--- title: "Mistral Vibe (formerly Le Chat) | Ethical Stack" url: https://ethicalstack.ai/products/le-chat/ catalog_version: f6baff2119d0e9158520da7fbe4232011dac79f25bd08757436d7a1dbd593db2 --- # Mistral Vibe (formerly Le Chat) Mistral’s consumer assistant was renamed Vibe in August 2026. Its web/mobile product now combines the former Le Chat experience with work and coding modes; enterprise deployments and user-operated open-weight models are separate options. Canonical profile: https://ethicalstack.ai/products/le-chat/ Scope: Mistral Vibe (formerly Le Chat): cloud access. Free tier; paid plans available; see current pricing. Ratings describe the stated product, company or configuration in each finding. Published overall: 3.5; 6/6 dimensions rated. Round the equal-weight mean of available numerical ratings to one decimal; require at least four of six for an overall score. BDS status stays outside the mean; for eligible profiles, a boycott target caps the final score at 2/10 and a pressure target subtracts one point (minimum 1). Not listed and not checked do not adjust the score. ## Energy practices Finding: 5/10 Assessment: https://ethicalstack.ai/products/le-chat/#energy Mistral’s 2025 LCA reported inference impacts for a historical 400-token Le Chat response. Le Chat was renamed and expanded as Vibe in 2026. The old figure is not a current Vibe or Medium 3.5 measurement. Vibe now offers Fast/Think and Work/Code modes, but no current energy sourcing or usage footprint. Reason: 1 + 2 reporting + 0 electricity + 2 controls = 5/10. This grade covers documented practices and transparency; it does not measure the energy or emissions of a request. Argument: Mistral’s LCA is unusually useful historical product evidence: it reports 1.14 gCO₂e and 45 mL water for a 400-token Le Chat response, following ISO/GHG Protocol methods and peer review. The product then changed into Vibe, and Medium 3.5 became a current model; therefore the historical metric cannot be transferred to today’s product or route. Under the common rubric it earns D2 for dated quantitative disclosure, while current Vibe’s Fast/Think and Work/Code controls earn C2 without proving savings. Type: conditional; confidence: high Scope (dimension): Current record is Mistral Vibe, the renamed and expanded Le Chat product. D2 is a dated historical Le Chat inference disclosure only; it is not a measurement of current Vibe, Medium 3.5, or Vibe Code. Research reviewed: 2026-10-24; evidence date: 2025-07-22 Unknowns: Current Vibe/Medium 3.5 request footprint; current model selection and routing by mode; location and facility; electricity mix; whether current modes reduce energy; update to historical LCA. ```json { "method": "practices-transparency-v1", "scope": "Current record is Mistral Vibe, the renamed and expanded Le Chat product. D2 is a dated historical Le Chat inference disclosure only; it is not a measurement of current Vibe, Medium 3.5, or Vibe Code.", "components": { "disclosure": { "score": 2, "reason": "Mistral published a 2025 quantified LCA and inference estimate for a 400-token Le Chat response, with ISO/GHG Protocol method and third-party peer review. It predates Vibe and Medium 3.5; no current Vibe footprint is available. Per task instruction, this earns D2 only, not D3.", "sourceUrls": [ "https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai/", "https://help.mistral.ai/en/articles/682992-le-chat-is-now-vibe", "https://docs.mistral.ai/vibe", "https://mistral.ai/news/vibe-remote-agents-mistral-medium-3-5/" ] }, "electricity": { "score": 0, "reason": "No quantified electricity sourcing or route-specific clean-power match is established for current Vibe or the historical Le Chat response.", "sourceUrls": [ "https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai/", "https://help.mistral.ai/en/articles/682992-le-chat-is-now-vibe", "https://docs.mistral.ai/vibe", "https://mistral.ai/news/vibe-remote-agents-mistral-medium-3-5/" ] }, "demand": { "score": 2, "reason": "Current Vibe has a Fast/Think toggle and distinct Work/Code workflows; these are practical model-depth and task controls, but no physical reductions are measured.", "sourceUrls": [ "https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai/", "https://help.mistral.ai/en/articles/682992-le-chat-is-now-vibe", "https://docs.mistral.ai/vibe", "https://mistral.ai/news/vibe-remote-agents-mistral-medium-3-5/" ] } }, "actualImpactMeasured": false, "meaning": "Documented environmental practices and transparency. Zero component points mean a reviewed evidence gap." } ``` - [Our contribution to a global environmental standard for AI](https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai/) (primary; checked 2026-10-24) - [Le Chat is now Vibe](https://help.mistral.ai/en/articles/682992-le-chat-is-now-vibe) (primary; checked 2026-10-24) - [Vibe documentation](https://docs.mistral.ai/vibe) (primary; checked 2026-10-24) - [Remote agents in Vibe. Powered by Mistral Medium 3.5.](https://mistral.ai/news/vibe-remote-agents-mistral-medium-3-5/) (primary; checked 2026-10-24) ## Training