Solstice-AI/Qwen3.8-27B-TTURBO-Cold-Fusion-709-L-Uncensored-UltraOptimised-VariableThinking-1M

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

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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.

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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)

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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:

  # 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.

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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

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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.