Bielik 11B v2.2 Instruct GGUF
Bielik 11B v2.2 Instruct is a Polish-language instruction-tuned model from speakleash, available in GGUF format for local inference. It supports 32,768-token context and runs on consumer hardware via quantization. Apache 2.0 licensed — commercial use is permitted.
If you need a local Polish-language assistant and have 8–16 GB of VRAM, Bielik 11B v2.2 is the most practical open option available in GGUF right now. It won't beat a 70B model on reasoning, but it's honest value for its size. Stick to Q5 or Q6 quants if quality matters. Recommend for Polish-first workloads; skip if your use case is multilingual or reasoning-heavy.
›Why this rating
Auto-generated rating (Opus 4.7 judge, claude-opus-4-7). Overall 9.00/10. License is explicit Apache 2.0 on the HF card, though the card also references additional Terms of Use at bielik.ai/terms — a minor caveat the row doesn't mention but doesn't invalidate the apache-2.0 tag. Metadata (11B, Mistral family, Polish, GGUF) is consistent with the card. The editorial voice is operator-grade: honest about quant degradation, the 11B reasoning ceiling, and low download count. Best use case is sharp (Polish instruction following / document Q&A). Deployability guidance (Q5/Q6 recommendation, 8–16 GB VRAM) is concrete and useful. Brand fit is solid for runlocalai readers needing a non-English local model.
Flags: - HF card references additional bielik.ai Terms of Use alongside Apache 2.0 — row claims unrestricted commercial use without noting this addendum; worth a one-line caveat - Context length of 32768 not explicitly confirmed in the excerpt provided (inherited from base model assumption)
Overview
Bielik 11B v2.2 Instruct is a Polish-language instruction-tuned model from speakleash, available in GGUF format for local inference. It supports 32,768-token context and runs on consumer hardware via quantization. Apache 2.0 licensed — commercial use is permitted.
Strengths
- Instruction-tuned specifically for Polish — one of the stronger open options in this language
- GGUF format with multiple quantization levels lets you trade quality for VRAM as needed
- 32K context fits long documents and multi-turn conversations
- Apache 2.0 license allows commercial deployment without restrictions
Weaknesses
- Heavily Polish-focused — don't expect reliable quality in other languages
- Lower quantizations (Q4 and below) will degrade output quality noticeably
- 11B parameters puts a ceiling on complex reasoning; larger models will outperform it on hard tasks
- Only 1,653 HF downloads — limited community feedback on real-world failure modes
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 6.1 GB | 8 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of Bielik 11B v2.2 Instruct GGUF.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run Bielik 11B v2.2 Instruct GGUF?
Can I use Bielik 11B v2.2 Instruct GGUF commercially?
What's the context length of Bielik 11B v2.2 Instruct GGUF?
Source: huggingface.co/speakleash/Bielik-11B-v2.2-Instruct-GGUF
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify Bielik 11B v2.2 Instruct GGUF runs on your specific hardware before committing money.