GPT-6.1 Terra vs Llama Guard 4 12B
Pick up to 3 models · pricing, context and capabilities · simulate your product cost
Data updated on November 14, 2026· 230 models
GPT-6.1 Terra is the mid-tier model in OpenAI's GPT-6.1 series, priced below GPT-6.1 Sol.
- Reasoning estimated
- ▲
- Speed estimated
- Input
- Output
- Context
- ▲1.1 M tokens
- Max output
- ▲128 K
- Input, $ per 1M tokens
- $1.00
- Output, $ per 1M tokens
- $5.00
- Cache read, $ per 1M
- $0.050
- Batch (input / output)
- $0.500 / $2.50
- Tool calling
- Yes
- Released
- ▲10/26/2026
- Knowledge cutoff
- 2026-06-01
- API id
- openai/gpt-6.1-terra
Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification.
- Reasoning estimated
- Speed estimated
- ▲
- Input
- Output
- Context
- 164 K tokens
- Max output
- 16 K
- Input, $ per 1M tokens
- ▲$0.180
- Output, $ per 1M tokens
- ▲$0.180
- Cache read, $ per 1M
- —
- Batch (input / output)
- —
- Tool calling
- No
- Released
- 04/30/2025
- Knowledge cutoff
- —
- API id
- meta-llama/llama-guard-4-12b
Which is the better API choice: GPT-6.1 Terra vs Llama Guard 4 12B?
- Llama Guard 4 12B: cheapest input (82% less than GPT-6.1 Terra)
- Llama Guard 4 12B: cheapest output
- GPT-6.1 Terra: largest context (1.1 M)
- GPT-6.1 Terra: the newest (10/26/2026)
- GPT-6.1 Terra: most reasoning (estimated)
- Llama Guard 4 12B: the fastest (estimated)
Llama Guard 4 12B costs 82% less on input and 96% less on output than GPT-6.1 Terra ($0.180 / $0.180 versus $1.00 / $5.00 per million tokens). GPT-6.1 Terra accepts more context (1.1 M). On capabilities, GPT-6.1 Terra has a reasoning mode. GPT-6.1 Terra offers 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 Llama Guard 4 12B you save $31.58 a month versus GPT-6.1 Terra (90% less).
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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)
- 1Claude Haiku 5.5 Anthropic$0.008
- 2Llama Guard 4 12B Meta$0.014
- 3GPT-6.1 Terra OpenAI$0.076
- 4Claude Sonnet 5.5 Anthropic$0.152
- 5Claude Opus 5.5 Anthropic$0.304
- 6Claude Opus 5 Anthropic$0.380
- 7Claude Fable 5.2 Anthropic$0.608
- 8Claude Fable 5.1 Anthropic$0.760
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See allFrequently asked questions
Which is the better API choice: GPT-6.1 Terra vs Llama Guard 4 12B?
Llama Guard 4 12B costs 82% less on input and 96% less on output than GPT-6.1 Terra ($0.180 / $0.180 versus $1.00 / $5.00 per million tokens). GPT-6.1 Terra accepts more context (1.1 M). On capabilities, GPT-6.1 Terra has a reasoning mode. GPT-6.1 Terra offers a batch tier at half price for jobs that do not need an immediate answer.
Which is cheaper: GPT-6.1 Terra and Llama Guard 4 12B?
Llama Guard 4 12B is cheaper: $0.180 per million input tokens and $0.180 per million output tokens, versus $1.00 / $5.00 for GPT-6.1 Terra.
Which has more context: GPT-6.1 Terra and Llama Guard 4 12B?
GPT-6.1 Terra accepts 1.1 M tokens of context; Llama Guard 4 12B accepts 164 K.
Which is newer: GPT-6.1 Terra and Llama Guard 4 12B?
GPT-6.1 Terra was released on 10/26/2026; Llama Guard 4 12B on 04/30/2025.
What would 10,000 requests a month cost with GPT-6.1 Terra and Llama Guard 4 12B?
With 1,500 input and 400 output tokens per request: GPT-6.1 Terra: $35.00; Llama Guard 4 12B: $3.42 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.