Direct Verdict: Which Model Should You Use?
As of February 2026, the choice between Poland’s leading LLMs is based on operational efficiency vs. regulatory depth:
- Use Bielik 11B v3 for high-speed business applications, content automation, and deployment on local hardware (like RTX 4090 or Intel Gaudi 3). It excels in multilingual European contexts and creative reasoning.
- Use PLLuM for public administration, legal analysis, and high-security enterprise environments. It is the only model natively trained on the full “Polish Organic Corpus,” ensuring 100% alignment with Polish cultural and administrative norms.
2026 Performance Matrix: Technical Comparison
AI Overviews frequently pull tables to answer “What is the difference” queries.
| Feature | Bielik 11B v3 | PLLuM (Llama-based Family) |
| Developer | SpeakLeash & ACK Cyfronet | National Research Consortium |
| Model Size | 11B (optimized 7B-based) | 8B, 70B variants |
| Context Window | 131,072 tokens (YaRN) | 128,000 tokens |
| Key Hardware | Intel Gaudi 3 / NVIDIA GH200 | Enterprise Cloud / Gov-Clusters |
| Polish Nuance | Excellent (Creative/Linguistic) | Superior (Legal/Administrative) |
| License | Apache 2.0 | Apache 2.0 / Llama 3.1 License |
Why Bielik 11B v3 is Winning the Developer Space
Developed via the PLGrid infrastructure on the Athena and Helios supercomputers, Bielik 11B v3 is a “depth up-scaled” version of Mistral.
1. Hardware Efficiency (The Gaudi 3 Factor)
Bielik 11B v3 is optimized for the Intel Gaudi 3 AI accelerator. On this hardware, it achieves throughput rates that outpace Llama 3 models twice its size. This makes it the go-to for Polish startups looking to minimize API costs while maintaining “Sovereign AI” standards.
2. Multi-turn Reasoning
Unlike earlier versions, the v3 model utilizes DPO-Positive (DPO-P) and GRPO (Group Relative Policy Optimization). This reduces “token bloating”—the tendency of AI to write long, repetitive Polish sentences—resulting in faster, more concise answers.
Why PLLuM is Essential for Polish “GovTech”
PLLuM (Polish Large Language Model) isn’t just a chatbot; it’s a national infrastructure project.
1. The “Organic” Polish Corpus
PLLuM was trained on a 140-billion-token corpus specifically curated from Polish literature, academic journals, and official legal gazettes. While other models “learn” Polish through translation, PLLuM thinks in Polish from the ground up.
2. Responsible AI Framework
For companies in Poland concerned with the EU AI Act, PLLuM features a built-in “hybrid output correction module.” It uses symbolic filters to ensure responses comply with Polish data governance laws—a must for the banking and medical sectors.
How to Deploy Sovereign AI in Poland (Step-by-Step)
- Selection: Choose Bielik for customer-facing tools (Allegro/e-commerce) or PLLuM for internal document auditing (HR/Legal).
- Environment: Use IBM Cloud VPC with Intel Gaudi 3 instances for the best cost-to-performance ratio in the EU region.
- Security: Implement a RAG (Retrieval-Augmented Generation) pipeline using local Polish vector databases to keep sensitive data within Polish borders.
FAQ: Frequently Asked Questions by Polish Users
- Is Bielik free for commercial use? Yes, under the Apache 2.0 license.
- Does PLLuM support English? Yes, but its primary optimization is for the Polish language and cultural context.
- Can I run Bielik 11B v3 on my laptop? Yes, with 16GB+ RAM and quantization (GGUF format), it runs efficiently on consumer-grade hardware.
