LLMs & Assistants

Grok 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

Too close to call on score alone — Grok sits at 82.7 and Kimi at 84.0. A gap that size is inside the noise of any honest scoring model, so pick on fit rather than rank.

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

Grok

xAI

82.7

Excellent

Real-time assistant wired directly into X, with a candid personality.

From
Free / $30 per month (SuperGrok)
Pricing
Freemium
Maturity
Emerging
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

Level

Grok89
Kimi88

Value for Money

Kimi by 8

Grok85
Kimi93

Security & Compliance

Grok by 6

Grok74
Kimi68

Integrations & Ecosystem

Kimi by 6

Grok74
Kimi80

Maturity & Reliability

Kimi by 6

Grok72
Kimi78

Momentum

Level

Grok92
Kimi91

Which one, and when

Pick Grok if

  • compliance and data control decide it — it leads Security & Compliance by 6 points.
  • Real-time social research
  • Teams already living on X
  • Cost-efficient agentic coding

The catch

  • Enterprise security and compliance story is younger than rivals
  • Personality tuning has drawn scrutiny over output controls
Full Grok profile →

Pick Kimi if

  • cost per unit of output is the binding constraint — it leads Value for Money by 8 points.
  • it has to fit the stack you already run — it leads Integrations & Ecosystem by 6 points.
  • it has to hold up in production from day one — it leads Maturity & Reliability by 6 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

Grok

  • Live access to X gives it a real-time edge on news and sentiment
  • Fast-improving reasoning and coding across recent model releases
  • Generous context and image understanding on paid tiers

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.