Mizan-Rerank-v2 — deprecated

This model is deprecated. Use the current Mizan reranker family instead.

Mizan-Rerank-v3-Turbo is the best replacement for v2: same family, same interface, but half the size (150M vs 305M), about twice the throughput, and higher on every held-out benchmark we measure. Mizan-Rerank-v3 is the larger option (306M) if you prefer it.

The current family

Model	Parameters	Throughput	Held-out mean nDCG@10	Fiqh nDCG@10	Status
Mizan-Rerank-v3-Turbo	150M	2,487 pairs/s	0.875	0.761	recommended replacement for v2
Mizan-Rerank-v3	306M	1,238 pairs/s	0.826	0.669	recommended
Mizan-Rerank-v2 (this model)	305M	1,191 pairs/s	0.685	0.618	deprecated

Held-out mean nDCG@10 is the mean over four held-out Arabic sets (MTEB NamaaMrTydi unseen subset, short adversarial, long-context adversarial, Multi-LLM); Fiqh nDCG@10 is measured on real fatwa-search queries with production candidate lists.

Migrating

The interface is identical, so migration is one line. Both models need trust_remote_code=True:

from sentence_transformers import CrossEncoder

# Before
model = CrossEncoder("ALJIACHI/Mizan-Rerank-v2", max_length=8192, trust_remote_code=True)

# After (recommended: half the size, ~2× the throughput, more accurate)
model = CrossEncoder("ALJIACHI/Mizan-Rerank-v3-Turbo", max_length=3072, trust_remote_code=True)

# Or the larger model
model = CrossEncoder("ALJIACHI/Mizan-Rerank-v3", max_length=3072, trust_remote_code=True)

Scores are not calibrated across versions, so if your pipeline uses an absolute score threshold to filter candidates, re-tune that threshold after switching.

Links

• Recommended replacement: Mizan-Rerank-v3-Turbo
• Larger model: Mizan-Rerank-v3
• Live demo (both models, with a switcher): ALJIACHI/Mizan-Rerank-V2-Demo
• License: Apache 2.0

Note for existing work

The weights are unchanged and stay online for reproducibility: existing pipelines pinned to ALJIACHI/Mizan-Rerank-v2 keep working. This card was reduced to a redirect on 2026-10-11; the full previous documentation (benchmarks, training configuration, usage examples) remains in the repository history, and the model's own benchmark chart is still at chart-1.png.

Citation

@software{Mizan_Rerank_v2_2026,
  author = {Ali Aljiachi},
  title = {Mizan-Rerank-v2: Arabic Long-Context Text Reranking Model},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/ALJIACHI/Mizan-Rerank-v2}
}

For new work, cite the replacement:

@software{Mizan_Rerank_v3_Turbo_2026,
  author = {Ali Aljiachi},
  title = {Mizan-Rerank-v3-Turbo: Compact Arabic Long-Context Reranker},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/ALJIACHI/Mizan-Rerank-v3-Turbo}
}