Models › jpt family

kirp CC BY-NC 4.0 out 30 days ago

9.41B parameters, images and text in, text out, 256K tokens of context.

Verified 2026-10-25 Rank #0 in Decision models · score 0 method v1 Sources 3 Downloads 30d 1.1k · #591 of 619 tracked

Can I run it?5.6GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?CC BY-NC 4.0Non-commercial only; commercial hosting not permitted without a separate licenselicence file2026-10-24
Do people use it?1.1kdownloads, 30 days#591 of 619 we track · below the median+0 likes, downloads +5% this week6 likesHugging Face2026-10-24

Worth reading

Picked by rule from 1 tracked piece: the lab's own post, the most shared, a field report, the latest.

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: 3 quantized builds and 7 Spaces.

  • As a service0no API provider listed
  • On own hardware3quantized builds
  • Built on22 fine-tunes · 0 adapters · 0 merges
  • In apps7Hugging Face Spaces

Top Spaces running it: multimodalart/jev-decision-index ♥ 802 · kirp/jpt-9b-typed-decisions ♥ 1

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Fits a 16 GB card at INT4

About 5.6 GB at INT4, 11 GB at FP8, 23 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 5.6 GB of weights (estimate; KV cache and activations extra)INT45.6 GBFP8: about 11 GB of weights (estimate; KV cache and activations extra)FP811 GBBF16: about 23 GB of weights (estimate; KV cache and activations extra)BF1623 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 5.6 GB of weights (estimate; KV cache and activations extra)INT45.6 GBFP8: about 11 GB of weights (estimate; KV cache and activations extra)FP811 GBBF16: about 23 GB of weights (estimate; KV cache and activations extra)BF1623 GB

Estimate params × bytes per param × 1.2 · how we estimate

The story so far

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

1 dated article and 10 repo commits so far

Teal is the weights (2026-09-25), amber triangles are 1 dated article (each links to it), grey ticks are repo commits.

DecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2026-10-04: 1 repo commit2026-09-27: 5 repo commits2026-09-25: 4 repo commitsSPE, Aramco Americas, and I2k Connect Explore an LLM for the Energy Industry · 2023-11-19Weights 2026-09-25 · 2026-09-25Weights 2026-09-25now
DecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2026-10-04: 1 repo commit2026-09-27: 5 repo commits2026-09-25: 4 repo commitsSPE, Aramco Americas, and I2k Connect Explore an LLM for the Energy Industry · 2023-11-19Weights 2026-09-25 · 2026-09-25Weights 2026-09-25now

What people built on it

5 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

5 derivatives on the Hub, most of them quantized

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

3 quantized (Hugging Face model tree)2 fine-tunes (Hugging Face model tree)3 quantized2 fine-tunes
3 quantized (Hugging Face model tree)2 fine-tunes (Hugging Face model tree)3 quantized2 fine-tunes

All variants →

Reference

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

Benchmarks

38 rows

Benchmarks 38 rows

measured third-party leaderboard rowauthor-reported number from the model card or eval files (38)No confidence intervals unless the source gave them; settings differ between rows, so compare within a benchmark, not across. Date = the benchmark's own date when it gives one, else when we read it.
BenchmarkValueSetting / notesReported byDate
author-reported ACOS20.3Languagemodel author2026-10-07
author-reported ANLI50Languagemodel author2026-10-07
author-reported Amazon ESCI40.6Retrievalmodel author2026-10-07
author-reported Arts28.6—model author2026-10-07
author-reported BBH · Reason through hard problems55.6Knowledgemodel author2026-10-07
author-reported BPoMP72.4Artsmodel author2026-10-07
author-reported BRIGHT · Rerank search results39.9Retrievalmodel author2026-10-07
author-reported Banking77 · Classify and make typed decisions65Retrievalmodel author2026-10-07
author-reported CLINC150+OOS35.8Retrievalmodel author2026-10-07
author-reported CLadder33.8Knowledgemodel author2026-10-07
author-reported CRUXEval29.6Knowledgemodel author2026-10-07
author-reported ChessBench7.3Gamesmodel author2026-10-07
author-reported ContractNLI74.2Languagemodel author2026-10-07
author-reported Decision Index (DI) · Classify and make typed decisions46.89—model author2026-10-07
author-reported FinEntity90Languagemodel author2026-10-07
author-reported GPQA Diamond · Reason through hard problems21.8Knowledgemodel author2026-10-07
author-reported GSM8K · Reason through hard problems69.2Knowledgemodel author2026-10-07
author-reported Habermas Machine13.2Artsmodel author2026-10-07
author-reported HellaSwag · Chat and follow instructions81.2Languagemodel author2026-10-07
author-reported HoVer32.7Retrievalmodel author2026-10-07
author-reported Humanity's Last Exam · Reason through hard problems0Knowledgemodel author2026-10-07
author-reported Humicroedit19.5Artsmodel author2026-10-07
author-reported Knowledge31.7—model author2026-10-07
author-reported Language56.7—model author2026-10-07
author-reported MMLU-Pro · Reason through hard problems49.1Knowledgemodel author2026-10-07
Show all 38 rows (13 more)
BenchmarkValueSetting / notesReported byDate
author-reported MuSR28.1Knowledgemodel author2026-10-07
author-reported NLI4CT59.1Languagemodel author2026-10-07
author-reported New Yorker52.6Artsmodel author2026-10-07
author-reported POP909-CL3.5Artsmodel author2026-10-07
author-reported RAGTruth50.6Languagemodel author2026-10-07
author-reported Retrieval44.6—model author2026-10-07
author-reported SATA-Bench22.6Knowledgemodel author2026-10-07
author-reported Terminal-Bench · Write code with agents27.4Artsmodel author2026-10-07
author-reported Tools67—model author2026-10-07
author-reported VAST46.6Languagemodel author2026-10-07
author-reported Winogrande · Chat and follow instructions49.2Languagemodel author2026-10-07
author-reported cfcolor11.4Artsmodel author2026-10-07
author-reported iSarcasmEval43.9Languagemodel author2026-10-07

