GPT-5.6 Sol vs GPT-5.6 Terra Pro
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on September 30, 2026· 217 models
GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 series.
- Reasoning estimated
- Speed estimated
- ▲
- Input
- Output
- Context
- 1.1 M tokens
- Max output
- 128 K
- Input, $ per 1M tokens
- $2.00
- Output, $ per 1M tokens
- ▲$10.00
- Cache read, $ per 1M
- $0.200
- Batch (input / output)
- $1.00 / $5.00
- Tool calling
- Yes
- Released
- 07/09/2026
- Knowledge cutoff
- 2026-02-16
- API id
- openai/gpt-5.6-sol
GPT-5.6 Terra Pro is the same underlying model as GPT-5.6 Terra, served with reasoning.mode set to pro for higher-quality responses on complex tasks.
- Reasoning estimated
- ▲
- Speed estimated
- Input
- Output
- Context
- 1.1 M tokens
- Max output
- 128 K
- Input, $ per 1M tokens
- $2.00
- Output, $ per 1M tokens
- $12.00
- Cache read, $ per 1M
- $0.200
- Batch (input / output)
- $1.00 / $6.00
- Tool calling
- Yes
- Released
- 07/09/2026
- Knowledge cutoff
- 2026-02-16
- API id
- openai/gpt-5.6-terra-pro
Which is the better API choice: GPT-5.6 Sol vs GPT-5.6 Terra Pro?
- GPT-5.6 Sol: cheapest output
- GPT-5.6 Terra Pro: most reasoning (estimated)
- GPT-5.6 Sol: the fastest (estimated)
GPT-5.6 Sol costs 0% less on input and 17% less on output than GPT-5.6 Terra Pro ($2.00 / $10.00 versus $2.00 / $12.00 per million tokens). All accept 1.1 M tokens of context. GPT-5.6 Sol and GPT-5.6 Terra Pro offer a batch tier at half price for jobs that do not need an immediate answer.
What would your product cost?
Estimate the monthly cost with your app's real volume. List prices, no cache or batch discounts.
With GPT-5.6 Sol you save $8.00 a month versus GPT-5.6 Terra Pro (10% less).
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- 3Qwen3.7 Flash Qwen$0.97
- 4DeepSeek V4 Flash 0731 DeepSeek$1.55
- 5Ministral 3 3B 2512 Mistral$1.90
- 6Qwen3.5-Flash Qwen$2.02
Paste your prompt: tokens and cost per model
Rough estimate (about 4 characters per token). Nothing is sent to any server.
Cost of sending it 1,000 times (input only)
- 1GPT-5.6 Sol OpenAI$0.152
- 2GPT-5.6 Terra Pro OpenAI$0.152
- 3Claude Sonnet 5.5 Anthropic$0.152
- 4Claude Sonnet 5 Anthropic$0.152
- 5Claude Opus 5.5 Anthropic$0.304
- 6Claude Opus 5 Anthropic$0.380
- 7Claude Fable 5.1 Anthropic$0.760
- 8Claude Fable 5 Anthropic$0.760
Popular comparisons
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- GPT-6.1 Sol vs Gemini 3.8 Flash
- GPT-6.1 Sol vs DeepSeek V4.1 Flash
- GPT-6.1 Sol vs Grok 4.7
- Gemini 3.8 Flash vs DeepSeek V4.1 Flash
- Gemini 3.8 Flash vs Grok 4.7
- DeepSeek V4.1 Flash vs Grok 4.7
Frequently asked questions
Which is the better API choice: GPT-5.6 Sol vs GPT-5.6 Terra Pro?
GPT-5.6 Sol costs 0% less on input and 17% less on output than GPT-5.6 Terra Pro ($2.00 / $10.00 versus $2.00 / $12.00 per million tokens). All accept 1.1 M tokens of context. GPT-5.6 Sol and GPT-5.6 Terra Pro offer a batch tier at half price for jobs that do not need an immediate answer.
Which is cheaper: GPT-5.6 Sol and GPT-5.6 Terra Pro?
GPT-5.6 Sol is cheaper: $2.00 per million input tokens and $10.00 per million output tokens, versus $2.00 / $12.00 for GPT-5.6 Terra Pro.
Which has more context: GPT-5.6 Sol and GPT-5.6 Terra Pro?
GPT-5.6 Sol and GPT-5.6 Terra Pro accept the same context: 1.1 M tokens.
What would 10,000 requests a month cost with GPT-5.6 Sol and GPT-5.6 Terra Pro?
With 1,500 input and 400 output tokens per request: GPT-5.6 Sol: $70.00; GPT-5.6 Terra Pro: $78.00 a month, at list price.
Where do the prices come from and how often are they updated?
From the public catalogs of OpenRouter, models.dev and LiteLLM, which publish each provider's list prices. They sync once a day and the last update date is shown above the comparison.
What does price per million tokens mean?
It is what the provider charges per million tokens you send (input) or the model generates (output). A token is roughly 4 characters. Output almost always costs more than input.
Sources: OpenRouter, models.dev and LiteLLM. Prices in USD per million tokens, list price, no volume discounts. Prompt tokens are an estimate; each provider's tokenizer may differ.