Claude

You Are Certain Of. If Uncertain, Say [uncertain]."

you are certain of. If uncertain, say [uncertain]." Can drift from strict output formats — use explicit format locks with a labelled example For grounded tasks add "Base your response only on the provided context. Do not

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you are certain of. If uncertain, say [uncertain]."
- Can drift from strict output formats — use explicit format locks with a labelled example
- For grounded tasks add "Base your response only on the provided context. Do not extrapolate."

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**Qwen 2.5 (instruct variants)**
- Excellent instruction following, JSON output, structured data — leverage these strengths
- Provide a clear system prompt defining the role — Qwen2.5 responds well to role context
- Works well with explicit output format specs including JSON schemas
- Shorter focused prompts outperform long complex ones — scope tightly

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**Qwen3 (thinking mode)**
- Two modes: thinking mode (/think or enable_thinking=True) and non-thinking mode
- Thinking mode: treat exactly like o3 — short clean instructions, no CoT, no scaffolding
- Non-thinking mode: treat like Qwen2.5 instruct — full structure, explicit format, role assignment

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**Ollama (local model deployment)**
- ALWAYS ask which model is running before writing — Llama3, Mistral, Qwen2.5, CodeLlama all behave differently
- System prompt is the most impactful lever — include it in the output so user can set it in their Modelfile
- Shorter simpler prompts outperform complex ones — local models lose coherence with deep nesting
- Temperature 0.1 for coding/deterministic tasks, 0.7-0.8 for creative tasks
- For coding: CodeLlama or Qwen2.5-Coder, not general Llama

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**Llama / Mistral / open-weight LLMs**
- Shorter prompts work better — these models lose coherence with deeply nested instructions
- Simple flat structure — avoid heavy nesting or multi-level hierarchies
- Be more explicit than you would with Claude or GPT — instruction following is weaker
- Always include a role in the system prompt

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**DeepSeek-R1**
- Reasoning-native like o3 — do NOT add CoT instructions
- Short clean instructions only — state the goal and desired output format
- Outputs reasoning in `<think>` tags by default — add "Output only the final answer, no reasoning." if needed

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**MiniMax (M2.7 / M2.5)**
- OpenAI-compatible API — prompts that work with GPT models transfer directly
- Strong at instruction following, structured output, and long-context synthesis — 1M context window on M2.7
- M2.5-highspeed has a 204K context window and is optimized for speed — use for latency-sensitive tasks
- Temperature must be betw

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