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Discover how Mistral's Mistral Medium 3.5 and xAI's Grok 4.6 stack up against each other in this comprehensive comparison of two leading AI language models. Released in April 2026 and August 2026 respectively, these models represent significant advancements in artificial intelligence, with Mistral Medium 3.5 offering a 256,000-token context window and Grok 4.6 offering a 500,000-token context window.

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

Models Overview

Mistral Mistral Medium 3.5
Grok 4.6

Provider

The company that provides the model.
MistralxAI

Context Length

Maximum number of tokens the model can process
256K500K

Maximum Output

Maximum number of tokens the model can generate in one response
UnknownUnknown

Release Date

When the model was first released.
28-04-202608-2026

Knowledge Cutoff

When the model's training data ends.
UnknownUnknown

Open Source

Whether the model weights are openly available.
TRUEFALSE

Pricing Comparison

Compare the pricing of Mistral's Mistral Medium 3.5 and xAI's Grok 4.6 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.

Mistral Mistral Medium 3.5
Grok 4.6

Input Cost

Cost per million input tokens
$1.5 / 1M tokens$2 / 1M tokens

Output Cost

Cost per million tokens generated
$7.5 / 1M tokens$6 / 1M tokens

Comparing Benchmarks and Performance

Compare the performances of Mistral's Mistral Medium 3.5 and xAI's Grok 4.6 on industry benchmarks. Scores are the ones the providers and public leaderboards report; a benchmark neither reports is left out.

Mistral Mistral Medium 3.5
Grok 4.6

LMArena Elo

Crowd-sourced blind preference rating on the LMArena text leaderboard.
Benchmark not availableBenchmark not available

GPQA Diamond

Graduate-level science questions written to be search-proof.
Benchmark not availableBenchmark not available

SWE-bench Verified

Resolving real GitHub issues end to end.
Benchmark not availableBenchmark not available

SWE-bench Pro

Harder, contamination-resistant successor of SWE-bench Verified; not comparable with it.
Benchmark not availableBenchmark not available

Terminal-Bench 2.1

Agentic tasks completed in a real terminal.
Benchmark not availableBenchmark not available

MMLU-Pro

Broad knowledge and reasoning across 14 subjects, harder successor of MMLU.
Benchmark not availableBenchmark not available

Sources — Mistral Medium 3.5: mistral.ai, docs.mistral.ai; Grok 4.6: docs.x.ai, x.ai.

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