LLM ComparisonGPT-4 TurboClaude 4.6 Opus

GPT-4 Turbo vs Claude 4.6 Opus

Compare GPT-4 Turbo and Claude 4.6 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-4 TurboClaude 4.6 Opus
ProviderOpenAIAnthropic
Model Typetexttext
Context Window128,000 tokens1,000,000 tokens
Input Cost
$10.00/ 1M tokens
$5.00/ 1M tokens
Output Cost
$30.00/ 1M tokens
$25.00/ 1M tokens

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Strengths & Best Use Cases

GPT-4 Turbo

OpenAI

1. Strong reasoning for its generation

  • Next-gen version of GPT-4 designed to be cheaper and faster than the original.
  • Good for analytical tasks, structured writing, coding guidance, and multi-step reasoning.

2. Image input support

  • Accepts images and provides text-only outputs.
  • Useful for OCR, visual Q&A, document extraction, UI analysis, and design interpretation.

3. Stable performance

  • Predictable model behavior suitable for legacy systems still built on GPT-4.
  • Works reliably for established pipelines and enterprise workloads.

4. Large 128K context window

  • Handles long documents, multi-file inputs, or extended conversational sessions.
  • Allows complex prompt chaining and large instruction sets.

5. Broad endpoint compatibility

  • Works with Chat Completions, Responses API, Realtime API, Assistants, Batch, Fine-tuning, Embeddings, and more.
  • Supports streaming and function calling.

6. Good choice for cost-controlled GPT-4-class workloads

  • Although older, still useful for teams who want GPT-4-level reasoning without upgrading immediately.
  • A midpoint between legacy GPT-4 and modern GPT-4o/5.1 models.

7. Text-only output simplifies downstream use

  • Ensures deterministic outputs for applications that need reliable text generation.
  • Good for RAG, data pipelines, automation tools, and enterprise systems.

8. Recommended migration path

  • OpenAI now recommends using GPT-4o or GPT-5.1 for improved speed, cost, reasoning, and multimodal capability.
  • GPT-4 Turbo remains available for backward compatibility and stability.

Claude 4.6 Opus

Anthropic

1. Anthropic's top model for coding and agents

  • Anthropic positions Opus 4.6 as its most intelligent model for building agents and coding.
  • It builds on Opus 4.5 with higher reliability and precision for professional software engineering, complex agentic workflows, and high-stakes enterprise tasks.

2. Strong frontier performance on real agent benchmarks

  • Anthropic reports state-of-the-art results across coding and agentic evaluations.
  • Public benchmark highlights include 65.4% on Terminal-Bench 2.0, 72.7% on OSWorld, and 90.2% on BigLaw Bench.

3. Best fit for long-horizon, high-context work

  • Supports up to a 1M token context window in beta and up to 128K output tokens.
  • Designed for long-running tasks that need sustained planning, careful debugging, code review, and strong context retention.

4. Advanced reasoning controls and workflow support

  • Supports adaptive thinking and the effort parameter, including the new max effort level.
  • Anthropic also introduced fast mode, compaction, and dynamic filtering with web search and web fetch for Opus 4.6-era agent workflows.

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