GPT-4o vs Claude 3.5 Sonnet
Compare pricing, context windows, and strengths for GPT-4o by OpenAI and Claude 3.5 Sonnet by Anthropic - and see how to put either to work in Appaca.
GPT-4o
A versatile, high-intelligence flagship GPT model that handles text and image inputs and produces fast, high-quality text outputs for a wide range of tasks.
View GPT-4oClaude 3.5 Sonnet
A fast, mid-tier model offering top-tier intelligence, strong reasoning, and advanced coding/vision capabilities at low cost.
View Claude 3.5 SonnetGPT-4o vs Claude 3.5 Sonnet at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-4o | Claude 3.5 Sonnet |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model type | Text | Text |
| Context window | 128K tokens | 200K tokens |
| Input price | $2.5 / 1M tokens | $3 / 1M tokens |
| Output price | $10 / 1M tokens | $15 / 1M tokens |
| Status | Current | Superseded by Claude 4.5 Sonnet |
How GPT-4o and Claude 3.5 Sonnet differ
What the numbers mean in practice when choosing between GPT-4o and Claude 3.5 Sonnet.
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GPT-4o is 17% cheaper on input tokens ($2.5 vs $3 per million), which adds up quickly in document-heavy workloads.
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GPT-4o is 33% cheaper on output tokens ($10 vs $15 per million) - the bigger factor for tools that generate long documents.
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Claude 3.5 Sonnet's 200K tokens context window is roughly 1.6x larger than GPT-4o's 128K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
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Claude 3.5 Sonnet has been superseded by Claude 4.5 Sonnet - for new builds, consider the newer model first.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-4o
1. High-intelligence, general-purpose model
- Strong reasoning, creativity, summarization, and problem-solving.
- Great balance of speed, accuracy, and cost.
2. Multimodal input support
- Accepts text + image inputs for visual reasoning, extraction, or description.
- Output is text only, making it predictable for production.
3. Excellent for structured and unstructured tasks
- Performs well on Q&A, writing, analysis, classification, chat, and planning.
- Supports Structured Outputs, making it suitable for deterministic workflows.
4. Strong tool-use capabilities
- Supports function calling, API orchestration, and tool-augmented workflows.
- Integrates well with assistants, batch operations, and automation pipelines.
5. Large context for complex tasks
- 128K context allows multi-document reasoning, multi-step conversations, and large input payloads.
6. Production-ready reliability
- Stable outputs, predictable behaviors, and broad modality coverage.
- Supported across all major API endpoints.
7. Lower latency than o-series reasoning models
- Faster responses due to no dedicated reasoning step.
- Ideal for interactive or near-real-time applications.
8. Fine-tuning and distillation supported
- Enables specialization for domain-specific tasks.
- Distillation helps create smaller, efficient custom models.
Claude 3.5 Sonnet
1. Intelligence & Reasoning
- Outperforms previous Claude models and competitor LLMs across major benchmarks.
- Excels in graduate-level reasoning (GPQA), knowledge tasks (MMLU), and coding (HumanEval).
- Handles nuance, humor, and complex instructions with human-like clarity.
2. Speed & Efficiency
- Runs 2x faster than Claude 3 Opus, making it ideal for real-time and high-volume workflows.
- Cost-effective pricing: $3/M input tokens and $15/M output tokens.
- Supports a 200K token context window, enabling rich, long-form reasoning.
3. Coding Capabilities
- Solves significantly more coding and bug-fix tasks (64% vs Opus's 38% in internal evaluations).
- Can autonomously write, edit, and execute code when tool use is enabled.
- Strong at translating and modernizing legacy codebases.
4. Vision Strength
- Best vision model in the Claude family, surpassing Opus on vision benchmarks.
- Excellent at interpreting charts, graphs, and imperfect images.
- Reliable text extraction from low-quality visuals for retail, logistics, finance, etc.
5. Agentic Workflows
- Highly capable for multi-step task orchestration.
- Performs well as the engine for agents requiring reasoning, planning, and tool-calling abilities.
6. Content Quality
- Produces natural, relatable writing with improved tone, style, and context awareness.
- Strong at long-form content creation and editing.
7. Safety & Reliability
- Rated ASL-2, meeting Anthropic's safety standards.
- Undergoes extensive red-teaming and external evaluation (UK AISI & US AISI).
- Not trained on user data without explicit permission.
Use GPT-4o or Claude 3.5 Sonnet - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-4o or Claude 3.5 Sonnet - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need and it builds a working app powered by GPT-4o or Claude 3.5 Sonnet. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-4o, test the same tool on Claude 3.5 Sonnet, and keep whichever performs better - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs and it builds a working app powered by GPT-4o or Claude 3.5 Sonnet - connected to the tools you already use.
Related comparisons
See how GPT-4o and Claude 3.5 Sonnet stack up against other models in the directory.
FAQs
GPT-4o is generally cheaper: $2.5 input / $10 output per million tokens, versus $3 / $15 for Claude 3.5 Sonnet. Actual cost depends on how many tokens your workload reads and writes.
Claude 3.5 Sonnet has the larger context window at 200K tokens, compared to 128K tokens for GPT-4o. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.
It depends on the job. Compare the pricing, context window, and strengths above against your workload - and remember the choice isn't permanent. In Appaca you can build a tool on GPT-4o, test the same tool on Claude 3.5 Sonnet, and switch at any time without rebuilding anything.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by GPT-4o, Claude 3.5 Sonnet, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build AI tools with GPT-4o or Claude 3.5 Sonnet
Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.