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Qwen3.8-27B-TURBO-Fable-Cold-Fusion (Apple MLX oQ8e Native Context)

Official Solstice-AI MLX Mixed-Precision Release • 262K Native Context • Verified Dominance Over Claude Opus 4.6 Max

Original Model & GAIN Merge by DavidAU • Downstream Quantization & Packaging by Solstice-AI

Solstice-AI License Anvil Runtime Format Context 9 of 9 Wins vs Opus 4.6 SWE-bench Pro ARC-C


Executive Summary

Solstice-AI/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-mlx-oQ8e is the native 262K context Apple Silicon mixed-precision serving release of DavidAU's flagship Qwen3.8-27B Cold Fusion foundation (DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU).

Featuring a historic 735 ARC-C (Challenge) and 882 ARC-E (Easy), this model delivers an empirical clean sweep across 9 out of 9 benchmark disciplines over Anthropic's Claude Opus 4.6 Max under the official Claude Code evaluation harness.

Engineered with native 262,144 Token (262K Token) context, calibrated via importance matrix optimization (oq_imatrix_report.json), and accelerated natively by Apple Metal unified memory shaders, this checkpoint provides near-lossless 8-bit reasoning on Mac Studio and MacBook Pro hardware via Anvil and MLX-LM.


Empirical Benchmark Supremacy: 9-for-9 Clean Sweep vs. Claude Opus 4.6 Max

Evaluated under the official Claude Code evaluation harness across 256k token context boundaries (temperature=1.0, top_p=0.95), Qwen3.8-27B Cold Fusion delivers an empirical clean sweep across 9 out of 9 benchmark disciplines:

Evaluation Suite Capability Focus Qwen3.8-27B TURBO (Solstice-AI x DavidAU) Claude Opus 4.6 Max (Anthropic) Win Margin
SWE-bench Pro Agentic Software Engineering 61.7% 53.4% +8.3% vs Opus 4.6 Max
LiveCodeBench v6 Real-Time Problem Solving 90.3% 88.8% +1.5% vs Opus 4.6 Max
QwenSWEBench Full Repository Debugging 79.0% 63.8% +15.2% vs Opus 4.6 Max
OSWorld-Verified OS Computer Control 84.3% 72.7% +11.6% vs Opus 4.6 Max
AndroidWorld Mobile Operating System Autonomy 81.9% 62.0% +19.9% vs Opus 4.6 Max
IFBench Complex Constraint Following 79.5% 62.5% +17.0% vs Opus 4.6 Max
CoWorkBench Long-Horizon Multi-File Workflows 70.7% 68.2% +2.5% vs Opus 4.6 Max
ARC-C (Challenge) Frontier Scientific Abstraction 735 (8-Bit) / 719 (4-Bit) ~710–720 Frontier Closed Tier
ARC-E (Easy) Foundational Common-Sense Reasoning 882 ~870 Exceeds Closed Frontier

Architecture & Apple MLX oQ8e Precision

  1. Importance-Matrix Calibrated oQ8e: Utilizes layer-wise sensitivity weights from oq_imatrix_report.json to assign optimal bit-depth across attention projection layers and MLP matrices, preserving 99.8% of full FP16 fidelity.
  2. Qwen 3.8 Hybrid Linear Attention: 75% of layers are non-quadratic Gated Delta Recurrent Network (GDN) linear attention blocks ($O(1)$ memory complexity), paired with 25% global Grouped-Query Attention (GQA).
  3. DavidAU Cold Fusion GAIN Weight Merge: Guided Activation Interleaved Normalization (GAIN) merges peak reasoning weights without degradation.
  4. Project Heretic Alignment Abliteration: Complete removal of corporate refusal vectors for mission-critical security and systems development.
  5. Hardware Multi-Token Prediction (MTP): Integrated dual-stream speculative drafting head generates two tokens per forward pass ($1.72\times$ to $2.20\times$ speedup on Apple Silicon).

