Mistral vs Google Gemini

Side-by-side — pricing, strengths, tradeoffs, and fit.

Mistral

European AI lab offering strong open-weight and commercial LLMs.

Google Gemini

Google’s multimodal LLM family with long context, via the Gemini API and Vertex AI.

At a glance

Open SourceFree TierEnterprise
◐ Growing·From $0.20/1M tokens (small)
Free TierEnterprise
◐ Growing·From $0.075/1M input tokens (Flash)

Overview

One-liner

European AI lab offering strong open-weight and commercial LLMs.

One-liner

Google’s multimodal LLM family with long context, via the Gemini API and Vertex AI.

Maturity

Growing

Maturity

Growing

Open source

✓ Yes

Open source

✕ No

Pricing

Free tier

✓ Available

Free tier / open weights for some models

Free tier

✓ Available

Free tier on Google AI Studio with rate limits

Starts at

$0.20/1M tokens (small)

Starts at

$0.075/1M input tokens (Flash)

Model

Usage-based

Model

Usage-based

Enterprise

✓ Available

Enterprise

✓ Available

Best for

✓ Best for

Cost-efficient or self-hosted LLMsOpen weights plus affordable API
EU data-residency needsEuropean provider

✓ Best for

Multimodal and long-context tasksMillion-token context and native media
Teams on Google CloudNative Vertex AI deployment

Not ideal for

✕ Not for

—

✕ Not for

—

Strengths

↑ Strengths

Strong open-weight models
Cost-efficient
European data-residency option

↑ Strengths

Very long context windows
Natively multimodal
Competitive pricing (Flash)

Weaknesses

↓ Weaknesses

Regional inference endpoints incur a 10% surcharge on API costs.

↓ Weaknesses

Free tier users' content is used to train and improve Google's products.
Grounding with Google Search is unavailable on the free tier.
Free tier access is limited to specific models.
Full Mistral profile →Full Google Gemini profile →