GPT-4 vs GPT-5.6 Terra
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GPT-4 | GPT-5.6 Terra |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input Price (1M) | $30.00 | $2.00 |
| Output Price (1M) | $60.00 | $12.00 |
| Context Window | 8,192 | 1,000,000 |
Verdict
GPT-4 costs $30.00 per 1M input tokens and $60.00 per 1M output tokens. GPT-5.6 Terra costs $2.00 per 1M input tokens and $12.00 per 1M output tokens. GPT-5.6 Terra is 93% cheaper on input tokens than GPT-4. For output tokens, GPT-5.6 Terra is the more affordable option at $12.00/1M vs $60.00.
On context window, GPT-5.6 Terra supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GPT-4
- ✓ You are already integrated with OpenAI
When to choose GPT-5.6 Terra
- ✓ You need the lowest input token cost ($ 2.00/1M)
- ✓ Your workload is output-heavy — GPT-5.6 Terra generates text cheaper
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is GPT-4 cheaper than GPT-5.6 Terra? ▼
GPT-5.6 Terra is cheaper on input tokens at $2.00/1M vs $30.00/1M for GPT-4 — a 93% saving.
What is the context window of GPT-4 vs GPT-5.6 Terra? ▼
GPT-4 has a 8,192-token context window. GPT-5.6 Terra has a 1,000,000-token context window. GPT-5.6 Terra supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GPT-4 or GPT-5.6 Terra? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GPT-5.6 Terra is the cheaper option. For maximum context length, GPT-5.6 Terra supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.