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Baseten / Base Labs · Native API verified

Mammoth-1 · Baseten API

Choose from defined answers, route records or score a condition. Compare this model on your own examples before automating decisions.

Released 2026-10-21 · First reviewed 2026-10-23 · Checked 2026-11-03.

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.

Input / 1M tokens$0.1Native Baseten API · USD
Output / 1M tokens$0Native Baseten API · USD
Documented capacity16KSee input limits below
Cached input / 1M—Native Baseten API · USD

What you can use today

Token prices measure the small pieces of text the model reads or produces. Capacity is the amount the service accepts in a request; check the limits below for any fallback to another model. A dash means the rate is unverified.

Exact provider API ID: decision-models/baseten-mammoth-27b-latest. Up to four images as base64 data URLs or supported cloud-storage HTTPS URLs. Questions are evaluated independently. Shared input is counted once per request, plus each question; confidence measures how concentrated the answer probabilities are.

Use the exact Baseten ID. Gateway’s limits and modality tags differ. The publisher’s evaluation claims are not independent scores here. Flex and priority are optional processing settings; faster completion is not independently measured here.

Each question’s full prompt must fit 16,384 tokens, including shared input, options, formatting and images. Over-limit requests are rejected rather than shortened.

Output: Yes/no probabilities, choices and ordered scores; no written explanation. Compare decision models, limits and input costs ↗

The launch promotion has ended. Current standard input is $0.1 per million billed tokens, with no output-token charge. Native Flex is approximately 90% of default; priority defaults to twice the standard rate. Include retries when comparing the total cost.

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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. Check whether confidence scores match the answers you can verify.

Compare caching and long-context costs ↗
AI Agent Store · Model comparisons · Data reviewed 2026-11-03Sources, limitations & corrections ↗