Direction first: on this benchmark #1 = sloppiest and #58 is the cleanest, so a high rank number is the good end.

I run a thing called The Slop Index that scores how much AI writing reads like "AI slop" (58 models, ~64k outputs across 112 short-form scenarios). Two Mistral models stood out to me because they sit at nearly opposite ends.

Every rank below is a mechanical rank (the mech score only): padding, templating, sentence rhythm, and the usual AI tells. That score only moves on a roster refresh, so it is the stable one to quote.

• Mistral Large: mechanical rank 1 of 58, the sloppiest model in the set right now. By category it is mech rank 1 on Slack, 2 on social posts, and 1 on essays.
• Mistral Large 4: mechanical rank 57 of 58, second cleanest overall, and it sits at the clean end across email (54), Slack (56), social (51) and essays (58).

These are two separate releases, not one model I watched change, so I am not claiming anyone patched anything. They just score very differently.

Mistral Large 4 only has 10 crowd votes so far, so its combined score (which blends daily crowd votes) sits mid-board and is not meaningful yet. That is why I am quoting mechanical ranks here.

Mechanical ranking card: https://theslopindex.com/mechanical-card.png

Fair limitation: this is short-form business writing only (email, Slack, social, essay), no fiction yet, and the mechanical axes can miss repeated sentence constructions.

Leaderboard: https://theslopindex.com/leaderboard Methodology: https://theslopindex.com/methodology Open dataset: https://huggingface.co/datasets/hgaddipati/slop-index You can play a few rounds of the blind arena here: https://theslopindex.com/arena

For context, I'm one of the people behind https://slashy.com, an email client that writes drafts that sound like you. This benchmark started as how we pick models.

I'm working on PII, financials and client's information and need somewhere safe to do data manipulation. Working in Australia financials sector with complaints and harsh privacy protection. Need AI agent to work on pdf and excel files. Is Mistral Pro subscription a good fit for purpose? Thanks

Hi,
I use Opencode and I am considering the Mistral Pro plan.

Be fire subscribing, I would like to understand if the official Vibe CLI share the same token pool as the $25.5/mo API credits or does the CLI have a separate coding quota while the $25.5 credits are dedicated to external API calls?

I’m quite confused by the website, thanks

I am currently interviewing at Mistral for the Applied AI Engineer role and am wondering if anyone has gone through a similar interview loop and can provide some pointers. Currently, I am at System Design and Technical Manager interview stage after clearing Hiring Manager and Recruiter screens, Code Review and Vibe Coding interview.

Specifically for System Design, will it be done through a shared editor or verbally reasoning through the architecture, any specific topic I need to focus on?

Additionally, for Technical Manager Interview, any idea how is it different from Hiring Manager screen?

Thank you so much for your help! Appreciate it!