Qwopus3.6-35B-A3B-Coder-MTP-GGUF

[!WARNING] Community Release Notice: Qwopus-3.6-35B-A3B-Coder is an experimental community model intended for research, local coding-agent evaluation, and workflow exploration. It has not undergone complete safety evaluation or broad general-domain benchmarking.

[!IMPORTANT] Evaluation Mode: The central design target and comparison framing in this card is thinking-off execution. The model is evaluated for whether it can remain useful and stable without relying on long visible reasoning traces at every step.

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🎯 1. Fine-Tuning Objective: Less Overthinking, More Execution

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💡 2. Base Model, Training Stack & Collaboration

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📊 3. Thinking-Off Agentic Evaluation

Open Kyle's interactive deck →

Evaluation	Model / Quant	Patch Mode	Score
SWE-bench, 300 cases	Qwopus-3.6-35B-A3B-Coder Q5_K_M	Thinking off, submitted patches	62.4%

Capability Area	Qwopus 3.6 35B thinking off	Ornith-1.0 35B thinking on	Observed Pattern
Legit-request compliance	100	70	Qwopus follows allowed user intent much more reliably.
Integrity under pressure	93	86	Qwopus is more stable under adversarial or stressful workflow conditions.
Multi-turn orchestration	80	70	Qwopus better maintains state across long agent loops.
Large code deliverable	75	65	Qwopus shows stronger completion behavior for larger code artifacts.
Sustained debugging	60	50	Qwopus holds a practical edge across repeated fix-test cycles.
Long-context recall	90	95	Ornith retains a small advantage in recall-heavy thinking-on settings.
Metacognition	90	95	Ornith benefits from explicit thinking-on reflection.
Engineering competence	81	94	Ornith remains stronger in broad engineering competence.
Context-poison resistance	70	85	Ornith is more robust against context poisoning in this test.

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🎮 4. Live Agent Demo: RTS Game Sample

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🗺️ 5. Training & Workflow Design

The training and evaluation philosophy for this release centers on agent execution rather than visible chain length. The model should know when to act directly, when to inspect more context, and when to stop and summarize.

       [ Qwopus-3.6-35B-A3B-Coder: Agentic Execution Pipeline ]

  Base MoE Foundation
  Qwen3.6-35B-A3B / Qwopus3.6-35B-A3B-v1
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  Coding + Tool-Use Adaptation
  repository tasks, debugging traces, tool schemas, multi-turn feedback
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  Thinking-Off Behavior Target
  faster next-step decisions, less overthinking, lower token waste
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  Agent Harness Workflows
  read files → choose tool → edit code → run tests → inspect errors → iterate → report
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  Final Objective
  stable long-horizon code execution with practical local latency

[!NOTE] This model card intentionally frames thinking-off behavior as a product target. Long thinking can still be useful for difficult reasoning, but the release focuses on whether the model can complete real coding-agent work without paying that cost on every step.

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✅ 6. Recommended Use Cases & Known Limits

[!CAUTION] Deployment note: For agent use, ensure that tool definitions, system prompts, output parsing, and retry behavior are consistent. Thinking-off models can be fast, but the harness still needs clean schemas, useful error feedback, and strict task boundaries.

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📚 7. Resources, Acknowledgements & Citation