research-level mathematics24.6%54.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics84.7%95.6% (best)
SWE-bench VerifiedFixing real GitHub issues57.6%—
SimpleQA VerifiedShort factual questions—36.5%
Price per million tokens
Input$1.25$0.95 (best)
Output$10.00$4.00 (best)
Cached input$0.125 (best)$0.19
Blended (3:1)$3.44$1.71 (best)
Long-context rateOver 200K: $2.50 / $15.00Same rate
Price sourceOfficial Google APIOfficial Moonshot AI API
Limits
Context window1,048,576 tokens (best)262,144 tokens
Max output65,536 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsYesNo
AudioYesNo
VideoYesYes
ReasoningYesYes
Tool callingYesYes
Structured outputYesYes
Availability
WeightsProprietaryOpen
API model IDgemini-2.5-prokimi-k2.7-code
API providers2251 (best)
ReleasedJun 17, 2025Jun 12, 2026
Knowledge cutoffJan 2025Jan 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.

  • Gemini 2.5 Pro$32.50
  • Kimi K2.7 Code$17.50
04 — Questions

Which should you choose?

Which is better: Gemini 2.5 Pro or Kimi K2.7 Code?

It is close. Our weighted score puts them within 1 points (Kimi K2.7 Code 64/100, Gemini 2.5 Pro 63/100), so choose by what matters most for your work: Kimi K2.7 Code for raw capability and Gemini 2.5 Pro for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 2.5 Pro or Kimi K2.7 Code?

Kimi K2.7 Code is cheaper at $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). Gemini 2.5 Pro costs $1.25 input / $10.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $1.71 per million tokens for Kimi K2.7 Code versus $3.44 for Gemini 2.5 Pro (2× as much).

Which scores higher on benchmarks?

Kimi K2.7 Code scores higher on the Capabilities Index (ECI): Kimi K2.7 Code 150.0 (#49 of 148) and Gemini 2.5 Pro 145.3 (#78 of 148). Their confidence ranges do not overlap (148.1–151.8 vs 143.6–146.9), so the gap is a real one. On individual benchmarks: GPQA Diamond — Kimi K2.7 Code 87.9%, Gemini 2.5 Pro 85.3%; FrontierMath Tiers 1–3 — Kimi K2.7 Code 54.0%, Gemini 2.5 Pro 24.6%; OTIS Mock AIME 2024–2025 — Kimi K2.7 Code 95.6%, Gemini 2.5 Pro 84.7%.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2.7 Code yet, so there is no like-for-like coding score. On overall capability, Kimi K2.7 Code 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?

Gemini 2.5 Pro has the largest context window at 1,048,576 tokens, against 262,144 for Kimi K2.7 Code. Maximum output per response: Gemini 2.5 Pro up to 65,536, Kimi K2.7 Code up to 262,144 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Pro accepts text, images, PDFs, audio and video; Kimi K2.7 Code accepts text, images and video. Gemini 2.5 Pro handles the widest range of inputs.

Are any of these open source?

Kimi K2.7 Code publishes its weights and can be self-hosted; Gemini 2.5 Pro is proprietary.

Which is newer?

Kimi K2.7 Code is the newest, released Jun 12, 2026. Gemini 2.5 Pro came out Jun 17, 2025. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, Kimi K2.7 Code 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.

05 — Keep comparing

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