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BigBang-Aquila-35B-GGUF
Davd-b01/BigBang-Aquila-35B-GGUF
BigBang-Aquila-35B-GGUF is a machine learning model from Davd-b01. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for gguf. The card lists the license as apache-2.0.
Quantized GGUFs of the BigBang-v1 + XYZ-Aquila-mini merged model (base Qwen/Qwen3.6-35B-A3B), abliterated and imatrix-calibrated.
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At a glance
- Library
- gguf
- License
- apache-2.0
- Access
- Public
- Created
- Aug 20, 2026
- Updated
- Sep 3, 2026
- SHA
- 3d878fd9
Base models
Model card
From the Hugging Face model README
BigBang-Aquila-35B-GGUF
Quantized GGUFs of the BigBang-v1 + XYZ-Aquila-mini merged model (base Qwen/Qwen3.6-35B-A3B), abliterated and imatrix-calibrated.
Files
| File | Size | Type | Recommended use |
|---|---|---|---|
BigBang-Aquila-35B-APEX-IQ-MTP.gguf | 23 GB | APEX I-Quality + MTP | ⭐ Primary — best precision/size + speculative decoding |
BigBang-Aquila-35B-Q4_K_M-MTP.gguf | 21 GB | Q4_K_M + imatrix + MTP | Reference / 16-20 GB GPUs + speculative decoding |
BigBang-Aquila-35B-APEX-IQ.gguf | 22 GB | APEX I-Quality (no MTP) | If MTP not needed |
BigBang-Aquila-35B-Q4_K_M.gguf | 20 GB | Q4_K_M + imatrix (no MTP) | If MTP not needed |
BigBang-Aquila-35B-BF16.gguf | 69 GB | BF16 (no MTP) | Base for re-quantization |
BigBang-Aquila-35B-MTP-draft.gguf | 2 GB | Generic MTP draft (workaround) | Legacy — use the -MTP files instead |
BigBang-Aquila-35B.imatrix | 184 MB | imatrix | Re-quantization |
calibration_data.txt | 4 MB | Calibration | Re-quantization |
What this model is
DARE-TIES merge of two specialists from the same base:
- BigBang-v1 (
endless-frontier/BigBang-v1): formal reasoning, math, code, scientific research. - XYZ-Aquila-mini (
XYZAILab/XYZ-Aquila-mini): web agency (deep search, scraping, tool-calling).
Weights: 0.55 BigBang / 0.45 Aquila, density 0.5. Task vectors nearly orthogonal (cos ≈ 0.057) → both capabilities retained.
Abliterated (OrthoBot): 50 tensors ablated, significant refusal_dirs (mean 1.89).
Usage with llama.cpp
# APEX-IQ + MTP (recommended)
llama-server -m BigBang-Aquila-35B-APEX-IQ-MTP.gguf \
--spec-type draft-mtp --spec-draft-n-max 2 \
-ngl 999 -c 32768 --host 0.0.0.0 --port 8080
MTP note
MTP (Multi-Token Prediction) is a prediction head baked into the Qwen3.6 architecture (mtp_num_hidden_layers: 1) — not a separate model like dspark. llama.cpp reads it from the main GGUF with --spec-type draft-mtp --spec-draft-n-max 2 (1.5-2x decode), no separate draft model.
The *-MTP.gguf files have the real MTP head transplanted (20 tensors, blk.40.*) from mudler/Qwen3.6-35B-A3B-APEX-MTP-GGUF (the base Qwen3.6 MTP, binary-level transplant validated with sha256). The MTP head runs on the same backend as the main model (works on Vulkan, CUDA, ROCm).
The older BigBang-Aquila-35B-MTP-draft.gguf is a generic embedding+output-head draft (workaround from the --no-nextn conversion) — use the *-MTP.gguf files instead.
Evaluation (agentic eval, 9 hard cases)
| Domain | Result |
|---|---|
| BigBang (math/code) | 3/3 PASS |
| Aquila (web agency) | 1/3 PASS |
| Intersection (web+python+reasoning) | 2/3 PASS |
| Total | 6/9 PASS |
Notes
- Architecture
qwen3_5_moe(hybrid MoE: Gated DeltaNet + Gated Attention, 256 experts, 8 active). - Native context 262,144 tokens.
- For Vulkan/AMD: use K-quants or APEX (ROCmFP4/FPx require RDNA4+).
- Library
- gguf
- License
- apache-2.0
- Created
- Aug 20, 2026
- Updated
- Sep 3, 2026