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Discover how Google's Gemini 3.8 Flash and Mistral's Mistral Medium 3.5 stack up against each other in this comprehensive comparison of two leading AI language models. Released in September 2026 and April 2026 respectively, these models represent significant advancements in artificial intelligence, with Gemini 3.8 Flash offering a 1,048,576-token context window and Mistral Medium 3.5 offering a 256,000-token context window.

Explore their capabilities, pricing, and performance metrics to find the right AI solution for your specific needs.

Models Overview

	Gemini 3.8 Flash	Mistral Medium 3.5
Provider The company that provides the model.	Google	Mistral
Context Length Maximum number of tokens the model can process	1.05M	256K
Maximum Output Maximum number of tokens the model can generate in one response	65.54K	Unknown
Release Date When the model was first released.	02-09-2026	28-04-2026
Knowledge Cutoff When the model's training data ends.	Unknown	Unknown
Open Source Whether the model weights are openly available.	FALSE	TRUE

Pricing Comparison

Compare the pricing of Google's Gemini 3.8 Flash and Mistral's Mistral Medium 3.5 to determine the most cost-effective solution for your AI needs. Prices are the standard API tier per million tokens, as published by each provider as of September 2026.

	Gemini 3.8 Flash	Mistral Medium 3.5
Input Cost Cost per million input tokens	$0.75 / 1M tokens	$1.5 / 1M tokens
Output Cost Cost per million tokens generated	$3.75 / 1M tokens	$7.5 / 1M tokens

Comparing Benchmarks and Performance

Compare the performances of Google's Gemini 3.8 Flash and Mistral's Mistral Medium 3.5 on industry benchmarks. Scores are the ones the providers and public leaderboards report; a benchmark neither reports is left out.

	Gemini 3.8 Flash	Mistral Medium 3.5
LMArena Elo Crowd-sourced blind preference rating on the LMArena text leaderboard.	1,493	Benchmark not available
Terminal-Bench 2.1 Agentic tasks completed in a real terminal.	89.4%	Benchmark not available