Ttimms/Bible-Assistant-Qwen3.5-4B-v3.2-GGUF overview
Bible AI Assistant v3.2 — GGUF GGUF quants of Ttimms/Bible Assistant Qwen3.5 4B v3.2 https://huggingface.co/Ttimms/Bible Assistant Qwen3.5 4B v3.2 — a Qwen3.5 …
Runs locally from ~2.28 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| bible-v3.2-4b-Q4_K_M.gguf | GGUF | Q4_K_M | 2.52 GB | Download |
| bible-v3.2-4b-Q5_K_M.gguf | GGUF | Q5_K_M | 2.86 GB | Download |
| bible-v3.2-4b-Q6_K.gguf | GGUF | Q6_K | 3.23 GB | Download |
| bible-v3.2-4b-Q8_0.gguf | GGUF | Q8_0 | 4.17 GB | Download |
| bible-v3.2-4b-f16.gguf | GGUF | F16 | 7.85 GB | Download |
| bible-v3.2-4b-nvfp4.gguf | GGUF | GGUF | 2.28 GB | Download |
Model Details
| Model ID | Ttimms/Bible-Assistant-Qwen3.5-4B-v3.2-GGUF |
|---|---|
| Author | Ttimms |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | Qwen/Qwen3.5-4B,Ttimms/Bible-Assistant-Qwen3.5-4B-v3.2 |
| Last modified | 2026-09-25T19:52:44.000Z |
Model README
---
license: apache-2.0
base_model:
- Qwen/Qwen3.5-4B
- Ttimms/Bible-Assistant-Qwen3.5-4B-v3.2
base_model_relation: quantized
tags:
- bible
- rag
- gguf
- llama.cpp
- qwen3.5
- nvfp4
- text-generation
language:
- en
pipeline_tag: text-generation
quantized_by: Ttimms
license_link: https://huggingface.co/Qwen/Qwen3.5-4B/blob/main/LICENSE
---
Bible AI Assistant v3.2 — GGUF
GGUF quants of Ttimms/Bible-Assistant-Qwen3.5-4B-v3.2
— a Qwen3.5-4B continued-fine-tune for retrieval-grounded Bible Q&A, and the
first checkpoint in the project's line to clear every acceptance gate: 80.3%
verbatim verse recall, 98.9% citation, 1.9% hallucination, and the strongest
result in its size class on a cross-encoder semantic metric against every
other ~4B bible-tuned model tested. See the base repo for the full model
card, version history, and the honest evaluation against larger models too.
Architecture
graph TD
Base["Qwen/Qwen3.5-4B"]
V31["v3.1 adapter (thematic-synthesis SFT)"]
Cont["DMT-style continued fine-tune - RAFT-fixed thematic_qa + rehearsal, lr 5e-5"]
Merge["merge adapter -> bf16"]
Conv["convert_hf_to_gguf --no-mtp + llama-quantize"]
ST["Bible-Assistant-Qwen3.5-4B-v3.2 (safetensors)"]
GG["...-v3.2-GGUF (Q4_K_M / Q5_K_M / Q6_K / Q8_0 / F16)"]
NV["...-v3.2-GGUF NVFP4 (advanced-gguf-quantizer, Blackwell-native)"]
RAG["hybrid RAG: dense (nomic) + BM25 + RRF + bge-reranker-v2-m3"]
LLM["llama.cpp / LM Studio / Ollama"]
Base --> V31 --> Cont --> Merge --> ST
Merge --> Conv --> GG
Merge --> Conv --> NV
ST --> RAG --> LLM
GG --> LLM
NV --> LLM
Download
Grab one file, not the whole repo.
| File | Quant | Size | Notes |
|---|---|--:|---|
| bible-v3.2-4b-Q4_K_M.gguf | Q4_K_M | 2.7 GB | recommended for general use |
| bible-v3.2-4b-nvfp4.gguf | NVFP4 | 2.5 GB | smallest; lower mean PPL ratio, higher KLD; see NVFP4-GGUF below before choosing this over Q4_K_M |
| bible-v3.2-4b-Q5_K_M.gguf | Q5_K_M | 3.1 GB | |
| bible-v3.2-4b-Q6_K.gguf | Q6_K | 3.5 GB | |
| bible-v3.2-4b-Q8_0.gguf | Q8_0 | 4.5 GB | near-lossless |
| bible-v3.2-4b-f16.gguf | F16 | 8.4 GB | full precision |
NVFP4-GGUF (Blackwell-native)
bible-v3.2-4b-nvfp4.gguf is a mixed NVFP4 quant built with
(deep-mode tensor search, allow_diagnostic sensitivity ranking, hard-gated
on tail KLD) targeting native Blackwell FP4 tensor cores
(BLACKWELL_NATIVE_FP4=1 confirmed on an RTX 5070 Ti / SM120 at eval time) —
a genuinely different quantization technique than the k-quant ladder above,
not just another point on the same size/quality curve.
