What is Mistral AI doing across hiring, forks, releases, and public writing?

Frontier labfresh 1d

Mistral AI

mistral.ai ↗github/mistralai ↗dossier.json rss

Signal timeline557 total

Jul 1, 2026

3wModelmistralai/Leanstral-1.5-119B-A6BNegligible traction (4 downloads), not a major release.sourcenotability 2.0/10↓531♥208

Apr 27, 2026

Apr 27Modelmistralai/Mistral-Medium-3.5-128B-EAGLENew model, low traction.sourcenotability 5.0/10↓206♥57

Mar 31, 2026

Mar 31Modelmistralai/Mistral-Medium-3.5-128BLarge model with strong community tractionsourcenotability 9.0/10↓188k♥408

Mar 11, 2026

Mar 11Modelmistralai/Leanstral-2603Low traction model release by Mistralsourcenotability 4.0/10↓131♥168

Mar 4, 2026

Mar 4Modelmistralai/Mistral-Small-4-119B-2603-eagleLow traction model release by Mistralsourcenotability 3.0/10↓1.8k♥55

Mar 3, 2026

Mar 3Modelmistralai/Mistral-Small-4-119B-2603-NVFP4New model release from notable lab, modest downloadssourcenotability 7.0/10↓2.6k♥109

Jan 23, 2026

Jan 23Modelmistralai/Mistral-Small-4-119B-2603Notable release from Mistral, solid downloadssourcenotability 7.0/10↓191k♥411

Jan 21, 2026

Jan 21Modelmistralai/Voxtral-Mini-4B-Realtime-2602Massive HF downloads, major lab model releasesourcenotability 9.0/10↓1995k♥928

Nov 30, 2025

Nov 30Modelmistralai/Mistral-Large-3-675B-Base-2512Major model release but minimal community tractionsourcenotability 6.0/10↓70♥44

Nov 28, 2025

Nov 28Modelmistralai/Mistral-Large-3-675B-Instruct-2512Major model release, modest traction.sourcenotability 8.0/10↓880♥239

Nov 28Modelmistralai/Mistral-Large-3-675B-Instruct-2512-NVFP4Major frontier model release, moderate tractionsourcenotability 8.0/10↓7.3k♥58

Nov 28Modelmistralai/Devstral-2-123B-Instruct-2512Notable model release by Mistral, decent downloads but not explosive.sourcenotability 7.0/10↓66k♥328

Nov 17, 2025

Nov 17Modelmistralai/Voxtral-4B-TTS-2603Notable TTS model release with solid tractionsourcenotability 7.0/10↓3.9k♥886

Nov 10, 2025

Nov 10Modelmistralai/Mistral-Large-3-675B-Instruct-2512-EagleNotable model but minimal tractionsourcenotability 5.0/10↓62♥28

Oct 31, 2025

Oct 31Modelmistralai/Ministral-3-14B-Reasoning-2512Notable reasoning model from Mistral; moderate traction.sourcenotability 7.0/10↓33k♥144

Oct 31Modelmistralai/Ministral-3-14B-Instruct-2512-BF16Notable Mistral model release, moderate traction.sourcenotability 7.0/10↓16k♥29

Oct 31Modelmistralai/Ministral-3-14B-Base-2512Notable model release by Mistral; moderate downloads.sourcenotability 7.0/10↓7.8k♥60

Oct 31Modelmistralai/Ministral-3-8B-Reasoning-2512Notable model release from Mistral, moderate traction.sourcenotability 7.0/10↓32k♥90

Oct 31Modelmistralai/Ministral-3-8B-Instruct-2512-BF16New Mistral 8B instruct model, decent traction.sourcenotability 7.0/10↓17k♥23

Oct 31Modelmistralai/Ministral-3-8B-Base-2512Notable model release, moderate tractionsourcenotability 7.0/10↓10k♥48

Oct 31Modelmistralai/Ministral-3-3B-Reasoning-2512Notable Mistral model with solid downloadssourcenotability 8.0/10↓116k♥117

Oct 31Modelmistralai/Ministral-3-3B-Instruct-2512-BF16New model release by Mistral; solid traction.sourcenotability 7.0/10↓314k♥34

Oct 31Modelmistralai/Ministral-3-3B-Base-2512New small model from Mistral, solid traction.sourcenotability 7.0/10↓7.5k♥72

Sep 28, 2025

Sep 28Modelmistralai/Mistral-Large-3-675B-Instruct-2512-BF16Large model release but negligible traction.sourcenotability 4.0/10↓32♥13

Sep 12, 2025

Sep 12Modelmistralai/Magistral-Small-2509Notable model by Mistral with decent traction.sourcenotability 7.0/10↓35k♥305

Top signals

Agent answer

Mistral AI has 557 loaded public signals: 201 hiring, 12 forks, 250 releases or model cards, 78 talking, and 16 repos. Latest signal: mistralai/client-python v2.7.2. Data-business radar maps 46 signals to Data demand, Evals and quality, Infrastructure, Safety and policy, Product and customer. The standing analysis was generated with an unknown model and 0 evidence refs.