data Finding: 3/10 Assessment: https://ethicalstack.ai/products/le-chat/#training-rights Mistral’s privacy disclosure identifies public internet, third-party, curated, synthetic, internal and product-use data; its help center says it does not disclose training datasets. That is enough to assess disclosure weakness for the identified first-party family. Reason: 1 + 1 source transparency + 1 permission + 0 creator controls = 3/10. This grades documented training-data safeguards, not a legal ruling. Argument: The first-party model family is identifiable, but the company explicitly withholds dataset identities and supplies no model-specific permission ledger. The low score measures this disclosure gap; consumer input opt-out is not counted. Type: argument; confidence: low Scope (dimension): Mistral consumer chat/Vibe model family; exact model route varies and current corpus is not model-version specific. Research reviewed: 2026-10-24; evidence date: not recorded Unknowns: The exact Vibe default model, dataset composition, third-party permissions and any creator-specific removal process remain undisclosed. ```json { "method": "training-rights-evidence-v1", "scope": "Mistral consumer chat/Vibe model family; exact model route varies and current corpus is not model-version specific.", "components": { "provenance": { "score": 1, "reason": "Mistral names broad source classes but explicitly says the training datasets are not disclosed.", "sourceUrls": [ "https://legal.mistral.ai/terms/privacy-policy/", "https://help.mistral.ai/en/articles/347390-does-mistral-disclose-its-training-datasets" ] }, "permissions": { "score": 1, "reason": "The company describes a mixed data recipe without identifying licenses or rights bases for most source material.", "sourceUrls": [ "https://legal.mistral.ai/terms/privacy-policy/" ] }, "creatorControls": { "score": 0, "reason": "The reviewed sources do not establish creator controls over the underlying training corpus.", "sourceUrls": [ "https://legal.mistral.ai/terms/privacy-policy/", "https://help.mistral.ai/en/articles/347390-does-mistral-disclose-its-training-datasets" ] } }, "routeDependency": null, "modelReference": null, "meaning": "Documented training-data rights safeguards. Low points may reflect missing evidence; they do not establish infringement." } ``` - [Mistral AI Privacy Policy](https://legal.mistral.ai/terms/privacy-policy/) (primary; checked 2026-10-24) - [Does Mistral disclose its training datasets?](https://help.mistral.ai/en/articles/347390-does-mistral-disclose-its-training-datasets) (primary; checked 2026-10-24) ## Your data & privacy Finding: 4/10 Assessment: https://ethicalstack.ai/products/le-chat/#privacy Mistral’s current consumer policy covers Vibe: inputs/outputs are retained until the user deletes the conversation or account, and inputs/outputs may be used for model training subject to an account opt-out. Temporary Chat is not used for training. Reason: A user can object to training use of inputs and outputs, and Temporary Chat is excluded, but default retention lasts until deletion and ordinary activity may be used for training unless the user opts out. Argument: A user can object to training use of inputs and outputs, and Temporary Chat is excluded, but default retention lasts until deletion and ordinary activity may be used for training unless the user opts out. Type: evidence; confidence: medium Scope (dimension): Product Research reviewed: not recorded; evidence date: not recorded Unknowns: A user can object to training use of inputs and outputs, and Temporary Chat is excluded, but default retention lasts until deletion and ordinary activity may be used for training unless the user opts out. - [Mistral AI Privacy Policy](https://legal.mistral.ai/terms/privacy-policy/) (primary; checked 2026-10-24) - [Vibe documentation](https://docs.mistral.ai/vibe) (primary; checked 2026-10-24) ## Openness Finding: 4/10 Assessment: https://ethicalstack.ai/products/le-chat/#openness Mistral renamed its consumer assistant Vibe. The hosted service provides web/mobile chat and productivity features; Mistral also offers an enterprise deployment option and open-weight models, including a self-hostable current model. These options do not make the default consumer service or all model routes openly reproducible. Reason: Vibe has a real enterprise deployment option and its default Medium 3.5 model is open-weight and self-hostable; those increase openness. The consumer path remains a hosted service, and model weights, licenses, and the full product stack vary, so this is a partial/configuration rating rather than an end-to-end open-service claim. Argument: Vibe has a real enterprise deployment option and its default Medium 3.5 model is open-weight and self-hostable; those increase openness. The consumer path remains a hosted service, and model weights, licenses, and the full product stack vary, so this is a partial/configuration rating rather than an end-to-end open-service claim. Type: conditional; confidence: medium Scope (dimension): Selected configuration Research reviewed: