Editing Openai/691a14bb-ac48-8008-85d0-2e4fb3f780d1 (section)

=== Assistant: Understood. ===
Understood. Here’s a model-by-model breakdown of the options shown in your Windsurf screenshot, focused strictly on coding performance, reasoning, and optimal use cases:

===== GPT-5 (low / medium / high reasoning) =====
* Pros: - Best at structured reasoning, complex refactoring, and long-context comprehension. - High-reasoning variant excels in debugging multi-file codebases and explaining architectural decisions. - Medium-reasoning offers nearly equal code accuracy at lower credit cost.
* Cons: - Slower for small edits or single-function tasks.
* Use: - High: full-system analysis, architectural planning, deep debugging. - Medium: mid-complex refactors, writing new modules. - Low: quick utility generation, single-function edits.

GPT-5-Codex
* Pros: Specialized for pure code completion, boilerplate generation, and syntax precision.
* Cons: Weak reasoning; not ideal for architectural design or explanation.
* Use: Code generation, scaffolding, template expansion.

GPT-4o / GPT-4.1
* Pros: Fast, balanced generalist. Reliable language-code interleaving.
* Cons: Narrower context, weaker long-term reasoning than GPT-5.
* Use: Documentation writing, lightweight code reviews, mixed natural-language and code tasks.

gpt-oss 120B (Medium)
* Pros: Good for rapid prototyping and experimentation.
* Cons: Inconsistent accuracy, occasional hallucinations.
* Use: Sandbox code sketches or exploratory tasks.

===== Claude Opus 4.1 / Thinking =====
* Pros: Exceptional long-context comprehension, strong safety and reasoning discipline.
* Cons: Very slow, high credit cost.
* Use: Large-file reasoning, dependency mapping, or multi-repo audits.

Claude Sonnet 4.5 / Thinking
* Pros: Improved speed-to-accuracy ratio over Opus. Handles multi-file code contexts well.
* Cons: Slightly verbose; may under-specify low-level code.
* Use: Design discussions, complex refactors needing explanation.

Claude Haiku 4.5
* Pros: Very fast, low-credit.
* Cons: Simplified reasoning, weaker on subtle logic.
* Use: Quick code edits, batch comment generation.

Claude 3.7 Sonnet / Thinking and Claude Sonnet 4 / Thinking
* Pros: Balanced between Haiku and Opus. Good context size.
* Cons: Slightly older reasoning stack.
* Use: General code documentation, bug reproduction analysis.

Claude 3.5 Sonnet / Claude 4 Opus (BYOK)
* BYOK indicates “Bring Your Own Key,” unavailable under your Pro plan.

===== SWE-1 / SWE-1.5 =====
* Pros: Fine-tuned specifically for software engineering (Windsurf-native). Excellent at file grouping, dependency awareness, and commit structure.
* Cons: Limited creative language ability; narrow code-domain coverage outside mainstream languages.
* Use: End-to-end PR generation, repo diff analysis, structured refactoring.

Gemini 2.5 Pro
* Pros: Strong reasoning in web and Python environments, integrated tool reasoning.
* Cons: Context truncation at long inputs.
* Use: Web or API-driven code integration, especially for mixed content (e.g., Python + JSON pipelines).

xAI Grok Code Fast
* Pros: Fast responses, good JavaScript/TypeScript support.
* Cons: Shorter context, inconsistent language reasoning.
* Use: Front-end or lightweight script generation.

Kimi K2
* Pros: Efficient multilingual code understanding.
* Cons: Limited context size, weaker API understanding.
* Use: Small logic units or translation between languages.

Qwen3-Coder / Fast
* Pros: Excellent for Python, Java, and C++. Efficient low-cost coder.
* Cons: Moderate reasoning; struggles on high-level design.
* Use: Quick code writing, automated test generation.

o3 / o3 (high reasoning)
* Pros: Logical rigor, concise output.
* Cons: Slightly mechanical phrasing, lower fluency in non-code tasks.
* Use: Formal logic, algorithm derivation, math-driven code.

DeepSeek-V3-0324 / R1
* Pros: Compact, efficient, low credit; handles tabular data well.
* Cons: Weak abstraction capability.
* Use: Data cleaning, simple code automation.

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Would you like me to rank them specifically for Windsurf’s Cascade coding agent workflows (e.g., file refactoring, code commenting, dependency tracing)? That would refine the practical guidance further.