GPT-5.3 Codex vs Claude 4.5 Opus
Compare pricing, context windows, and strengths for GPT-5.3 Codex by OpenAI and Claude 4.5 Opus by Anthropic - and see how to put either to work in Appaca.
GPT-5.3 Codex
Most capable agentic coding model to date, optimized for long-horizon software engineering tasks with configurable reasoning and multimodal input.
View GPT-5.3 CodexClaude 4.5 Opus
Anthropic's November 2025 flagship model, combining maximum capability with practical performance for coding, agents, computer use, and enterprise workflows.
View Claude 4.5 OpusGPT-5.3 Codex vs Claude 4.5 Opus at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.3 Codex | Claude 4.5 Opus |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model type | Text | Text |
| Context window | 400K tokens | 200K tokens |
| Input price | $1.75 / 1M tokens | $5 / 1M tokens |
| Output price | $14 / 1M tokens | $25 / 1M tokens |
| Status | Current | Superseded by Claude 4.6 Opus |
How GPT-5.3 Codex and Claude 4.5 Opus differ
What the numbers mean in practice when choosing between GPT-5.3 Codex and Claude 4.5 Opus.
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GPT-5.3 Codex is 65% cheaper on input tokens ($1.75 vs $5 per million), which adds up quickly in document-heavy workloads.
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GPT-5.3 Codex is 44% cheaper on output tokens ($14 vs $25 per million) - the bigger factor for tools that generate long documents.
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GPT-5.3 Codex's 400K tokens context window is roughly 2x larger than Claude 4.5 Opus's 200K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
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Claude 4.5 Opus has been superseded by Claude 4.6 Opus - for new builds, consider the newer model first.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-5.3 Codex
1. Strongest Codex Model for Agentic Engineering
- OpenAI positions GPT-5.3 Codex as its most capable agentic coding model to date.
- Built for long-horizon software engineering tasks that require planning, iteration, and reliable code transformation across files.
2. Configurable Reasoning + Multimodal Input
- Supports configurable reasoning effort from low to xhigh so teams can trade off depth against latency.
- Accepts both text and image inputs while producing text output.
3. Large Context for Real Codebases
- 400 k token context window helps it work across larger repositories, implementation plans, and supporting documentation.
- Allows up to 128 k output tokens for longer code generations, patches, and technical write-ups.
4. Current Knowledge for Modern Dev Workflows
- Knowledge cut-off of Aug 31 2025 keeps it aligned with newer frameworks, libraries, and tooling.
- Supports streaming, function calling, and structured outputs for agent-style coding workflows.
Claude 4.5 Opus
1. Maximum capability with more practical pricing
- Anthropic introduced Opus 4.5 as its most intelligent model, combining maximum capability with practical performance.
- It was positioned as the best model in the world for coding, agents, and computer use at launch, with pricing reduced to $5/M input and $25/M output.
2. Step-change gains for coding and advanced agent work
- Anthropic describes Opus 4.5 as state-of-the-art on real-world software engineering tests.
- It also improved everyday knowledge-work tasks like deep research, slides, and spreadsheets while staying strong on long-horizon agent workflows.
3. Better control over reasoning depth
- Opus 4.5 introduced the
effortparameter, letting developers trade off response thoroughness against token efficiency. - This made it easier to use one flagship model across both high-depth analysis and more cost-sensitive production workloads.
4. Stronger computer use and continuity
- Added enhanced computer use with a zoom action for inspecting detailed screen regions.
- Preserves prior thinking blocks across turns, helping the model maintain reasoning continuity in extended multi-step tasks.
Use GPT-5.3 Codex or Claude 4.5 Opus - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.3 Codex or Claude 4.5 Opus - 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-5.3 Codex or Claude 4.5 Opus. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.3 Codex, test the same tool on Claude 4.5 Opus, 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-5.3 Codex or Claude 4.5 Opus - connected to the tools you already use.







Related comparisons
See how GPT-5.3 Codex and Claude 4.5 Opus stack up against other models in the directory.
FAQs
GPT-5.3 Codex is generally cheaper: $1.75 input / $14 output per million tokens, versus $5 / $25 for Claude 4.5 Opus. Actual cost depends on how many tokens your workload reads and writes.
GPT-5.3 Codex has the larger context window at 400K tokens, compared to 200K tokens for Claude 4.5 Opus. 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-5.3 Codex, test the same tool on Claude 4.5 Opus, 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-5.3 Codex, Claude 4.5 Opus, 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-5.3 Codex or Claude 4.5 Opus
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.