AI Agent StorePerplexity · Provider documented
Perplexity Decider v1.1 27B · local download
Run the v1.1 decision model on your own GPU to assign labels and probabilities to text or images. This download has different limits from the hosted Gateway offer.
First reviewed 2026-10-15 · Checked 2026-10-15. The launch date has not been confirmed.
We still need comparable independent tests. You can compare the confirmed features and limits below, but we cannot yet give this version an Agent Fit or Practical Value rating. Test it on records with known answers, including cases that should go to a person.
What you can use today
You download the model files and supply the hardware and software to run them. Capacity is the amount of information a request can contain; settings and available memory can limit what fits.
Exact checkpoint ID: perplexity-ai/pplx-decider-v1.1-27b. The supplied implementation reads each decision within 8,192 tokens and rejects longer inputs. Images share that space. Its training and reported tests use smaller images than the default serving setting; use the documented setup when reproducing those results.
Weights are Apache 2.0. The card asks for Python 3.12+, CUDA and roughly 49 GiB for weights plus working memory. Its private-repository wording conflicts with publicly readable files; confirm download access. Keep the supplied attention and calibration settings to preserve the tested behavior.
The supplied prepare function limits text and all images for one decision to 8,192 tokens. Training and evaluation used images up to 512×512; the serving default allows up to 2048×2048 and uses more memory.
Output: Yes/no probabilities, choices and ordered scores. Compare decision models, limits and input costs ↗
No hosted token price applies to this download. Budget for hardware, memory and operation; the Gateway quote does not measure local running costs.
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Test it before switching
Give each model the same examples, tools and definition of success. Record correct outcomes, response time, retries and total cost. Include the time and hardware needed to run it.
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