NOESIS / AMAImedia

Last updated: 2026-08-29

Released as part of the NOESIS Professional Multilingual Dubbing Automation Platform (framework: DHCF-FNO — Deterministic Hybrid Control Framework for Frozen Neural Operators).

• Founder: Ilia Bolotnikov
• Organization: AMAImedia.com
• X (Twitter): @AMAImediacom
• LinkedIn: Ilia Bolotnikov
• Telegram: @djbionicl
• NOESIS version: v16.1
• Release date: 2026-08-26

Language support

This Qwen3.5-derived model follows the official Qwen3 language list below (119 languages and dialects) and the official Qwen3.5 coverage statement of 201 languages and dialects. Qwen3.5 publishes the expanded coverage count but does not provide an exhaustive 201-name enumeration in its model card. The list below is the complete language list published by Qwen for Qwen3 and is included as the transparent, documented baseline for this derivative.

English, French, Portuguese, German, Romanian, Swedish, Danish, Bulgarian, Russian, Czech, Greek, Ukrainian, Spanish, Dutch, Slovak, Croatian, Polish, Lithuanian, Norwegian Bokmål, Norwegian Nynorsk, Persian, Slovenian, Gujarati, Latvian, Italian, Occitan, Nepali, Marathi, Belarusian, Serbian, Luxembourgish, Venetian, Assamese, Welsh, Silesian, Asturian, Chhattisgarhi, Awadhi, Maithili, Bhojpuri, Sindhi, Irish, Faroese, Hindi, Punjabi, Bengali, Oriya, Tajik, Eastern Yiddish, Lombard, Ligurian, Sicilian, Friulian, Sardinian, Galician, Catalan, Icelandic, Tosk Albanian, Limburgish, Dari, Afrikaans, Macedonian, Sinhala, Urdu, Magahi, Bosnian, Armenian; Chinese (Simplified Chinese, Traditional Chinese, Cantonese), Burmese; Arabic (Standard, Najdi, Levantine, Egyptian, Moroccan, Mesopotamian, Ta’izzi-Adeni, Tunisian), Hebrew, Maltese; Indonesian, Malay, Tagalog, Cebuano, Javanese, Sundanese, Minangkabau, Balinese, Banjar, Pangasinan, Iloko, Waray (Philippines); Tamil, Telugu, Kannada, Malayalam; Turkish, North Azerbaijani, Northern Uzbek, Kazakh, Bashkir, Tatar; Thai, Lao; Finnish, Estonian, Hungarian; Vietnamese, Khmer; Japanese, Korean, Georgian, Basque, Haitian, Papiamento, Kabuverdianu, Tok Pisin, Swahili.

Released as part of the NOESIS Professional Multilingual Dubbing Automation Platform (framework: DHCF-FNO — Deterministic Hybrid Control Framework for Frozen Neural Operators).

NOESIS-Qwopus3.5-4B-v3-Supervisor-LongCtx-BF16

Role: Long-context Supervisor — PRODUCTION (multi-segment QC, orchestration plan, cross-stage review, batch best-of-N) for the dubbing pipeline. From: base NOESIS-Qwopus3.5-4B-v3 + plain-LoRA nt346_longctx_qwopus4b (CCE, max_len 768, completion-masked) merged. Trained on NF4 base, merged into BF16. BF16 = PRIMARY. Siblings: -NF4 (6GB runtime), -Q8_0.gguf (laptop), LoRA adapter.

Test results (2026-06-17)

Supervisor eval — eval_longctx_supervisor_v1.py (12 tests, grammar-constrained)

Quant	Size	Score
Q8_0	4.17 GB	11/12
IQ2_XXS	1.43 GB	8/12 (2-bit cliff: under-escalates on 248K vocab — not recommended)

Only failure at 11/12 = L1_mixed (aggregates trunc+speed mix to reject vs retry; fail-safe). Prior best long-ctx model (LFM2.5-7.5B) was 7/12.

Translation — FLORES devtest (chrF++/BLEU, n=20, no-think)

Direction	chrF++	BLEU
eng→rus	51.5	25.6
eng→cmn	32.0	7.4
AVG	41.7	16.5

Comparison vs dedicated models (same FLORES n=20)

Model	Supervisor-12	Translate AVG chrF++/BLEU
This (4B-LongCtx)	11/12	41.7 / 16.5
base 4B (no LoRA)	5/12	42.4 / 15.4
Qwopus3.5-9B-Translate Q4	5/12	43.8 / 16.5

Takeaway: gains full supervision (+6 over base) with no loss of translation (parity with base; within ~2 chrF of the dedicated 9B translator at < half the params). Strong all-rounder.

Speed (RTX 3060 Laptop 6GB, GPU, 33/33 layers offloaded)

• Q8_0: gen 53.5 tok/s, prompt eval 366 tok/s. (vs 9B-Translate Q4: 49.1 / 307.)

Eval on GPU via standalone llama-completion.exe -ngl 99 (pip llama_cpp is CPU-only). Written: 2026-06-17