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GoogleGemini 3.6 FlashVSMistral AICodestral 22B

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 Gemini 3.6 Flash and Codestral 22B directly in their respective provider playgrounds to see which fits your specific prompt styles best.
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Model Specs

Gemini 3.6 Flash

Benchmarks & Scores

Coding (swe-bench-pro)
58.7%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)
93%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)
$3.00Input: $1.50 | Output: $7.50
Context WindowLarger
1.05M tokens
Model Specs

Codestral 22B

Open SourceAPI Available

Benchmarks & Scores

Coding (human-eval)
81.1%

good at code completion, standalone functions, and basic algorithms

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

Frequently Asked Questions about Gemini 3.6 Flash vs Codestral 22B

Codestral 22B is cheaper than Gemini 3.6 Flash. Codestral 22B has a blended cost of $0.45/1M tokens, which is about 6.7x cheaper than Gemini 3.6 Flash at $3.00/1M tokens.

For coding tasks, Gemini 3.6 Flash scores 58.7% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases), while Codestral 22B scores 81.1% on human-eval (good at code completion, standalone functions, and basic algorithms).

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