AI Launch Profile
Mistral NeMo
Mistral AI released Mistral NeMo, a 12B model built with NVIDIA, offering a 128K context window and Apache 2.0 checkpoints.
At a glance
Launch Snapshot
- Company
- Mistral AI
- Launch date
- July 18, 2024
- Launch type
- Open-Source Release
- Category
- AI Open-Weight Models
- Audience
- Developers, Enterprises, Researchers
- Pricing
- Apache 2.0 checkpoints are available for self-deployment; API and platform costs depend on provider usage.
- Free plan
- Yes
- API
- Yes
- Open weights/source
- Yes
Launch Context
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Verification & Sources
- Status
- Verified
- Source links
- 3
- Freshness
- Needs recheck: verified June 8, 2026
- Last verified
- June 8, 2026
- Last updated
- June 11, 2026
Key source checks
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Kingy Launch Score
7.7 / 10 · Solid
One earned credibility score, computed from cited evidence — not a placeholder. How the Kingy Launch Score works
Why this score
- Source & verification 7.5/10 — The official announcement plus the model-card documentation — dated, single-vendor sourcing. mistral.ai
- Product evidence 9.0/10 — Apache 2.0 checkpoints available for self-deployment, plus Hugging Face distribution and API access. huggingface.co
- Significance & novelty 7.0/10 — A 12B model built with NVIDIA offering a 128K context window under Apache 2.0 — a capable small open model. mistral.ai
- Traction signals not scored — insufficient sourced evidence
- Offer clarity 7.0/10 — Apache 2.0 self-deployment is documented; API and platform costs depend on provider usage. docs.mistral.ai
Evidence checked 2026-07-10
Creator Coverage Next Steps
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Kingy AI Take
Mistral AI released Mistral NeMo, a 12B model built with NVIDIA offering a 128K context window, with Apache 2.0 checkpoints for self-deployment plus API access (mistral.ai). Developers and Enterprises needing a smaller multilingual open model with long context can run it wherever they like. Small-model quality varies sharply by task, so benchmark it against your workloads rather than assuming parity with larger models.
Who it is for
Developers and enterprises seeking a smaller multilingual open model with long context and easier deployment.
Traction notes
Useful for developers who need a capable smaller open model with long context.
Source-backed record