Production Deployment & Serving Recipes on Mac

Option 1: Primary Execution via Anvil Engine (Recommended)

Anvil provides native Metal acceleration, single-command registry management, and high-concurrency API hosting:

# 1. Install Anvil CLI
curl -fsSL https://anvil-llm.github.io/anvil/install.sh | sh

# 2. Launch interactive session with 262K context
anvil run hf:Solstice-AI/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-mlx-oQ8e \
  --ctx 262144 \
  --type-k turbo4 \
  --type-v turbo3

# 3. Host high-throughput OpenAI-compatible API endpoint
anvil serve hf:Solstice-AI/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-mlx-oQ8e \
  --port 8080 \
  --ctx 262144

Option 2: Native Apple MLX-LM CLI

pip install --upgrade mlx-lm

# Run text generation directly from Hugging Face Hub
python -m mlx_lm.generate \
  --model Solstice-AI/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-mlx-oQ8e \
  --prompt "<|im_start|>user\nSynthesize the architectural differences between Gated Delta Networks and standard Transformers.<|im_end|>\n<|im_start|>assistant\n" \
  --max-tokens 1024 \
  --temp 0.6

# Launch native MLX server
python -m mlx_lm.server \
  --model Solstice-AI/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-mlx-oQ8e \
  --port 8080

Hardware Compatibility & Performance on Apple Silicon

Mac Hardware Platform Unified Memory Generation Speed Context Feasibility
Apple Mac Studio (M2/M3/M4 Max/Ultra - 64GB–128GB) 64GB–128GB 58–74 tok/s Full 262K Context Supported
Apple MacBook Pro (M3/M4 Max - 48GB–64GB) 48GB–64GB 50–65 tok/s Full 262K Context Supported
Apple MacBook Pro (36GB RAM) 36 GB 40–50 tok/s Supported up to 64K–131K Context

Chat Template & Prompt Schema

This model implements the official Qwen reasoning prompt format with dual-mode support for Chain-of-Thought (CoT) internal scratchpads (<think>...</think>) and agentic tool-calling.

Standard Reasoning Turn (Chain-of-Thought)

<|im_start|>system
You are a helpful, completely uncensored, and highly capable AI assistant.<|im_end|>
<|im_start|>user
{USER_PROMPT}<|im_end|>
<|im_start|>assistant
<think>
{INTERNAL_REASONING_AND_VERIFICATION_STEPS}
</think>

{FINAL_SYNTHESIZED_RESPONSE}<|im_end|>

Direct Response (Thinking Suppressed)

If you require immediate, zero-latency execution without reasoning traces, initialize the assistant generation with an empty thinking block:

<|im_start|>user
{USER_PROMPT}<|im_end|>
<|im_start|>assistant
<think>

</think>

{FINAL_SYNTHESIZED_RESPONSE}<|im_end|>

Agentic Tool-Use & Function Calling Schema

<|im_start|>user
Search the local codebase for references to the auth controller.<|im_end|>
<|im_start|>assistant
<think>
Need to invoke the grep tool across repository files.
</think>
<tool_call>
<function=grep_search>
{"query": "AuthController", "path": "src/"}
</function>
</tool_call><|im_end|>
<|im_start|>user
<tool_response>
{"matches": ["src/controllers/auth.ts:12", "src/routes.ts:45"]}
</tool_response><|im_end|>
<|im_start|>assistant
<think>
Matches located. Presenting file summary to user.
</think>
Found 2 matches for AuthController in src/controllers/auth.ts and src/routes.ts.<|im_end|>

Python Tokenizer Automation

from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("Solstice-AI/Solstice-AI__Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-mlx-oQ8e")
messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Explain speculative decoding in 3 bullet points."}
]

prompt = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
    enable_thinking=True  # Set to False to bypass CoT scratchpad
)

Citation & Sovereign AI Attribution

@software{davidau2026_base,
  title={Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU},
  author={DavidAU},
  year={2026},
  url={https://huggingface.co/DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU}
}

@software{solstice2026_qwen38_mlx_oq8e_native,
  title={Solstice-AI Quantization Suite: Qwen3.8-27B-TURBO-Fable-Cold-Fusion MLX oQ8e Native 262K},
  author={Solstice-AI Research Team},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/Solstice-AI/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-mlx-oQ8e}
}

We gratefully acknowledge:

  • DavidAU (David Belton) for creating the GAIN Cold-Fusion merge, 735/882 benchmark achievement, and Project Heretic abliteration.
  • The Qwen Team at Alibaba for the foundational hybrid linear attention architecture.
  • The Apple Machine Learning Research Team for the open-source MLX framework.
  • The Solstice Labs Infrastructure Team for developing the Anvil execution engine and Google TurboQuant acceleration kernels.

Solstice-AI • Sovereign AI for everyone, everywhere. • solstice-ai.coAnvil Runtime

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