sovasoft/zora-v1.11

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Zora v1.11 — an open, honest LLM for the Balkans & Southeast Europe

зора = „dawn". One to unite them all. — by Sovasoft (ai.in.rs)

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1 · What Zora is

Zora is an open 8B language model (built on Qwen3-8B) for 12 languages of the Balkans and Southeast Europe: Serbian, Croatian, Bosnian, Macedonian, Slovenian, Albanian, Montenegrin, Bulgarian, Greek, Turkish, Romanian, Hungarian.

Zora is not built to be the biggest model — it is built to be honest, in-language, and multi-perspective:

• thinks in the target language instead of pivoting through English,
• shows several perspectives on contested topics instead of one national view,
• and above all: admits when it doesn't know instead of inventing facts.

2 · The development story (v1.0 → v1.1 → v1.11)

Version	Languages	State
v1.0	6	first public release
v1.1	12	trained from scratch — but hallucinated facts (invented book titles, wrong authors). Never released.
v1.11	12	the honest fix: says „I don't know", searches when unsure, in-language reasoning. This release.

v1.1 taught us the key lesson — a small model can't memorize every fact, so instead of faking it, v1.11 was retrained to be honest (see the benchmark below).

3 · Strengths & limits (honest)

Strengths

• ✅ Honesty: admits uncertainty instead of hallucinating (HALLU 1→10, DETAIL 0→8 vs v1.1)
• ✅ In-language quality: teaching, long-form, instructions — all strong across 12 languages
• ✅ Tool discrimination: answers general knowledge directly, searches only when needed
• ✅ Multi-perspective on contested history/culture

Limits (be aware)

• ⚠️ Multi-step logic/math (LOGIC/ANALYSIS) is weak — an 8B limit; step-by-step <think> helps and improves in v1.12
• ⚠️ Factual depth is limited (8B) — for exact facts (law, dates, current data) use RAG/web-search, don't rely on memory
• ⚠️ Quantization: use Q5_K_M / Q6_K / Q8_0. Avoid Q4 and below — heavy quantization made the model hallucinate in our tests.

4 · Benchmark (BalkanBench, 13 axes × 12 languages)

🔬 BalkanBench is open — test any model yourself: https://github.com/olivilo/balkanbench Deterministic scoring (script / language / keywords / numbers). v1.11 (16-bit): 84/156.

Zora leads the field — beating models 3–4× its size, including the current Gemma-4-31B and Qwen3.6-30B:

Model	Size	Score
Zora v1.11	8B	84
Gemma-4-31B	31B	77
Mistral-24B	24B	73
Qwen3.6-30B	30B	73
Salamandra	7B	66
EuroLLM	9B	65
Qwen2.5-32B	32B	65
Gemma-2-27B	27B	63
Aya	8B	61
BgGPT	7B	56
YugoGPT	7B	35

Quantization stays strong — Q5/Q6/Q8 all remain usable (avoid Q4):

The honesty fix in numbers, and per-axis strengths:

5 · Usage

Recommended quant: Q5_K_M (balanced) or Q6_K (near-lossless). Ollama: ollama run olivilo/zora # or: ollama run hf.co/sovasoft/zora-v1.11:Q5_K_M.

from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("sovasoft/zora-v1.11")
model = AutoModelForCausalLM.from_pretrained("sovasoft/zora-v1.11", device_map="auto")

6 · Help Zora grow

Zora's weakest areas are factual depth and some smaller languages. Send us open, licensable sources (texts, corpora, glossaries) in any of the 12 languages → kontakt@ai.in.rs. See the multilingual manifesto WHY-LANGUAGES on why thinking in your own language matters.

7 · Acknowledgements

Zora exists because of open source. We give our formal, heartfelt thanks:

• Above all, to the Qwen team at Alibaba — for developing and open-sourcing Qwen3 (Apache-2.0), the foundation model Zora is built upon. Without their generosity, Zora would not exist.
• To the platforms and structures that made this possible — Kaggle, Google Colab, Modal, HuggingFace, Ollama, Unsloth — for the compute, the tools, and the open infrastructure.
• To the open-source community, for the models, code, and knowledge freely shared with everyone.
• To the people of the Balkans — whose languages, voices, stories and perspectives are Zora's very heart.
• And to all that is.

зора — the dawn belongs to everyone.

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Sovasoft · ai.in.rs · one to unite them all