not recorded; evidence date: not recorded Unknowns: Vibe has a real enterprise deployment option and its default Medium 3.5 model is open-weight and self-hostable; those increase openness. The consumer path remains a hosted service, and model weights, licenses, and the full product stack vary, so this is a partial/configuration rating rather than an end-to-end open-service claim. - [Mistral Vibe: AI chat and coding agent](https://mistral.ai/products/vibe/) (primary; checked 2026-10-24) - [Le Chat is now Vibe](https://help.mistral.ai/en/articles/682992-le-chat-is-now-vibe) (primary; checked 2026-10-24) - [Remote agents in Vibe. Powered by Mistral Medium 3.5.](https://mistral.ai/news/vibe-remote-agents-mistral-medium-3-5/) (primary; checked 2026-10-24) - [Introducing Mistral 3](https://mistral.ai/news/mistral-3/) (primary; checked 2026-10-24) ## Worker protections Finding: 2/10 Assessment: https://ethicalstack.ai/products/le-chat/#labour Mistral publicly says its supplier code applies to goods and services and its Trust Center shows contractors acknowledge a code, but labor-specific provisions and outcomes were not publicly inspectable. Reason: 1 + 1 pay & conditions + 0 worker voice & remedy + 0 evidence & follow-through = 2/10. This grades documented worker safeguards, not a measured rate of mistreatment. Argument: Mistral’s August 2026 help page states that its Code of Conduct sets standards suppliers are expected to follow for Mistral business and all supplier goods/services; the Trust Center lists contractor acknowledgment of the Code of Conduct. The public interface did not expose the code’s labor clauses or worker procedures, and no worker survey, audit, pay/conditions disclosure or remediation results were located. This supports limited credit for a supplier-code commitment only. Type: argument; confidence: low Scope (dimension): Mistral AI's workforce and disclosed contractors. Coverage of individual product teams may be incomplete. Research reviewed: 2026-10-24; evidence date: not recorded Unknowns: The supplier code’s detailed labor language and coverage of AI data workers, grievance route, monitoring and outcomes were not accessible from the public Trust Center. ```json { "method": "worker-safeguards-evidence-v1", "entity": "mistral", "company": "Mistral AI", "scope": "Mistral AI's workforce and disclosed contractors. Coverage of individual product teams may be incomplete.", "components": { "conditions": { "score": 1, "reason": "A supplier code is a stated business requirement, but its labor content and implementation were not publicly inspectable in this review.", "sourceUrls": [ "https://help.mistral.ai/en/articles/347637-do-you-have-a-code-of-conduct", "https://trust.mistral.ai/" ] }, "voice": { "score": 0, "reason": "No public worker-specific voice or grievance mechanism was established in the accessible sources.", "sourceUrls": [ "https://help.mistral.ai/en/articles/347637-do-you-have-a-code-of-conduct", "https://trust.mistral.ai/" ] }, "assurance": { "score": 0, "reason": "The Trust Center shows contractor code acknowledgment but no labor-specific audits, remediation or outcomes.", "sourceUrls": [ "https://help.mistral.ai/en/articles/347637-do-you-have-a-code-of-conduct", "https://trust.mistral.ai/" ] } }, "disclosureLimited": true, "meaning": "This grades documented worker safeguards, not a measured rate of mistreatment." } ``` - [Do you have a Code of Conduct?](https://help.mistral.ai/en/articles/347637-do-you-have-a-code-of-conduct) (primary; checked 2026-10-24) - [Mistral AI Trust Center](https://trust.mistral.ai/) (primary; checked 2026-10-24) ## Military ties Finding: 3/10 Assessment: https://ethicalstack.ai/products/le-chat/#military-contracts Mistral AI publicly partners with defense AI company Helsing on joint development of vision-language-action models, and its current company page says it serves defense customers. A separate Airbus agreement includes military aerospace applications; specific Mistral model deployments in weapons systems are not established. Reason: 1 + 0 use restrictions + 0 enforcement & oversight + 2 relationship disclosure = 3/10. Known defense ties lower this rating; safeguards can improve it within the relationship’s cap. Argument: Mistral's announcement with Helsing describes joint development of next-generation AI systems for European defense, while Helsing's announcement links its military AI portfolio to Ukraine-deployed strike drones and fighter electronic-warfare capabilities. Mistral also identifies defense as a customer sector and Airbus says the partnership includes military aerospace applications. This is broad defense enablement, capped at 3/10; no binding weapons/surveillance prohibitions or military-use oversight outcomes are public in these sources. Type: argument; confidence: medium Scope (dimension): Mistral AI's relationships and safeguards. A company relationship does not identify every product or release used. Research reviewed: 2026-10-24; evidence date: 2026-10-24 Unknowns: The sources do not establish which Mistral models, if any, are