Model Cost Profile

AllenAI: Olmo 3.1 32B Instruct

Developer: allenai

Pricing updated Mar 10, 2026

Input rank: #132Output rank: #132

Live Pricing

Input: $0.2000

Output: $0.6000

Pricing via OpenRouter API ยท Last synced Mar 10, 2026

AllenAI's Olmo 3.1 32B Instruct model offers a substantial context window of 65,536 tokens, making it suitable for applications requiring extensive text comprehension, such as legal document analysis and long-form content generation. Teams leveraging this model can expect input costs of $0.20 per 1 million tokens and output costs of $0.60 per 1 million tokens, allowing for scalable budgeting based on usage patterns. This pricing structure is particularly advantageous for organizations that need to process large volumes of data while maintaining high-quality outputs.

๐Ÿ”ง Tool Calling๐Ÿ“‹ Structured Output

Context Window

65,536

Tokens

Input Price / 1M

$0.2000

Prompt tokens

Output Price / 1M

$0.6000

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

AllenAI: Olmo 3.1 32B Instruct Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 10
$0.2000$0.4000$0.6000Mar 7Mar 8Mar 9Mar 10

Current Input / 1M

$0.2000

Current Output / 1M

$0.6000

Cheaper Alternatives to Compare

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FAQ

Common pricing and benchmark questions for AllenAI: Olmo 3.1 32B Instruct.

How much does AllenAI: Olmo 3.1 32B Instruct cost per 1M input tokens?

AllenAI: Olmo 3.1 32B Instruct input pricing is $0.2000 per 1M tokens based on the latest synced provider data.

How much does AllenAI: Olmo 3.1 32B Instruct cost per 1M output tokens?

AllenAI: Olmo 3.1 32B Instruct output pricing is $0.6000 per 1M tokens based on the latest synced provider data.

What context window does AllenAI: Olmo 3.1 32B Instruct support?

AllenAI: Olmo 3.1 32B Instruct supports a context window of 65,536 tokens.

How can I compare AllenAI: Olmo 3.1 32B Instruct with cheaper alternatives?

Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.