<!-- https://models.searchit-agent.ai/en/models/mistral-large-2-1/ | searchit Models -->

# Mistral Large 2.1

Mistral Large 2.1 by Mistral AI: no offer with a token price is listed at present. Profile and benchmarks are on this page.

- [Compare offers](https://models.searchit-agent.ai/ui-fat/modelle_api?q=mistral-large-2-1)
- [View price history](https://models.searchit-agent.ai/ui-fat/modelle_api?q=mistral-large-2-1)

## Profile

| Profile |  |
|---|---|
| Developer | Mistral AI |
| Type | Language models |
| Origin | FR |
| Input types | text |
| Context (tokens) | 131,072 |
| Max. output (tokens) | 104,857 |
| Reasoning | ohne |
| Parameters (bn) | 123 |
| Open weights | ✓ yes |
| Licence | proprietär |
| VRAM at 4-bit (GB) | 72 (RTX PRO 6000) |
| Released | – |

[Open in the app](https://models.searchit-agent.ai/ui-fat/modelle_api?q=mistral-large-2-1)

searchit Entity Extraction (24 Sept 2026): 45.8 %

## Offers with processing in the EU (0)

No offers in this group.

[Open in the app](https://models.searchit-agent.ai/ui-fat/modelle_api?q=mistral-large-2-1)

## Offers outside the EU (0)

No offers in this group.

[Open in the app](https://models.searchit-agent.ai/ui-fat/modelle_api?q=mistral-large-2-1)

## AI Act

Whether the developer has signed the Code of Practice for general-purpose AI models: unknown. What this means is explained under “EU and AI Act”. [EU processing and AI Act](https://models.searchit-agent.ai/en/knowledge/eu-and-ai-act/)

## Benchmarks

| Benchmarks |  |
|---|---:|
| GPQA Diamond (Artificial Analysis) | 48.6 |
| Humanity's Last Exam (Artificial Analysis) | 3.3 |
| Berkeley Function-Calling Leaderboard V4 | 38.4 |
| OTIS Mock AIME 2024-2025 (Epoch AI) | 7.8 |
| FrontierMath Tiers 1-3 v2 (Epoch AI) | 0.34 |
| Vectara HHEM-2.3 | 4.5 |
| Vectara HHEM-2.3 – antwortrate | 99.9 |
| Vectara HHEM-2.3 – halluzination | 4.5 |
| LiveBench (Aufgabensatz 2026-01-08) | 48.43 |
| MÖVE (Bundesdruckerei), arXiv 2606.13111 – qa | 0.7 |
| searchit Extraktions-Messlauf REPO-9 (PROMPT-CRAWLER-TEXT-START, 8 Dokumente × 3 Läufe) – treffer beziehungen | 30.7 |
| searchit Extraktions-Messlauf REPO-9 (PROMPT-CRAWLER-TEXT-START, 8 Dokumente × 3 Läufe) – treffer entitaeten | 60.9 |
| MMLU-Pro (TIGER-Lab Leaderboard) | 67.9 |

_[Report an error on this page](https://models.searchit-agent.ai/en/report/report-error/?seite=https%3A%2F%2Fmodels.searchit-agent.ai%2Fen%2Fmodels%2Fmistral-large-2-1%2F)_

---

Prices as of 14 Oct 2026. Providers' list prices, without guarantee.
