Available Models
This page contains information on models available in the LLM context.
We provide a collection of open-weight large language models (LLMs) which are self-hosted on our HPC infrastructure, giving you flexibility and choice in your workflows to choose the ones that best fit your needs. User prompts and requests are processed in real time only. The content of these prompts is not saved, logged, or stored at any point. Your data is therefore handled with high protection standards to ensure confidentiality and security.
Model updates
Our model list will be updated in regular intervals, taking into account our available hardware resources as well as observed demand, usage patterns and utilization.
Current model list
| Model | Provider | Release Date | max. Content Length | Capabilities | Limitation and Comments |
|---|---|---|---|---|---|
| Mixtral-8x22B | Mistral AI | 2024-04-17 | 64K | Excels in reasoning, mathematics, coding, multilingual benchmarks | large but a bit older |
| Mistral-Small-3.2-24B | Mistral AI | 2025-06-25 | 128K | Compact 24B model optimized for low-latency inference; Good overall performance and quality |
Details: Mixtral-8x22B
Mixtral 8×22B is an open-source large language model (LLM) developed by Mistral AI, released in April 2024 under the permissive Apache 2.0 license. It employs a Sparse Mixture-of-Experts (SMoE) architecture:
- The model spans 141 billion total parameters, but typically activates only 39 billion parameters per inference, thanks to the MoE design
- It consists of 8 experts, each with 22B parameters, with 2 experts activated per token
Key Capabilities & Strengths:
- Efficiency & Cost-effectiveness: The SMoE setup allows Mixtral 8x22B to be faster and more cost-efficient than many dense models of similar or larger size (e.g., LLaMA 2 70B)
- Large Context Window: It supports a context window of 64,000 tokens, enabling it to process and recall large documents with precision
- Multilingual Proficiency: Mixtral 8x22B is capable in several languages, i.e. English, French, German, Italian, and Spanish, performing strongly on multilingual benchmarks compared to models
- Strong Performance in Math & Coding: It excels in reasoning-intensive tasks, coding, and mathematics. On benchmarks like GSM8K, HumanEval, and others, Mixtral 8×22B achieves top-tier scores—e.g., ~90.8% on GSM8K maj@8
Details: Mistral-Small-3.2-24B
Mistral-Small-3.2-24B belongs to the "Small" series from Mistral AI, specifically an enhanced iteration of the earlier Mistral Small 3.1 and Small 3 series. All 24B-parameter models are released under the Apache 2.0 license. It was officially introduced around June 2025, with model card version 2506 representing the "Instruct" variant optimized for instruction following.
Key Capabilities & Strengths:
- Stronger Instruction Following: Shows major improvements on tough benchmarks (Wildbench, Arena Hard), making it more reliable for guided tasks.
- Reduced Repetition & Infinite Loops: Generates cleaner outputs with fewer cases of runaway or repetitive text.
- Enhanced STEM & Coding Abilities: Higher accuracy on programming (HumanEval+, MBPP+) and reasoning-heavy benchmarks.
- Vision Input Support: Can handle images as input, enabling multimodal tasks like document parsing or visual Q&A.
- Extended Context Window (128K tokens): Capable of working with very long documents, transcripts, or multi-step workflows.
Deprecated models
None.
