Code Assistant

Codestral Environmental Impact

Q: How much energy does Codestral use per query?

Each Codestral query consumes approximately 0.8 Wh of energy. This is 3x more than a traditional Google search (~0.3 Wh).

Q: What is Codestral's carbon footprint?

Based on the carbon intensity of its inference location (Mistral AI (France)), each Codestral query produces approximately 0.5g of CO2.

Q: How does Codestral compare to a Google search?

A Codestral query uses 3x more than a traditional Google search in terms of energy consumption. A Google search uses approximately 0.3 Wh, while Codestral uses 0.8 Wh per query.

Q: How much water does Codestral use?

Each Codestral query consumes approximately 3.3 mL of water, primarily used for cooling the data centers that process the request.

StandardEstimated

Mistral's specialised code generation model

Architecture: Dense Transformer (code-specialised)
Parameters: 22B
Context: 32,000 tokens
Provider: Mistral AI

0.80 Wh

Energy per query

0.50 g

CO₂ per query

3 mL

Water per query

3x more than

vs Google search

Energy per query

0.80 Wh

3x more than a Google search (0.3 Wh)

CO2 per query

0.50 g

France grid (50 gCO₂/kWh)

Water per query

3 mL

~303 queries to fill 1 litre

Processing location

Mistral AI (France)

Provider

Mistral AI

How does Codestral compare?

Ranked #43 of 152 models by energy per query

View full comparison

Detailed Breakdown

Energy Consumption

Codestral is Mistral's dedicated code model, trained on 80+ programming languages. At ~0.8 Wh per code completion, it sits between lightweight autocomplete models and full-capability chat models. Code generation tends to produce longer outputs than chat, increasing per-query energy.

Mistral AI — Codestral (May 2024)

Power Source & Carbon

Hosted on Mistral's infrastructure in France, benefiting from one of Europe's cleanest grids at approximately 50 g CO2/kWh due to France's nuclear energy base.

Mistral AI — About

Water Usage

At ~3.3 mL per completion, Codestral has a moderate water footprint typical of medium-sized models.

UC Riverside — Making AI Less Thirsty (2023)

About Codestral

Codestral is a code assistant model from Mistral AI, released in May 29, 2024. Mistral's specialised code generation model. Each query uses 0.80 Wh of energy and produces 0.50 g of CO₂. That's about 2.7x what a Google search consumes. It ranks in the top quartile of code assistant models for energy efficiency (#2 of 12).

Codestral benefits from running in France, one of the cleaner grid regions in our dataset at 50 gCO₂/kWh with 90% renewable energy. The same model running in a coal-heavy region would produce significantly more carbon per query.

These figures are estimates derived from hardware specifications and API benchmarks — Mistral AI has not published official energy data for Codestral. Actual consumption may vary significantly depending on batching, quantisation, and infrastructure optimisations that we cannot observe from outside.

Codestral in Context

7.3 kWh

per year

Your yearly Codestral footprint

At 25 queries per day, your annual Codestral usage consumes 7.3 kWh — comparable to running a LED light bulb for a month. That produces 4.6 kg of CO₂.

Key Insights

Runs on a 90% renewable grid — among the cleanest AI inference locations

What does your Codestral usage cost the planet?

Use our calculator to estimate your personal environmental footprint based on how often you use Codestral.

Calculate My Compute

Frequently Asked Questions

How much energy does Codestral use per query?

Each Codestral query consumes approximately 0.80 Wh of energy. This is 3x more than a traditional Google search (~0.3 Wh).

What is Codestral's carbon footprint?

Based on the carbon intensity of Mistral AI (France), each query produces approximately 0.50 g of CO2. The grid in this region has a carbon intensity of 50 g CO2/kWh with 90% renewable energy.