LLMs & Assistants

ChatGPT vs DeepSeek.

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 83.6, a margin of 7.1 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 maturity & reliability, integrations & ecosystem and security & compliance; DeepSeek 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
DeepSeek

DeepSeek AI

83.6

Excellent

Open-weight frontier models at a fraction of the usual cost.

From
Free (open weights) / low-cost API
Pricing
Open Source
Maturity
Emerging
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
DeepSeek88

Value for Money

DeepSeek by 7

ChatGPT88
DeepSeek95

Security & Compliance

ChatGPT by 10

ChatGPT82
DeepSeek72

Integrations & Ecosystem

ChatGPT by 12

ChatGPT90
DeepSeek78

Maturity & Reliability

ChatGPT by 20

ChatGPT92
DeepSeek72

Momentum

ChatGPT by 5

ChatGPT93
DeepSeek88

Which one, and when

Pick ChatGPT if

  • it has to hold up in production from day one — it leads Maturity & Reliability by 20 points.
  • it has to fit the stack you already run — it leads Integrations & Ecosystem by 12 points.
  • compliance and data control decide it — it leads Security & Compliance 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 DeepSeek if

  • cost per unit of output is the binding constraint — it leads Value for Money by 7 points.
  • Cost-sensitive AI workloads
  • Self-hosted frontier reasoning
  • Teams fine-tuning open models

The catch

  • Hosted service raises data-residency questions for regulated buyers
  • Enterprise support and certifications lag Western labs
Full DeepSeek 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

DeepSeek

  • Frontier-class reasoning and coding at a small fraction of the cost
  • Open weights allow self-hosting, fine-tuning and full data control
  • API pricing undercuts most closed competitors substantially

Other comparisons in LLMs & Assistants

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