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Mistral

Mistral AI provides open and commercial large language models and the Le Chat conversational assistant for developers and businesses.

Primary category: AI Chat
About this data
This page reflects public online discussion, collected and scored by automated systems and summarized using AI. It is not a statement of fact, not an audit, and not our own opinion of the product. Automated analysis can be incomplete or wrong, and scores carry the limitations described in our methodology. Companies can respond with their own perspective. See how this is calculated.

Updated July 6, 2026

Overall Pulse Score

61
Pulse Score

+6 over this period

A 0-100 index summarizing the tone of 1,037 relevant public mentions gathered from public online communities across 25 weeks in the selected period. It measures online sentiment, not a rating of the product's quality.

Weekly Sentiment Trend

Pulse Score by week over the selected period. Each point is one complete week of mentions.

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This week in public discussion

Sentiment around Mistral showed a modest uptick over the recent period, with commenters praising AI quality and feature additions, including discussion of a local agent skills integration that several mentions highlighted as a notable step for open model flexibility. However, complaint themes were also prominent, with users reporting bugs around model compatibility and raising privacy and copyright concerns. Some discussion touched on skepticism about Mistral's role in public sector deals. Overall tone remained mixed, with cautious interest alongside recurring frustrations.

Read the deeper analysis

AI-generated summary of public online discussion during this period. It reflects the tone of that discussion, not facts about the product or our views.

Sentiment mix by week

How the tone of public discussion splits each week.

Ringed points mark weeks with unusually high discussion volume, more than double this product's typical week.

Most-discussed praise

Strong features177
AI quality168
Compared to rivals162
New releases72
Good integrations58

Most-discussed complaints

Compared to rivals145
AI quality111
Bugs58
Missing features46
Reliability34

Themes across the selected period, with mention counts.

How Mistral compares

Pulse Score over the selected period versus the top tracked competitors in AI Chat.

Where the mentions come from

Share of the 1,037 relevant public mentions in the selected period, by source.

Hacker News58% (600)
Bluesky20% (203)
GitHub16% (166)
YouTube7% (68)

Sample public mentions

Showing 5 of 1,037 analyzed public mentions in this period, with links to the original source. We do not reproduce full threads.

Hi HN, I'm Antoine Zambelli, AI Director at Texas Instruments.I built Forge, an open-source reliability layer for self-hosted LLM tool-calling.What it does:- Adds domain-and-tool-agnostic guardrails (retry nudges, step enforcement, error recovery, VRAM-aware context management) t...

Hacker NewsMay 19, 2026

"I Want to Wash My Car. The Car Wash Is 50 Meters Away. Should I Walk or Drive?" This question has been making the rounds as a simple AI logic test so I wanted to see how it holds up across a broad set of models. Ran 53 models (leading open-source, open-weight, proprietary) with ...

Hacker NewsFeb 23, 2026

My great-grandfather Reuben P. Box was a US Forest Ranger in Northern California, and I've got his daily work diary from 1927-1945, through the depression, WWII, Conservation Corps, and lots of forest fires. I've scanned the entire thing, had Claude help with transcription, index...

Hacker NewsFeb 16, 2026

GGUF models doesnt'work anymore. ### What is the issue? Since Ollama 0.30, some models that previously worked on Ollama 0.24 have stopped functioning. These models include: - Gemma4:26b-a4b-it-q8_0 - Deepseek-php33-mlx:latest - Deepseek-coder-v2:16b - Mistral-small3.2:24b However...

GitHubJun 2, 2026

ChatGPT thinks I died in 2011. (Spoiler: I did not.) Mistral thinks I'm a British actor in The Crown and Doctor Who. GLM thinks I wrote The Elements of Style (my name is neither Strunk nor White) and The Chicago Manual of Style.

BlueskyJun 24, 2026

2,457+ more analyzed mentions, full history, and theme breakdowns are part of Pro.

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Deeper analysis

  • Feature quality and open-source accessibility dominated praise, but bug reports and reliability complaints were nearly as prominent in the conversation.
  • Sentiment dipped to its lowest point in early June before recovering sharply in the final two weeks, though the late rebound came with reduced discussion volume.
  • Privacy and copyright concerns were a persistent source of division, with commenters split between appreciating openness and voicing institutional distrust.
  • Competitor comparisons ran in both directions, reflecting an unsettled community view of where Mistral stands relative to alternatives.
Praise themeMentions
Strong features177
AI quality168
Compared to rivals162
New releases72
Good integrations58
Complaint themeMentions
Compared to rivals145
AI quality111
Bugs58
Missing features46
Reliability34

Discussion about Mistral over the past four weeks opened at a middling baseline, with early conversation carrying a broadly neutral-to-mixed tone. The score trajectory tells a story of instability: after a notable lift in early May, sentiment slid back through mid-May and continued declining into early June, touching the lowest point in the observed window. Commenters during that stretch appeared more preoccupied with technical friction and unresolved concerns than with enthusiasm, and the volume of mentions stayed relatively high, suggesting the conversation was active but contentious rather than celebratory.

The most dominant positive themes centered on feature praise and perceived AI quality, with a meaningful share of discussion framing Mistral favorably in comparison to competitors. Several mentions highlighted the open-source angle and local-model accessibility as genuine differentiators, with at least one contributor expressing excitement about new integrations that extend Mistral to local, private deployments. New feature releases also drew some positive attention, suggesting that product momentum was visible to engaged commenters.

On the complaint side, bugs drew the highest complaint volume, and reliability concerns layered onto that frustration. Privacy worries surfaced as a recurring undercurrent, with several mentions tying Mistral to broader unease around copyright practices and institutional procurement decisions. One thread of discussion suggested suspicion about how Mistral is positioned in public-sector deals, carrying a skeptical and at times cynical tone.

Sentiment recovered sharply in the final two weeks of the window, with the score climbing to its highest point in the full period on notably lower mention volume, which some tracking contexts associate with a more favorable but narrower audience. Whether that recovery signals a genuine shift or a temporary quiet period remains unclear from the discussion alone. Opinion was most divided around privacy and institutional trust, where positive framing of openness coexisted with pointed skepticism.

AI-generated summary of public online discussion during this period. It reflects the tone of that discussion, not facts about the product or our views.

Member perspectives

Individual opinions from Pro members, posted over time. These are personal member views, not aggregated sentiment data.

Data summary

Total mentions analyzed (all time)
2,462
Mentions in selected period
1,037
Weeks in range
25
vs AI Chat average (48)
Above by 13
Pricing
Free tier; paid plans available
Sources
Hacker News (600), Bluesky (203), GitHub (166), YouTube (68)

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Mistral

61

Trainual

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Full comparison

Score-level preview from live weekly tracking.

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