Why high: one template-boundary shift from a group whose members all declare the same family.
Mancer: Weaver (alpha) is Mancer's model. Its measured tokenizer sits with the Llama2 group, which is evidence that it builds on the Llama2 tokenizer. Tokenizer reuse is normal engineering, open vocabularies travel between labs, and this says nothing against Mancer's authorship of the model itself.
| We checked | What we found | Where it came from |
|---|---|---|
| How it counts tokens | Counted cleanly, and no other model in the catalogue counts the same way | tk_03ecdf53 |
| How its API is set up | A combination of settings no other listing in the catalogue uses | api_3ef4cdbd |
| How much it can read and write | Reads up to 8,000 tokens at once, writes up to 6,000 | its own listing |
| Who served our requests | Mancer 2 | we measured it, 21 August 2026 |
Click a row to open the full comparison.
We sent Mancer: Weaver (alpha) fifty short pieces of text and recorded what each one cost it in tokens. The bars below are those costs. Two models built on the same tokenizer produce the same bars; a model built on a different one produces a different set, which is what makes this a fingerprint.
Overhead subtracted: 107 prompt tokens.
An attempt to recreate Claude-style verbosity, but don't expect the same level of coherence or memory. Meant for use in roleplay/narrative situations.
Supported parameters
frequency_penaltylogit_biaslogprobsmax_tokensmin_ppresence_penaltyrepetition_penaltyresponse_formatseedstoptemperaturetop_atop_ktop_logprobstop_p
defaults: {}
