Model Cost Profile

Deep Cogito: Cogito v2.1 671B

Developer: deepcogito

Pricing updated Mar 11, 2026

Input rank: #254Output rank: #193

Live Pricing

Input: $1.25

Output: $1.25

Pricing via OpenRouter API ยท Last synced Mar 11, 2026

Deep Cogito: Cogito v2.1 671B, developed by deepcogito, offers a substantial context window of 128,000 tokens, making it suitable for applications requiring extensive text analysis, such as legal document review or large-scale content generation. With a competitive pricing structure of $1.25 per million tokens for both input and output, teams can effectively manage costs while leveraging the model for complex tasks like conversational AI or data-driven insights. This model's capabilities enable organizations to enhance productivity and streamline workflows, particularly in industries that rely on processing large volumes of text.

๐Ÿ“‹ Structured Output๐Ÿง  Reasoning

Context Window

128,000

Tokens

Input Price / 1M

$1.25

Prompt tokens

Output Price / 1M

$1.25

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Deep Cogito: Cogito v2.1 671B Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$1.25$1.25$1.25Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$1.25

Current Output / 1M

$1.25

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FAQ

Common pricing and benchmark questions for Deep Cogito: Cogito v2.1 671B.

How much does Deep Cogito: Cogito v2.1 671B cost per 1M input tokens?

Deep Cogito: Cogito v2.1 671B input pricing is $1.25 per 1M tokens based on the latest synced provider data.

How much does Deep Cogito: Cogito v2.1 671B cost per 1M output tokens?

Deep Cogito: Cogito v2.1 671B output pricing is $1.25 per 1M tokens based on the latest synced provider data.

What context window does Deep Cogito: Cogito v2.1 671B support?

Deep Cogito: Cogito v2.1 671B supports a context window of 128,000 tokens.

How can I compare Deep Cogito: Cogito v2.1 671B 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.