GPT-5.2 vs LLaMA 3 70B
Compare pricing, context windows, and strengths for GPT-5.2 by OpenAI and LLaMA 3 70B by Meta - and see how to put either to work in Appaca.
GPT-5.2
Previous frontier model for complex professional work with configurable reasoning effort.
View GPT-5.2GPT-5.2 vs LLaMA 3 70B at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.2 | LLaMA 3 70B |
|---|---|---|
| Provider | OpenAI | Meta |
| Model type | Text | Text |
| Context window | 400K tokens | 8.2K tokens |
| Input price | $1.75 / 1M tokens | - |
| Output price | $14 / 1M tokens | - |
| Status | Superseded by GPT-5.4 | Current |
How GPT-5.2 and LLaMA 3 70B differ
What the numbers mean in practice when choosing between GPT-5.2 and LLaMA 3 70B.
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GPT-5.2's 400K tokens context window is roughly 48.8x larger than LLaMA 3 70B's 8.2K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
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GPT-5.2 has been superseded by GPT-5.4 - for new builds, consider the newer model first.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-5.2
1. Advanced Reasoning for Diverse Domains
- Built to tackle coding and agentic workflows across multiple industries, with configurable reasoning support.
2. Multi-Modal & Long-Form Capabilities
- Handles both text and image inputs, producing text output.
- Allows up to 128 k output tokens for lengthy responses.
3. Large Context & Updated Knowledge
- 400 k token context window accommodates extensive codebases or documents.
- Knowledge cut-off of Aug 31 2025 keeps it current with recent developments.
LLaMA 3 70B
LLaMA 3 70B is a powerful, large-scale open-source model that excels at a wide range of tasks, including nuanced content creation, code generation, and complex reasoning. Its open nature allows for fine-tuning and customization, making it a top choice for developers looking to build specialized applications.
Use GPT-5.2 or LLaMA 3 70B - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.2 or LLaMA 3 70B - 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-5.2 or LLaMA 3 70B. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.2, test the same tool on LLaMA 3 70B, 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-5.2 or LLaMA 3 70B - connected to the tools you already use.
Related comparisons
See how GPT-5.2 and LLaMA 3 70B stack up against other models in the directory.
FAQs
Pricing models differ: see the full GPT-5.2 and LLaMA 3 70B pages in the Appaca AI models directory for current pricing details.
GPT-5.2 has the larger context window at 400K tokens, compared to 8.2K tokens for LLaMA 3 70B. 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-5.2, test the same tool on LLaMA 3 70B, 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-5.2, LLaMA 3 70B, 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-5.2 or LLaMA 3 70B
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.