LLMs & Assistants

Gemini vs Kimi.

Both sit in LLMs & Assistants, scored on the same six pillars from the same published methodology. Here is where they actually differ.

The short answer

Gemini scores higher — 90.4 against 84.0, a margin of 6.4 points. That is the overall answer, not the whole one: the pillar breakdown below is where the decision usually actually gets made.

Gemini leads on security & compliance, integrations & ecosystem and maturity & reliability.

Gemini

Google

90.4

Exceptional

Google's multimodal frontier models woven through Workspace and Android.

From
Free / $19.99 per month (AI Pro)
Pricing
Freemium
Maturity
Mature
Founded
2023
Kimi

Moonshot AI

84.0

Excellent

Open-weight frontier assistant with standout agentic coding at rock-bottom cost.

From
Free chat / from $0.60 per 1M tokens (API)
Pricing
Open Source
Maturity
Established
Founded
2023

Pillar by pillar

The same six pillars and fixed weights used for every tool on the site. A lead of fewer than 5 points is not called for either side — these are evidence-backed judgements, not measurements. Read the methodology.

Capability

Gemini by 5

Gemini93
Kimi88

Value for Money

Level

Gemini90
Kimi93

Security & Compliance

Gemini by 20

Gemini88
Kimi68

Integrations & Ecosystem

Gemini by 11

Gemini91
Kimi80

Maturity & Reliability

Gemini by 8

Gemini86
Kimi78

Momentum

Level

Gemini90
Kimi91

Which one, and when

Pick Gemini if

  • compliance and data control decide it — it leads Security & Compliance by 20 points.
  • it has to fit the stack you already run — it leads Integrations & Ecosystem by 11 points.
  • it has to hold up in production from day one — it leads Maturity & Reliability by 8 points.
  • Google Workspace organizations
  • Multimodal workloads
  • Cost-sensitive API usage at scale

The catch

  • Product surface changes frequently; naming and tiers can confuse
  • Best experience assumes commitment to the Google ecosystem
Full Gemini profile →

Pick Kimi if

  • Cost-sensitive frontier LLM workloads
  • Self-hosted agentic coding
  • Teams fine-tuning open models

The catch

  • China-based hosting raises data-residency and compliance questions for regulated buyers
  • Trails the very top on some pure-reasoning benchmarks (GPQA-Diamond, AIME) versus GPT-5.4
Full Kimi profile →

What each is good at

Gemini

  • Native multimodality including long-video understanding
  • 1M+ token context windows at competitive API prices
  • Ships inside Gmail, Docs, Sheets and Android at massive scale

Kimi

  • Frontier-class agentic coding — K2.7-Code leads Opus 4.8 on MCP-Mark Verified
  • Trillion-parameter MoE with open weights for self-hosting and fine-tuning
  • 256K context and API pricing that undercuts most closed competitors many times over

Other comparisons in LLMs & Assistants

Comparing something else? Build your own side-by-side across any tools in the catalog.