Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-1M (GGUF UltraOptimised)
Official Solstice-AI Quantization Suite • Hardware Multi-Token Prediction (MTP) • 10-Level Cognitive Architecture • Twin-Turbo GAIN
Original Model & GAIN Merge by DavidAU • Curated Quantization, MTP Integration & Cognitive Architecture by Solstice-AI
Executive Summary
Solstice-AI/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-UltraOptimised-MTP-1M is the curated, zero-bloat GGUF release of DavidAU's flagship Qwen3.8-27B Twin Turbo Cold Fusion foundation (DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored).
This curated release eliminates non-MAX duplicates, degraded extreme low-bits, and external drafters in favor of pure, Pareto-optimal checkpoints with Native Hardware Multi-Token Prediction (MTP) and Solstice-AI's 10-Level Cognitive Reasoning Architecture.
Curated "GOATed" Checkpoints
Every checkpoint in this suite is a MAX-MTP tier: retaining the critical output tensor (output.weight / lm_head) in unquantized 16-bit precision alongside Q8_0 MTP heads to preserve reasoning accuracy (Arc-C 701+ at 4-bit):
| Checkpoint File |
Size |
VRAM Budget |
Optimal Target |
...-MAX-MTP-Q4_K_M.gguf |
17.23 GB |
16 GB VRAM |
The GOAT 4-bit (16-bit lm_head, Arc-C 701, ideal for RTX 4080 / 16GB GPUs) |
...-MAX-MTP-Q5_K_M.gguf |
19.73 GB |
24 GB VRAM |
The GOAT 5-bit (sweet spot of generation speed & reasoning depth) |
...-MAX-MTP-Q6_K.gguf |
22.38 GB |
24–32 GB VRAM |
High-fidelity near-lossless sweet spot for RTX 3090/4090 & Apple Silicon |
...-MAX-MTP-Q8_0.gguf |
28.16 GB |
32 GB+ VRAM |
Full reference precision |
mmproj-BF16.gguf |
0.87 GB |
System RAM/VRAM |
Spatial-temporal multimodal vision projector (images & video frames) |
10-Level Cognitive Reasoning Architecture
Built directly into tokenizer_config.json and chat_template.jinja, this suite introduces a 10-level cognitive spectrum. Levels feature soft-elastic pacing (thoughts scale organically to problem difficulty without artificial token caps).
Triggering Modes In-Chat & Via API
- In-Chat Message Tags (works across Ollama, LM Studio, OpenWebUI, LibreChat):
- Thinking Mode: Add
{REASON:<alias>} anywhere in your message (e.g., {REASON:amax}, {REASON:uhigh}, {REASON:athena}). The tag is stripped from the prompt and persists across subsequent chat turns.
- Instant Instruct Mode (Zero Reasoning Tokens): Prefix with
i (e.g., {REASON:iamax}, {REASON:iuhigh}, {REASON:iathena}) to close <think></think> immediately and generate a direct answer framed through that persona.
- API Parameters:
```python
# Thinking Mode
response = client.chat.completions.create(
model="...",
messages=[{"role": "user", "content": "Analyze system architecture"}],
extra_body={"chat_template_kwargs": {"reasoning_effort": "amax"}}
)
# Instant Instruct (0 Thinking Tokens)
response = client.chat.completions.create(
model="...",
messages=[{"role": "user", "content": "Fast code generation"}],
extra_body={"chat_template_kwargs": {"enable_thinking": False, "reasoning_effort": "uhigh"}}
)
```
The Cognitive Spectrum
| Level |
Primary Key |
Technical Aliases |
Mythological Alias |
Cognitive Framework & Behavior |
| 0 |
disabled |
none, off, direct |
Mortal |
0 tokens: <think></think> closed immediately for instant direct output. |
| 1 |
ulow |
ultra-low, micro |
Hermes |
Rapid instinct & sanity check. Direct path from premise to verdict (<150 tokens). |
| 2 |
low |
compact, fast |
Apollo |
Crisp logic and premise validation with zero cognitive overhead. |
| 3 |
lmed |
low-medium, targeted |
Artemis |
Boundary hunter: tests zero conditions, nulls, and hidden edge cases. |
| 4 |
medium |
med, balanced |
Athena |
Strategic balance: evaluates architectural trade-offs and structural cohesion. |
| 5 |
mhigh |
medium-high, architect |
Prometheus |
Proactive forethought: models 10x/100x scale, failure modes, and fault tolerance. |
| 6 |
high |
deep, thorough |
Solstice |
Deep systemic derivation: multi-branch hypothesis trace and red-team falsification. |
| 7 |
xhigh |
extreme-high (Default) |
Hyperion |
Native Qwen 3.8 continuous derivation and exhaustive semantic deconstruction. |
| 8 |
uhigh |
ultra-high, swarm |
Einstein |
20-Agent Swarm: Deploys 20 virtual perspective agents across Sternberg styles. |
| 9 |
amax |
absolute-max, deep-research |
Oracle |
Deep Research Council: 1–5 complexity scaling, multi-expert panel & audit matrix. |
Quickstart
Native MTP Speculative Decoding via llama.cpp
Checkpoints with -MTP- feature native dual-stream token prediction built into the weights (no external drafter file needed):
# High-speed interactive chat with native MTP
llama-cli \
--hf-repo Solstice-AI/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-UltraOptimised-MTP-1M \
--hf-file Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-MTP-Q4_K_M.gguf \
--mmproj mmproj-BF16.gguf \
-c 1048576 \
-ngl 99 \
-p "{REASON:amax} Perform a rigorous architectural evaluation of microservices vs monoliths."
Server Deployment
llama-server \
--hf-repo Solstice-AI/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-UltraOptimised-MTP-1M \
--hf-file Qwen3.8-27B-TTURBO-Fable-C-Fusion-709-L-Uncen-NM-DAU-NEO-MAX-MTP-Q4_K_M.gguf \
--mmproj mmproj-BF16.gguf \
--host 0.0.0.0 --port 8080 -c 1048576 -ngl 99
Citations & Acknowledgments
- DavidAU for the phenomenal Qwen3.8-27B Twin-Turbo Cold Fusion GAIN merged base foundation.
- Qwen Team for the foundational Qwen 3.8 architecture.
- Solstice-AI for downstream curated quantization, MTP packaging, and the 10-level cognitive architecture.
