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AI Choice Engine

Model comparison

Gemini 2.5 Pro vs Kimi K2.6

Google against Moonshot AI, compared on context, price, and verified benchmark results.

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

Google

Gemini 2.5 Pro

Balanced

vs

Moonshot AI

Kimi K2.6

Balanced · Open weights

AI model capability comparison
SpecificationGemini 2.5 ProKimi K2.6
ProviderGoogleMoonshot AI
TierBalancedBalanced
Context windowWinner: 1.05M262K
Max output66KNot verifiedUnverified
Input / 1M tokens$1.25Winner: $0.95
Output / 1M tokens$10Winner: $4
WeightsClosedOpen
ParametersNot disclosedUnverified1T total / 32B active (MoE, 384 experts)
Reasoning levelslow, medium, highNot verifiedUnverified
Modalitiestext, image, video, audio, pdftext, image, video
LicenseNot disclosedUnverifiedModified MIT
API model idgemini-2.5-prokimi-k2.6
ReleasedJune 17, 2025April 20, 2026
Artificial Analysis Intelligence Index (2026-09-26)16.1Winner: 27

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

  • 2026-09-26
    Artificial Analysis

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.

Pricing tiers

Gemini 2.5 Pro: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed.

Kimi K2.6: $0.95/$4.00 per MTok on the Moonshot API; cached input $0.16. No documented hard output cap; evals ran 98,304-token generations.

BalancedRecord checked September 26, 2026

Gemini 2.5 Pro

Gemini 2.5 Pro is Google's previous-generation Pro with a 1.05M-token context and strong multimodal support.

Best for

  • Long documents
  • Multimodal input
  • Google Workspace integration

Watch out

Since 2026-09-18 Google limits Gemini API access to existing 2.5 users (new projects are pointed to 3.8 Flash or 3.5 Flash-Lite); the Gemini API deprecations page shows no shutdown date — check Vertex AI's lifecycle page separately.

BalancedOpen weightsRecord checked September 26, 2026

Kimi K2.6

Kimi K2.6 is Moonshot's open-weight volume workhorse — a 1T MoE with native image/video input at 256K context, the base Kimi K2.7-Code and K3 build on.

Best for

  • Open-weight volume work
  • Multimodal input on a budget
  • Self-hosting at mid size

Watch out

256K context is small next to K3's 1M; video input is experimental (official API only). No documented hard output cap.

When the cheaper one wins

Kimi K2.6 is cheaper on output at $4 per million tokens against $10 for Gemini 2.5 Pro — about 2.5×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

Run the model picker

Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 2/5 core specs verified on both sides — Not published for at least one side: max output, parameter count, reasoning levels.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 2 days ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? Gemini 2.5 Pro · Kimi K2.6

Common questions

Gemini 2.5 Pro vs Kimi K2.6

Answered from the verified figures on this page rather than general guidance.

Is Gemini 2.5 Pro or Kimi K2.6 cheaper for input?
Kimi K2.6 is cheaper at $0.95 per million input tokens, against $1.25 for Gemini 2.5 Pro — roughly 1.3× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 2.5 Pro has tiered pricing: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed. Kimi K2.6 has tiered pricing: $0.95/$4.00 per MTok on the Moonshot API; cached input $0.16. No documented hard output cap; evals ran 98,304-token generations.
Is Gemini 2.5 Pro or Kimi K2.6 cheaper for output?
Kimi K2.6 is cheaper at $4 per million output tokens, against $10 for Gemini 2.5 Pro — roughly 2.5× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 2.5 Pro has tiered pricing: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed. Kimi K2.6 has tiered pricing: $0.95/$4.00 per MTok on the Moonshot API; cached input $0.16. No documented hard output cap; evals ran 98,304-token generations.
Which has the larger context window, Gemini 2.5 Pro or Kimi K2.6?
Gemini 2.5 Pro accepts 1.05M tokens against 262K for Kimi K2.6. This only matters if you routinely send very long documents or large codebases.
Should I use Gemini 2.5 Pro or Kimi K2.6?
Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. Gemini 2.5 Pro suits long documents; Kimi K2.6 suits open-weight volume work.
Can I self-host Gemini 2.5 Pro or Kimi K2.6?
Kimi K2.6 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Gemini 2.5 Pro is a closed model whose supported access paths are controlled by its provider.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Input price: Kimi K2.6 costs $0.95 per 1M tokens versus $1.25 for Gemini 2.5 Pro — a 1.3x difference at the headline tier.
  • Context: Gemini 2.5 Pro takes 1.05M against 262K for Kimi K2.6 — only decisive if your prompts approach the smaller window.
  • Measured capability: Kimi K2.6 leads Artificial Analysis Intelligence Index 27 to 16.1 (measured 2026-09-26).
  • Deployment: Kimi K2.6 publishes weights you can self-host; the other is API-only.
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