**Real, measured result — a mixed outcome, stated plainly rather than
rounded to a single "better/worse":** identical methodology, same bf16
reference, same calibration/eval corpus, both files run through
llama-perplexity --kl-divergence back-to-back.
| | Size | bpw | Mean PPL ratio vs bf16 | Mean KL-divergence vs bf16 |
|---|--:|--:|--:|--:|
| NVFP4 (this file) | 2.45 GB | 4.66 | 1.1130 ± 0.0008 | 0.1109 ± 0.0003 |
| Q4_K_M (published) | 2.71 GB | 5.15 | 1.1228 ± 0.0008 | 0.0929 ± 0.0003 |
NVFP4 is smaller and has a lower mean-token perplexity ratio than
Q4_K_M despite spending fewer bits per weight (4.66 vs 5.15 bpw) — but it
has a higher mean KL-divergence against the bf16 reference, meaning its
per-token probability distribution drifts further from the base model even
where average next-token accuracy holds up. Passed this project's own
coherence + hard tail-KLD gate (p99/p999) either way.
Which to pick: Q4_K_M if you want the closest per-token match to the
unquantized model's behavior (the safer default for a RAG assistant that
quotes verses verbatim). NVFP4 if size and mean perplexity matter more than
tail-distribution fidelity, or you're specifically exercising Blackwell's
native FP4 path.
**Status (2026-09-17): this is the current NVFP4 candidate, not a final
answer.** A follow-up run (nvfp4_mxfp6 profile, promoting the most
KLD-sensitive tensors to MXFP6_E2M3 instead of leaving the whole model at a
uniform NVFP4 floor) is queued to test whether real additional bits closes
the KLD gap to Q4_K_M without losing NVFP4's size/PPL win. This card will be
updated with that result when it lands — check back before assuming this is
the final NVFP4 quality bar for this checkpoint.
Run it in
- llama.cpp —
llama-server -m <file>.gguf -ngl 99 - LM Studio (bundles a recent llama.cpp)
- koboldcpp
- Jan
- text-generation-webui
- Ollama — once its bundled llama.cpp includes this arch (see Requirements)
Requirements
Qwen3.5 is a hybrid architecture (qwen35 / Gated-DeltaNet + attention). You
need a recent llama.cpp — a build that includes the qwen35 hybrid arch
(commit 3173a56 or newer). Verified working with llama-cli/llama-server
from a source build — coherent output, correctly quoted John 3:16, 175 tok/s
on an RTX 5070 Ti.
- ✅ llama.cpp (current):
llama-server -m bible-v3.2-4b-Q4_K_M.gguf -ngl 99 - ✅ LM Studio (recent versions bundle a current llama.cpp)
- ⚠️ Ollama 0.33.x: the bundled llama.cpp is too old for the
qwen35arch
(check_tensor_dims: tensor 'blk.32.attn_norm.weight' not found). Use once
Ollama updates its runtime, or run llama.cpp directly.
bible-v3.2-4b-nvfp4.gguf was built and evaluated end-to-end on an RTX 5070 Ti
(Blackwell, SM120) using llama.cpp's native NVFP4 GEMM path. It has not been
verified on non-Blackwell hardware in this session — if your llama.cpp build
or GPU lacks native FP4 kernel support, prefer one of the k-quant files above.
Thinking mode
The Qwen3.5 chat template defaults to thinking on. This model was fine-tuned
without <think> traces, so for a grounded RAG assistant you want it off:
- llama.cpp
/v1/chat/completions: pass
"chat_template_kwargs": {"enable_thinking": false}, or
- use a chat template that emits a closed empty
<think>\n\n</think>\n\nafter
<|im_start|>assistant\n (the project's deployment/pc/Modelfile does this).
Intended use
Retrieval-augmented Bible Q&A — the model expects retrieved verses in a Context:
block, then the question. It is not designed for context-free use, medical /
legal / financial advice, counselling (it redirects those to a pastor / crisis
line), or authoritative theological rulings.
License
Weights: Apache-2.0 (inherits from Qwen3.5-4B). Project code: MIT. Bible
translations: public domain. See the base repo for full attribution and the
version history that led to this checkpoint.
Run Ttimms/Bible-Assistant-Qwen3.5-4B-v3.2-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models