LLMs & Assistants

DeepSeek vs Mistral AI.

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 — DeepSeek sits at 83.6 and Mistral AI at 83.4. A gap that size is inside the noise of any honest scoring model, so pick on fit rather than rank.

DeepSeek leads on value for money; Mistral AI leads on security & compliance and maturity & reliability.

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
Mistral AI

Mistral AI

83.4

Excellent

European frontier lab with strong open-weight models and Le Chat.

From
Free / €14.99 per month (Pro)
Pricing
Freemium
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

DeepSeek88
Mistral AI84

Value for Money

DeepSeek by 6

DeepSeek95
Mistral AI89

Security & Compliance

Mistral AI by 13

DeepSeek72
Mistral AI85

Integrations & Ecosystem

Level

DeepSeek78
Mistral AI78

Maturity & Reliability

Mistral AI by 6

DeepSeek72
Mistral AI78

Momentum

Level

DeepSeek88
Mistral AI84

Which one, and when

Pick DeepSeek if

  • cost per unit of output is the binding constraint — it leads Value for Money by 6 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 →

Pick Mistral AI if

  • compliance and data control decide it — it leads Security & Compliance by 13 points.
  • it has to hold up in production from day one — it leads Maturity & Reliability by 6 points.
  • EU data-sovereignty requirements
  • Self-hosted deployments
  • Cost-efficient API workloads

The catch

  • Frontier capability trails the top US labs on hardest tasks
  • Smaller assistant ecosystem and fewer consumer features
Full Mistral AI profile →

What each is good at

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

Mistral AI

  • Best-in-class open-weight models for self-hosting
  • EU jurisdiction simplifies GDPR and data-sovereignty compliance
  • Aggressive pricing across API tiers

Other comparisons in LLMs & Assistants

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