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Model comparison
OpenAI's GPT-5.4 against OpenAI's GPT-5.6 Terra: vendor list prices, limits, abilities and the Artificial Analysis indexes side by side - and what OpenSmartRoute does when both are available.
GPT-5.6 Terra lists at $4.50 per million tokens blended against $5.63 for GPT-5.4 - 1.3x less.
GPT-5.6 Terra scores 42 on the intelligence index against 39 - 3 points apart.
GPT-5.6 Terra scores 77 on the coding index against 71 - 6 points apart.
GPT-5.6 Terra was released about 4 months later.
Vendor list prices per million tokens and published limits; indexes are Artificial Analysis composites (0-100).
| Specification | GPT-5.4 | GPT-5.6 Terra |
|---|---|---|
| Input price / 1M tokens | $2.50 | $2.00 |
| Output price / 1M tokens | $15.0 | $12.0 |
| Blended (3 in : 1 out) | $5.63 | $4.50 |
| Cached input / 1M | $0.25 | $0.20 |
| Context window | 1.1M | 1.1M |
| Max output | 128K | 128K |
| Input | text, image, file | file, image, text |
| Output | text | text |
| Tool calls | ||
| Structured output | ||
| Reasoning | ||
| Open weights | ||
| Intelligence index | 39 | 42 |
| Coding index | 71 | 77 |
| Agentic index | - | 43 |
| Released | Mar 5, 2026 | Jul 9, 2026 |
| Available on this deployment |
List price times tokens for three typical workloads; your mix of input and output decides which model's pricing suits you.
| Workload | GPT-5.4 | GPT-5.6 Terra | Difference |
|---|---|---|---|
| Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations. | $125 | $100 | $25.00 less on GPT-5.6 Terra |
| Document summaries100M in, 5M out - long inputs, short answers. | $325 | $260 | $65.00 less on GPT-5.6 Terra |
| Coding assistant60M in, 20M out - a team's editor assistant, output-heavy. | $450 | $360 | $90.00 less on GPT-5.6 Terra |
GPT-5.6 Terra is both cheaper and stronger on the intelligence index, so with both in the catalogue the router sends it almost everything; GPT-5.4 earns a request only on something it alone offers - a longer context, a modality, a data boundary or a region your rules require.
# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry)
targets:
- { id: gpt-5.6-terra, kind: llm, metadata: { model: openai/gpt-5.6-terra } }
- { id: gpt-5.4, kind: llm, metadata: { model: openai/gpt-5.4 } }
# rules.yaml - the cheaper model by default, the stronger one when the request is hard
rules:
- name: simple-requests-stay-cheap
when: { max_complexity: 0.45 }
prefer: [gpt-5.6-terra]
weight: 0.8
- name: hard-requests-escalate
when: { min_complexity: 0.45 }
prefer: [gpt-5.4]
weight: 0.8Every OpenAI and OpenAI model, with prices, is on the vendor pages; the rankings show what the router actually picks.