whichLlmmodel
Back to Dashboard

Mistral AICodestral 22BVSxAIGrok 4.20

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

Standardized reasoning and coding benchmarks are currently pending verification for one or both of these models. We recommend testing Codestral 22B and Grok 4.20 directly in their respective provider playgrounds to see which fits your specific prompt styles best.
Was this recommendation helpful?
Model Specs

Codestral 22B

Open SourceAPI Available

Benchmarks & Scores

Coding (human-eval)
81.1%

basic standalone code completion and simple functions

Reasoning (gpqa-diamond)
N/A

graduate-level science QA

Cost & Context

Cost (per 1M tokens)6.7x cheaper
$0.45Input: $0.30 | Output: $0.90
Context Window
32.77k tokens
Model Specs

Grok 4.20

Benchmarks & Scores

Coding (swe-bench-pro)
51.8%

complex codebases, multi-file repositories, and architectural planning

Reasoning (gpqa-diamond)
90%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)
$3.00Input: $2.00 | Output: $6.00
Context WindowLarger
1.05M tokens

Frequently Asked Questions about Codestral 22B vs Grok 4.20

Codestral 22B is cheaper than Grok 4.20. Codestral 22B has a blended cost of $0.45/1M tokens, which is about 6.7x cheaper than Grok 4.20 at $3.00/1M tokens.

For coding tasks, Codestral 22B scores 81.1% on human-eval (basic standalone code completion and simple functions), while Grok 4.20 scores 51.8% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).

Do you want to find a model for your constraints?

Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.

Open Model Finder