Cost and performance comparison
GPT-5.6 Terra vs GPT-5.2
Model AOpenAI
GPT-5.6 Terra
- Cost / 1M Tokens
- $5.00
- 70% in · 30% out mix
- Value Index (score÷cost)
- 18.8
- Higher = better value
- Speed
- 86/100
- Context
- 1.1M
- Tier
- Smart Tier
List price from the OpenAI pricing page, verified October 12, 2026.
Check the sourceModel BOpenAI
GPT-5.2
- Cost / 1M Tokens
- $5.43
- 70% in · 30% out mix
- Value Index (score÷cost)
- 17.7
- Higher = better value
- Speed
- 85/100
- Context
- 400K
- Tier
- Smart Tier
List price from the OpenAI pricing page, verified October 12, 2026.
Check the sourceIn-depth analysis
GPT-5.6 Terra vs GPT-5.2: Detailed Comparison
GPT-5.6 Terra is OpenAI's mid-range-tier language model with a 1.1M-token context window, excelling at reasoning. GPT-5.2 from OpenAI is a mid-range-tier model supporting 400K tokens in context, with standout performance in reasoning.
Price is not the deciding factor here. For the same text, GPT-5.6 Terra and GPT-5.2 land within 8% of each other, which is inside the margin your own input/output ratio will move anyway. Pick on capability, context, or latency instead — the monthly bill will look much the same either way. GPT-5.6 Terra is priced at $2.00/M input tokens and $12.00/M output tokens. GPT-5.2 costs $1.75/M input and $14.00/M output.
On iOPTERA's editorial scores, GPT-5.2 leads with 94/100 for coding and 96/100 for reasoning, against GPT-5.6 Terra's 93/100 and 94/100.
Capability breakdown
Across the five core benchmark categories, here is how GPT-5.6 Terra and GPT-5.2 stack up head to head:
Best model by task
- coding: GPT-5.2 wins with 94/100
- reasoning: GPT-5.2 wins with 96/100
- data extraction: GPT-5.6 Terra wins with 93/100
- creative tasks: GPT-5.2 wins with 95/100
- vision/multimodal: GPT-5.6 Terra wins with 93/100
Estimated monthly cost at scale
For 10M + 2M tokens of text a month (counted the way OpenAI's tokenizer counts), GPT-5.6 Terra runs about $44.00 while GPT-5.2 runs about $45.50 — GPT-5.6 Terra saves roughly $1.50 (3%) every month.
What actually decides it
Both models come from OpenAI, so they share a tokenizer, an API surface, and a billing account. Switching between them is a model-string change and nothing else — no new SDK, no re-tokenizing your prompts to re-estimate cost, no second vendor to onboard. That makes routing between them far cheaper to implement than a cross-vendor split.
These are the same lab's model at the same tier, 7 months apart — so this is an upgrade question, not a choice between alternatives. GPT-5.6 Terra is the current entry; GPT-5.2 is here because plenty of production traffic still runs on it. If you are starting something new there is little reason to pick the older one, and if you are already on it the question is whether the migration cost is worth the gain.
GPT-5.6 Terra carries the larger context window at 1.1M tokens versus 400K for GPT-5.2. The gap is real but not decisive — it matters if your prompts routinely run long, and is irrelevant if they sit where most production prompts sit, well under 100K. Bear in mind that filling a large window is also what makes a request expensive.
Throughput is close enough to ignore — 86/100 versus 85/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.
With prices this close (8% apart), pick on fit rather than cost. GPT-5.2 holds the benchmark edge; weigh that against where each one is weakest — creative tasks and data extraction respectively — and use the calculator above with your own token mix.
What you actually pay
The list price is only the start. Prompt caching, batch processing and long prompts change the bill, and each provider sets them differently. Prices per 1M tokens.
| Pricing term | GPT-5.6 Terra | GPT-5.2 |
|---|---|---|
| List price (input / output) | $2.00 / $12.00 | $1.75 / $14.00 |
| Cached input | $0.2010% of the input price | $0.17510% of the input price |
| Batch API | 50% off input and output | 50% off input and output |
| Long prompts | Over 272K tokens: $4.00 / $18.00 | — |
| Input with 80% cache hits | $0.56 | $0.49 |
With 80% of input served from the cache, GPT-5.2 costs 13% less than GPT-5.6 Terra for the same input text, counting each model's tokenizer.
The last row assumes 80% of input tokens are read from the cache, as in a chat app that re-sends a long system prompt or RAG over the same documents. Cache-write and storage charges are not included.
Checked on October 8, 2026 against the pricing pages of OpenAI.
Capability scores
iOPTERA editorial scores across 5 categories — informed by public benchmarks, not measured by us
Coding
Reasoning
Extraction
Creative
Vision
Speed Score
Context Window
What Is a Token?
Models don't read words — they process tokens.
A token is roughly 4 characters of English text (~¾ of a word). Your API bill is priced per million tokens — understanding this directly reduces your costs.
Short phrase
"Hello, world!"
- GPT-5.6 Terra
- $0.80
- GPT-5.2
- $0.70
Business email
One typical email (~200 words)
- GPT-5.6 Terra
- $54.00
- GPT-5.2
- $47.25
Code file
50-line Python script
- GPT-5.6 Terra
- $80.00
- GPT-5.2
- $70.00
Prices shown are for 100,000 runs of each workload — one run costs a fraction of a cent on both GPT-5.6 Terra and GPT-5.2, so the number only becomes meaningful at production volume. Input tokens only; add your output volume in the calculator below.
How to check your token usage
response.usage.total_tokensEvery API response includes a usage object. Sum total_tokens across all calls to get your monthly figure, then use the calculator below.
Your Cost Calculator
Enter your actual monthly token usage to see real savings
Quick Presets
GPT-5.6 Terra
$150.00/mo
$1,800.00/yr
GPT-5.2
$162.75/mo
$1,953.00/yr
Annual Savings
$153.00 saved per year
GPT-5.6 Terra cheaper · $12.75/mo
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