LLMs & Assistants

ChatGPT 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

ChatGPT scores higher — 90.7 against 84.0, a margin of 6.7 points. That is the overall answer, not the whole one: the pillar breakdown below is where the decision usually actually gets made.

ChatGPT leads on security & compliance, maturity & reliability and integrations & ecosystem; Kimi leads on value for money.

ChatGPT

OpenAI

90.7

Exceptional

The most widely adopted general-purpose AI assistant.

From
Free / $20 per month (Plus)
Pricing
Freemium
Maturity
Mature
Founded
2022
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

ChatGPT by 7

ChatGPT95
Kimi88

Value for Money

Kimi by 5

ChatGPT88
Kimi93

Security & Compliance

ChatGPT by 14

ChatGPT82
Kimi68

Integrations & Ecosystem

ChatGPT by 10

ChatGPT90
Kimi80

Maturity & Reliability

ChatGPT by 14

ChatGPT92
Kimi78

Momentum

Level

ChatGPT93
Kimi91

Which one, and when

Pick ChatGPT if

  • compliance and data control decide it — it leads Security & Compliance by 14 points.
  • it has to hold up in production from day one — it leads Maturity & Reliability by 14 points.
  • it has to fit the stack you already run — it leads Integrations & Ecosystem by 10 points.
  • General knowledge work
  • Prototyping AI use cases
  • Teams standardizing on one assistant

The catch

  • Data-training controls require explicit opt-out on consumer tiers
  • Rate limits on frontier models even for paid tiers at peak times
Full ChatGPT profile →

Pick Kimi if

  • cost per unit of output is the binding constraint — it leads Value for Money by 5 points.
  • 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

ChatGPT

  • Broadest feature set of any assistant: browsing, code execution, vision, voice and image generation in one product
  • Massive ecosystem of custom GPTs and third-party integrations
  • Fast release cadence keeps it at or near the state of the art

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.