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LLM ComparisonGPT-4.1o1-pro

GPT-4.1 vs o1-pro

Compare GPT-4.1 and o1-pro. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-4.1o1-pro
ProviderOpenAIOpenAI
Model Typetexttext
Context Window1,047,576 tokens200,000 tokens
Input Cost
$2.00/ 1M tokens
$150.00/ 1M tokens
Output Cost
$8.00/ 1M tokens
$600.00/ 1M tokens

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Strengths & Best Use Cases

GPT-4.1

OpenAI

1. Smartest non-reasoning model

  • Highest intelligence among models without a reasoning step.
  • Great for tasks where speed + accuracy matter without deep chain-of-thought.

2. Excellent instruction following

  • Very strong at structured tasks, formatting, and precise execution.
  • Ideal for productized workflows and deterministic outputs.

3. Reliable tool calling

  • Works smoothly with Web Search, File Search, Image Generation, and Code Interpreter.
  • Supports MCP and advanced tool-enabled API flows.

4. Large 1M-token context window

  • Allows extremely long conversations, large documents, and multi-file use cases.
  • Handles context-heavy tasks without requiring chunking.

5. Low latency (no reasoning step)

  • Faster responses than GPT-5 family when reasoning mode isn't required.
  • More predictable timing for production use.

6. Multimodal input

  • Accepts text + image.
  • Output is text only.

7. Supports fine-tuning

  • Can be fine-tuned for specialized tasks.
  • Also supports distillation for smaller custom models.

o1-pro

OpenAI

1. Maximum-compute o-series model

  • Uses significantly more compute per query compared to o1.
  • Produces deeper, more reliable reasoning chains.
  • Best suited for high-stakes tasks that need correctness over speed.

2. Trained with reinforcement learning for deliberate thinking

  • Explicit "think-before-answer" architecture.
  • Excels at complex reasoning requiring multi-step analysis.

3. Very strong at math, science, coding, and technical proofs

  • Handles long derivations, algorithm design, and difficult logic problems.
  • Produces structured and explainable reasoning trails.

4. Great for multi-turn reasoning workflows

  • Responses API optimized: can think over multiple internal turns before responding.
  • Ideal for agentic reasoning pipelines.

5. Large context window

  • 200,000-token context for large documents, multi-file review, and long reasoning traces.

6. Multimodal input (text + image)

  • Can analyze images for mathematical diagrams, charts, handwritten content, UI layouts, etc.
  • Output is text only.

7. Consistency, reliability, and depth

  • Designed for situations where accuracy matters more than latency or cost.
  • Strong error-checking and self-correction abilities.

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