Models › Bespoke family

Bespoke-Nimble-9B-v2

bespokelabs Apache 2.0 out 33 days ago

Verified 2026-10-26 07:27 UTC Rank #0 in Decision models · score 0 method v1 Sources 3 Downloads 30d 836 · #597 of 619 tracked

Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-26
Do people use it?836downloads, 30 days#597 of 619 we track · below the median+0 likes, downloads +18% this week10 likesHugging Face2026-10-26

Worth reading

Picked by rule from 3 tracked pieces: the lab's own post, the most shared, a field report, the latest.

3 best of 3 tracked

The 2 picks above, plus these 1. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. ArticleBespoke-Stratos: The unreasonable effectiveness of reasoning distillationbespokelabs.ai · 2025-01-26 · 13 HN pts

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

No API provider serves it, so its downloads are people running it themselves: 7 Spaces.

  • As a service0no API provider listed
  • On own hardware0quantized builds
  • Built on00 fine-tunes · 0 adapters · 0 merges
  • In apps7Hugging Face Spaces

Top Spaces running it: multimodalart/jev-decision-index ♥ 802

The story so far

Weights, every dated article, and repo commits on one rail.

Most coverage came in the first two weeks

Teal is the weights (2026-09-23), amber triangles are 3 dated articles (each links to it), grey ticks are repo commits.

OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2026-09-23: 7 repo commitsBespoke Nimble: open data, open model, open recipe for an open Jev · 2026-09-18Bespoke Synth 1.0 – open-source software modular synthesizer · 2021-09-14Bespoke-Stratos: The unreasonable effectiveness of reasoning distillation · 2025-01-26Weights 2026-09-23 · 2026-09-23Weights 2026-09-23now
OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2026-09-23: 7 repo commitsBespoke Nimble: open data, open model, open recipe for an open Jev · 2026-09-18Bespoke Synth 1.0 – open-source software modular synthesizer · 2021-09-14Bespoke-Stratos: The unreasonable effectiveness of reasoning distillation · 2025-01-26Weights 2026-09-23 · 2026-09-23Weights 2026-09-23now

Reference

Everything else, folded: the full tables, every source.

What the card says

3 cited sentences

Summary generated, cited

Bespoke-Nimble-9B-v2 is a PEFT LoRA adapter for text-based, schema-conditioned decisions based on the Qwen/Qwen3.5-9B model.[1][2] The model scores answer-token logits to provide boolean judgments, categorical choices, and ordinal scores under an Apache 2.0 license.[3][4] It supports up to 255 choices per field within an 8,192-token context limit.[5][6]

  1. “PEFT LoRA adapter”
  2. base models
  3. “boolean judgments, categorical choices, and ordinal scores”
  4. license
  5. “255 choices per field”
  6. “8,192-token context limit”

Generated 2026-10-07 15:18 UTC by parasail-gemma-4-26b-a4b-it; each numeral points at the fact it rests on. Not a verdict.

Use-case evidence

4 use cases

What it is good at 4 use cases

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

10 fields

Listed in Decision models

Facts

Librarypeft
MoEno
Languagesen
LicenseApache 2.0 (apache-2.0)
Hub snapshot2026-10-26

Decision facts

catalog

Decision-model catalog curated

How it was madeLoRA/adapter fine-tune
Lineage bucketF - fine-tune of an open model (public/synthetic data)
Lineage evidenceboard file inspection (adapter/head/weight files) + HF base_model field
Base modelQwen/Qwen3.5-9B-Base
DI 0.2.1 score39.57 (independent (DI 0.2.1 board))
ECE (board)0.0240
Median latency77.3 ms (DI board, 1x RTX PRO 6000, single process)
Hosted price (input)self-hosted/M
Sourcehttps://huggingface.co/bespokelabs/Bespoke-Nimble-9B-v2

All variants

lineage

Lineage

Adapter Family: bespokelabs/Bespoke 0 derivatives on the Hub

Base model: Qwen/Qwen3.5-9B

Repository changelog

7 commits

Repository changelog 7 commits

DateCommitSHA
2026-09-23 Support up to 255 choices in v2 inference without changing weights 4b8c04d
2026-09-23 Document automatic v2 temperature in the GitHub loaders e1f8311
2026-09-23 Require explicit opt-in for raw v2 probabilities aec13f1
2026-09-23 Apply transferred GitHub probability temperature to v2 scoring 84c365a
2026-09-23 Update README.md 01ebf0a
2026-09-23 Upload verified 4926-example Bespoke-Nimble-9B-v2 LoRA checkpoint a3ca9ca
2026-09-23 initial commit 9388849

Articles and coverage

3 pieces

Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency. Summaries are generated from a stored copy of the article text; every sentence cites a span of that text, and nothing is shown that failed the citation check.

Analysis2

bespokesynth.com2021-09-14HN front pageabout the Bespoke familyHN 745 pts · 242 comments350 words
Bespoke is a free, open-source modular synthesizer licensed under GPLv3 with releases for Mac, Windows, and Linux. It contains 190+ modules optimized for jamming and exploration instead of a global timeline. Users can pay $20 or $40 to donate to the NAACP Legal Defense and Educational Fund while accessing identical features.written, reviewed, cited
bespokelabs.ai2025-01-26about the Bespoke familyHN 13 pts · 2 comments767 words
Bespoke Labs released Bespoke-Stratos-32B, a reasoning model distilled from DeepSeek-R1 using Berkeley NovaSky's Sky-T1 data pipeline. The model outperforms Sky-T1 and o1-preview on Math and Code benchmarks while achieving near-DeepSeek-R1 performance with 47x fewer training examples. Training utilized the Bespoke Curator pipeline to generate the dataset within 1.5 hour, employing gpt-4o-mini to filter math solutions and increase retained correct solutions from 25% to 73%.written, reviewed, cited
  • The team found DeepSeek-R1 reasoning traces were sufficiently well-formatted for parsing without an intermediate reformatting step.
  • Sky-T1 authors noted they saw little or no improvement training 7B or 14B models with their data.

Community1

twitter.com2026-09-18about the Bespoke familyHN 7 pts · 0 comments

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Sources

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Sources

Hub snapshot: 2026-10-26 · HF API: 2026-10-26 07:25 UTC · Providers: 2026-10-26 07:26 UTC · Articles: 2026-10-26 07:27 UTC · Summary: 2026-10-07 15:18 UTC · Last verified 2026-10-26 07:27 UTC

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