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jevIMAGE

SubQ Snap 决策模型对标 Jev

新 API 决策模型宣称 100K 上下文 660ms、Decision Index 61.7 高于 Jev 的 57.9,但不开源。

David Hendrickson
@TeksEdge18 天前收录原推发布于 2026.10.13
SubQ Snap 决策模型对标 Jev
David Hendrickson @TeksEdge原推发布于 2026.10.13
在 X 上打开原推

Saw this launch announcement and feel sorry for Jev. That's because a new AI model can read 100,000 tokens and make a decision in under 1 second. SubQ Snap launched today. It's a decision model built to ingest huge amounts of context and return structured choices/probabilities. According to SubQ ⚡ 32K context → ~250 ms ⚡ 100K → ~660 ms ⚡ 384K → ~2.5 sec And it supports up to 📚 384K multimodal context 👁️ text + images 🎯 Decision Index → 61.7 🆚 Jev → 57.9 💰 $0.05 / 1M input tokens 💸 output → free It uses SubQ's Sparse Attention. Instead of normal attention getting more expensive as context grows, SubQ says its attention compute scales linearly with context length. ⚠️ No open weights. | No local download. | No model size disclosed. It's API-only for now. Link in ALT

x.com/teksedge/status/2109705667770785985采集于 2026.10.13 10:07