An open Jev-style LoRA on Qwen3.5-9B from Bespoke Labs, trained on 2,676 contrastively curated examples to score the allowed answer tokens directly for enums, booleans and rubric levels. Recipe, data and a public benchmark suite are released with it.
Invergent's decision model for text and images. A fine-tune of Gemma-4-26B-A4B (about 4B parameters active per token) that answers Choice, Noul and Score questions, with an optional thinking mode for harder questions.
Decides
choice, noul, score, classify, route
choice, score, noul, classify, route
Architecture
nimble
rune
Fine-tuned from
qwen/qwen3.5-9b
google/gemma-4-26b-a4b-it
License
apache-2.0
apache-2.0
Availability
Open weights + hosted API
Open weights + hosted API
Hosted by
Bespoke Labs
Invergent
Input price
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Decision accuracy
90.1%
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Calibration error
0.054
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Valid action rate
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Median latency
106 ms
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p95 latency
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Evaluation suite
Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
Questions
What is the difference between bespoke-nimble-9b and rune?
bespoke-nimble-9b is from Bespoke Labs and rune from Surogate (Invergent). Both have open weights and a hosted API. Both answer choice, noul, score, classify and route questions. rune reads up to 262K tokens of state, against 8K tokens for bespoke-nimble-9b. bespoke-nimble-9b is the smaller model, at 9.0B parameters to 26B.
Which is more accurate, bespoke-nimble-9b or rune?
Only bespoke-nimble-9b publishes an accuracy figure (90.1% on Bespoke held-out set (324 examples)); rune does not, so there is no comparison to make without your own test.
Which is cheaper, bespoke-nimble-9b or rune?
bespoke-nimble-9b: Hosted, price not published, or free to self-host. rune: Hosted, price not published, or free to self-host. Open weights cost nothing per call beyond your own hardware.
Can I run bespoke-nimble-9b or rune locally?
Yes, both: systemone pull bespoke-labs/bespoke-nimble-9b and systemone pull surogate/rune download the weights.