Hiring 201 Forks 12 Releases 250 Talking 78 Repos 16

Mistral AI

has loaded 557 public signals

Mistral AI

has hiring signal count 201

Mistral AI

has fork signal count 12

Mistral AI

has release signal count 250

Analysis — agent synthesisfull report →generated June 8, 2026

Thesis

Mistral AI is executing a broad open-weights strategy across every modality and size tier at once: text instruct/reasoning models from 3B up to 128B, a Voxtral audio/speech family (realtime, TTS), and a Devstral coding line. Distribution runs through Hugging Face at serious volume and a full client/tooling stack (mistral-inference, mistral-common, multi-language SDKs). The 2512/2602/2603 release cadence shows rapid, version-stamped iteration aimed at being the default open frontier alternative.

Shipping

The headline asset is speech/audio. `Voxtral-Mini-4B-Realtime-2602` leads with 1,187,772 30-day downloads (871 likes), with siblings `Voxtral-Mini-3B-2507` (378,895 downloads), `Voxtral-Small-24B-2507` (53,674), and a TTS entry `Voxtral-4B-TTS-2603` (25,891 downloads, 843 likes).

On text, the Small tier carries the install base: `Mistral-Small-3.2-24B-Instruct-2506` at 585,920 downloads, the newer `Mistral-Small-4-119B-2603` (49,665), and the 128B-class `Mistral-Medium-3.5-128B` (433,635). The Magistral reasoning line ships `Magistral-Small-2509` (55,566) and `Magistral-Small-2506` (46,228, 608 likes). A new edge-focused Ministral-3 family spans base/instruct/reasoning variants at 3B/8B/14B — e.g. `Ministral-3-3B-Reasoning-2512` (53,201) and `Ministral-3-8B-Instruct-2512-BF16` (51,106). Coding is covered by `Devstral-Small-2507` (33,490 downloads, 365 likes).

The open-source tooling is meaningful on its own: `mistral-inference` (10,814 stars), `mistral-vibe` (4,419 stars, shipping fast at v2.14.0), `mistral-finetune` (3,093), and `cookbook` (2,259). The plumbing layer — `mistral-common` (v1.11.3) and SDKs `client-python` (v2.4.9) and `client-ts` (with dedicated GCP and Azure v2.0.0 packages) — keeps releasing in lockstep with the models.

Research themes

No first-party writing captured yet.

Hiring & scaling

The 15 open roles point at commercial deployment and operations rather than core pretraining. The clearest signal is a concentrated "Applied AI / Forward Deployed" build-out in Munich — "Applied AI, Technical Lead, Forward Deployed AI Engineer - Munich", "Applied AI, Forward Deployed Machine Learning Engineer - Munich", and "Applied AI, Senior/Staff Forward Deployed Machine Learning Engineer - Munich" — plus an "AI4Engineering" vertical in Paris ("Applied Scientist / Domain Expert, AI4Engineering - EMEA", "AI Deployment Strategist, AI4Engineering - EMEA") and an "Applied AI Engineer, Site Reliability Engineer - EMEA". That is a customer-facing, enterprise-deployment motion. The rest is company-scaling overhead: GTM ("Strategic Account Marketing Manager, APAC" in Singapore, "Product Monetisation & Pricing Lead", "Solution Operations Manager - Singapore"), finance/legal ("Financial Controller", "Legal Counsel, Banking / Financing (Project finance)"), and people/workplace ops across Paris and Palo Alto. Geographically the center of gravity is Paris, with Munich, Singapore (APAC) and Palo Alto (North America) as the expansion edges.

Traction highlights

Most-downloaded model: `Voxtral-Mini-4B-Realtime-2602` at 1,187,772 30-day downloads, followed by `Mistral-Small-3.2-24B-Instruct-2506` (585,920) and `Mistral-Medium-3.5-128B` (433,635).
Most-starred repo: `mistral-inference` (10,814 stars), then `mistral-vibe` (4,419) and `mistral-finetune` (3,093).
Hacker News: thin — the only captured thread is `mistralai/mistral-vibe` at just 3 points and 0 comments.

Deep reports

Deep report

Human data & annotation at the frontier — what the hiring reveals

What 86 open human-data / annotation / data-quality roles reveal about the fuel layer — the clearest "sell to the labs" buy signal, since labs structurally buy data rather than build it.

Read the analysis →