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Govind Kamtamneni

thegovind

Models in Library3
Datasets in Library0
Models on Hugging Face13
Followers5

Models

Model · Text classification

blink-4b

Govind Kamtamneni

Small, fast decisions for routing and checks at volume. Send text or JSON state with choice, noul (yes/no), or score questions. Get a probability for every offered answer, not generated text. Each batch takes one forward pass; large requests can use several batches. Use choice to route a request, noul for a yes/no check, or score for an ordered rating. The same call can ask several questions about a single state. Try it: POST /v1/systemone, GET /v1/models, and GET /healthz. Point TypeSafe's server-side Python or JavaScript SDKs at it with TYPESAFEBASEURL; text decisions use the same request and response fields as hosted Jev. Requests run one at a time by default; --batch-window-ms 5 enables…

Open weights other 4.2B parameters 262,144 tokens transformers

Model · Text classification

blink-27b

Govind Kamtamneni

The most accurate blink model for hard typed decisions. It also performed best of the three in local browser-agent runs that passed page elements as text, not screenshots; see browser-agent setup. These local pages are not a benchmark. Send text or JSON state with choice, noul (yes/no), or score questions. Get a probability for each offered answer without generated text. Each batch uses one forward pass; large requests can use several batches. For browser agents, send the page and candidate elements as JSON state; make operations and click targets choice questions. The probability map lets an agent pick among its proposed actions. This is a text-element workflow, not autonomous web…

Open weights other 26.9B parameters 262,144 tokens transformers

Model · Image and text to text

blink-mimo-9b

Govind Kamtamneni

Send a text or JSON state and your questions: choice picks from up to 255 options, noul is yes/no, and score takes 2–10 ordered levels. Each question gets probabilities over its offered options from one forward pass, with no generated text. Long or large multi-question requests may use several batches. Personal research release by thegovind, not an official product of any company. No affiliation with TypeSafe AI, Xiaomi, Alibaba Cloud or the Qwen team. Weights are for non-commercial research; see Licence. We ran the full Decision Index 0.2 suite ourselves with the official scoring kit at commit 19ad28e on 2026-09-25. This is a descriptive run, not a leaderboard submission or accepted…

Open weights other 9.4B parameters 262,144 tokens transformers