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SubQ Snap
Long-context decision model for agent workflows
1 follower
Long-context decision model for agent workflows
1 follower
SubQ Snap is a long-context decision model for AI agents. Instead of writing text, it picks from a set of allowed answers, like which file to read, which tool to call next, or whether a test passed. It takes up to 384K tokens of text and images in one call and handles 100K-token requests in under a second. Costs $0.05 per million input tokens, with output free. In Public Preview, capacity is limited.
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