GPT-5 vs Claude 4.8 Opus
Compare pricing, context windows, and strengths for GPT-5 by OpenAI and Claude 4.8 Opus by Anthropic - and see how to put either to work in Appaca.
GPT-5
A high-reasoning model for coding and agentic tasks with configurable reasoning effort, supporting text + image input and large context windows.
View GPT-5Claude 4.8 Opus
Anthropic's flagship model for coding and agents, building on Opus 4.7 with stronger reliability, a cheaper fast mode, and gains across coding, computer use, and professional work.
View Claude 4.8 OpusGPT-5 vs Claude 4.8 Opus at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5 | Claude 4.8 Opus |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model type | Text | Text |
| Context window | 400K tokens | 1M tokens |
| Input price | $1.25 / 1M tokens | $5 / 1M tokens |
| Output price | $10 / 1M tokens | $25 / 1M tokens |
| Status | Superseded by GPT-5.1 | Current |
How GPT-5 and Claude 4.8 Opus differ
What the numbers mean in practice when choosing between GPT-5 and Claude 4.8 Opus.
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GPT-5 is 75% cheaper on input tokens ($1.25 vs $5 per million), which adds up quickly in document-heavy workloads.
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GPT-5 is 60% cheaper on output tokens ($10 vs $25 per million) - the bigger factor for tools that generate long documents.
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Claude 4.8 Opus's 1M tokens context window is roughly 2.5x larger than GPT-5's 400K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
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GPT-5 has been superseded by GPT-5.1 - for new builds, consider the newer model first.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-5
1. High reasoning capability
- Designed for intelligent reasoning across complex domains.
- Supports reasoning tokens and adjustable reasoning effort.
2. Strong coding and agentic performance
- Optimized for multi-step coding tasks, tool-use chains, and agent workflows.
- Handles complex logic, planning, and structured problem solving reliably.
3. Multimodal input
- Accepts text + image as input.
- Produces text outputs with strong instruction following.
4. Extensive tool support
- Works with Web Search, File Search, Image Generation (as a tool), Code Interpreter, MCP, and more.
- Integrated across Chat Completions, Responses API, Realtime, Assistants, Batch, Embeddings, etc.
Claude 4.8 Opus
1. Modest but tangible gains across the board
- 69.2% on SWE-bench Pro (+4.9 points over Opus 4.7's 64.3%), 88.6% on SWE-bench Verified, and a 1,890 Elo on GDPval-AA - about 121 Elo ahead of GPT-5.5.
- Anthropic frames it as an incremental refinement of Opus 4.7 rather than a step-change release.
2. The most reliable agent model Anthropic has shipped
- The only model to complete every case end-to-end on Anthropic's internal Super-Agent benchmark, beating prior Opus models and GPT-5.5 at parity on cost.
- Leads CursorBench across every effort level with more efficient tool calling - fewer steps for the same intelligence.
- 84% on Online-Mind2Web and stronger OSWorld-Verified scores make it the strongest computer-use and browser-agent model Anthropic has tested.
3. New highs for professional and legal work
- Highest score ever recorded on Anthropic's Legal Agent Benchmark, and the first model to break 10% on its all-pass standard.
- Roughly a 4x improvement in honesty and calibrated uncertainty versus Opus 4.7 on Anthropic's evaluations.
4. Cheaper, faster controls
- Standard pricing holds at $5/M input and $25/M output, unchanged from Opus 4.7.
- Fast mode now runs at 2.5x speed for $10/M input and $50/M output - about a third of what fast mode cost on prior Opus releases.
- A new effort dial gives finer control over how hard the model works before answering.
5. Long-horizon agent workflows
- 1M token context window in beta and up to 128K output tokens.
- Introduces Dynamic Workflows (research preview) in Claude Code - Opus can write its own orchestration script and run up to 16 concurrent / 1,000 total subagents in a single session.
Use GPT-5 or Claude 4.8 Opus - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5 or Claude 4.8 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 or Claude 4.8 Opus. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5, test the same tool on Claude 4.8 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 or Claude 4.8 Opus - connected to the tools you already use.
Related comparisons
See how GPT-5 and Claude 4.8 Opus stack up against other models in the directory.
FAQs
GPT-5 is generally cheaper: $1.25 input / $10 output per million tokens, versus $5 / $25 for Claude 4.8 Opus. Actual cost depends on how many tokens your workload reads and writes.
Claude 4.8 Opus has the larger context window at 1M tokens, compared to 400K tokens for GPT-5. 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, test the same tool on Claude 4.8 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, Claude 4.8 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 or Claude 4.8 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.