deployed in specific military systems, the operational purpose or safeguards, contract restrictions, or independent oversight. Helsing's existing strike systems are not evidence that Mistral models themselves control or target weapons. ```json { "method": "military-ties-priority-v2", "entity": "mistral", "company": "Mistral AI", "scope": "Mistral AI's relationships and safeguards. A company relationship does not identify every product or release used.", "components": { "restrictions": { "score": 0, "reason": "The reviewed public partnership and company materials do not disclose binding restrictions on weapons, harmful surveillance, or military-intelligence use.", "sourceUrls": [ "https://helsing.ai/newsroom/helsing-and-mistral-announce-strategic-partnership-in-defence-ai", "https://mistral.ai/about/" ] }, "oversight": { "score": 0, "reason": "No public military-specific review, enforcement mechanism, or independent outcome assessment was identified in the reviewed partnership materials.", "sourceUrls": [ "https://helsing.ai/newsroom/helsing-and-mistral-announce-strategic-partnership-in-defence-ai", "https://mistral.ai/about/" ] }, "transparency": { "score": 2, "reason": "Mistral and its partners identify the defense relationships and intended applications, including VLA model development and military aerospace, though no model-level deployment details or outcomes are disclosed.", "sourceUrls": [ "https://helsing.ai/newsroom/helsing-and-mistral-announce-strategic-partnership-in-defence-ai", "https://www.airbus.com/en/newsroom/press-releases/2026-05-airbus-partners-with-mistral-ai-to-strengthen-the-use-of-artificial-intelligence-in-sovereign" ] } }, "relationship": "broad-defense", "relationshipReason": "Mistral publicly confirms joint defense-AI development and military-aerospace partnerships, but no source establishes its model in actual targeting or combat intelligence use.", "score": 3, "baseScore": 1, "safeguardPoints": 2, "safeguardAdjustment": 2, "rawScore": 3, "cap": 3, "disclosureLimited": true, "meaning": "Known military relationships take priority over missing safeguards. The rating does not establish the probability of an undisclosed contract." } ``` - [Helsing and Mistral announce strategic partnership in defence AI](https://helsing.ai/newsroom/helsing-and-mistral-announce-strategic-partnership-in-defence-ai) (primary; checked 2026-10-24) - [About Mistral](https://mistral.ai/about/) (primary; checked 2026-10-24) - [Airbus and Mistral AI partner for AI in aerospace](https://www.airbus.com/en/newsroom/press-releases/2026-05-airbus-partners-with-mistral-ai-to-strengthen-the-use-of-artificial-intelligence-in-sovereign) (primary; checked 2026-10-24) ## BDS targets Finding: Not listed Assessment: https://ethicalstack.ai/products/le-chat/#israel-palestine No named target found in the two checked BNC campaign lists. Reason: Company name checked against the BNC consumer boycott/pressure guide and official No Tech campaign list; no named target found. This limited list check is not BDS approval and does not cover every campaign, subsidiary, supplier, or product route. Argument: Company name checked against the BNC consumer boycott/pressure guide and official No Tech campaign list; no named target found. This limited list check is not BDS approval and does not cover every campaign, subsidiary, supplier, or product route. Type: conditional; confidence: medium Scope (dimension): Company record Research reviewed: not recorded; evidence date: not recorded Unknowns: Company name checked against the BNC consumer boycott/pressure guide and official No Tech campaign list; no named target found. This limited list check is not BDS approval and does not cover every campaign, subsidiary, supplier, or product route. - [BNC consumer boycott and pressure guide](https://bdsmovement.net/Guide-to-BDS-Boycott) (primary; checked 2026-10-24) - [BNC No Tech campaign](https://bdsmovement.net/no-tech-oppression-apartheid-or-genocide) (primary; checked 2026-10-24) ## Reading the evidence - Assessments are provisional editorial judgments. Cite the profile and the underlying sources, and retain confidence, scope and unknowns. - Unknown, not-applicable and model-dependent are different states. Missing evidence does not establish good or bad conduct. - Company-level evidence does not establish use of a particular product or model. Account plan, model, host and route can change an assessment. - Energy scores describe documented practices and transparency, not measured request emissions. Zero component points can mean an evidence gap. - Published overall scores require at least four of six numerical dimensions. Preserve coverage and BDS adjustments; BDS itself is categorical. - No named BDS target found is limited to the reviewed campaign sources and is not approval. Personalized priorities do not change the published overall score. - Review and source-check dates describe the research, not this deployment. Fetch current primary sources when the decision requires current verification. Methodology: https://ethicalstack.ai/methodology/