Use-case evidence

8 use cases

Facts

20 fields

Listed in Decision models

Facts

Pipeline tagimage-text-to-text
Librarytransformers
ArchitecturesQwen3_5ForConditionalGeneration
Model typeqwen3_5
Dtypebfloat16
Params by dtypeBF16: 9,409,809,904 · F32: 3,840
Size bandL
MoEno
Context length262,144 (config.json max_position_embeddings)
LicenseCC BY-NC 4.0 (cc-by-nc-4.0)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · Qwen3_5ForConditionalGeneration · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · Qwen3_5ForConditionalGeneration · 773cb938fe9484a8f7e7e46fb1b1fe96412c59ed

vLLM registry (7050ef881ff0835f6890a47db1859a24c65481d6) · SGLang registry (773cb938fe9484a8f7e7e46fb1b1fe96412c59ed) · Matched by architecture class name against each project's registry on main; 'supported' means the architecture is registered, not that this checkpoint was tested.

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for jpt-9b: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)23 GB · Single GPU (<24 GB)
FP8 (1 byte/param)11 GB · Single GPU (<24 GB)
INT4 (0.5 bytes/param)5.6 GB · Single GPU (<24 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

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 score46.89 (independent (DI 0.2.1 board))
ECE (board)0.0773
Median latency148.6 ms (DI board, 1x RTX PRO 6000, single process)
Hosted price (input)self-hosted/M
Sourcehttps://huggingface.co/kirp/jpt-9b

All variants

5 variants

Lineage

Fine-tuned from Qwen/Qwen3.5-9B Family: kirp/jpt 5 derivatives on the Hub

Base model: Qwen/Qwen3.5-9B

quantized: 3finetune: 2

Top variants (5 shown, ranked by downloads)

Relation
Quant
5 rows
Variant Relation Quant Params Band License Author Likes Downloads
prithivMLmods/jpt-9b-GGUF quantized GGUF — — cc-by-nc-4.0 prithivMLmods 3 1.3k
RepublicOfKorokke/jpt-9b-oQ4e quantized — 9.41B L — RepublicOfKorokke 0 113
RepublicOfKorokke/jpt-9b-oQ4e-fp16 quantized -fp16 9.41B L — RepublicOfKorokke 0 72
sergolsub/mlx-jpt-9B finetune mlx 9.41B L cc-by-nc-4.0 sergolsub 0 9
sergolsub/mlx-jpt_9B finetune mlx — — cc-by-nc-4.0 sergolsub 0 0

Repository changelog

10 commits

Repository changelog 10 commits

DateCommitSHA
2026-10-04 Model card: AG News / Emotion / SST-5 train splits are in the training mix (not out-of-distribution) 9fda2c7
2026-09-27 Model card: JPT-9B JevBench public 0.853 measured with the JevBench CLI b447cc7
2026-09-27 Model card: add JPT-35B-A3B to the family links, JevBench and Decision Index dd416ab
2026-09-27 Model card: Jev 1.13.0 official scores as baseline; Decision Index by area vs Jev e389a7c
2026-09-27 Model card: fix badge anchors 2b96880
2026-09-27 Model card: new layout (charts, badges, Decision Index 0.2.1, versioned benchmarks with references) a27d740
2026-09-25 Add Decision Index 0.2 score 7114b0c
2026-09-25 Add model card d5e20b2
2026-09-25 JPT-9B: mix_train_env_v11, LoRA r16 merged, chat prompt, T=1.087 2ad078e
2026-09-25 initial commit fcee91c

Articles and coverage

1 piece

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.

Analysis1

jpt.spe.org2023-11-19about the jpt familyHN 1 pts · 0 comments258 words
SPE, Aramco Americas, and i2k Connect Inc. signed an MOU to develop an energy-industry specific large language model. The initiative aims to enhance the OnePetro portal, which contains more than 314,000 items from 22 publishing partners, by enabling conversational answers that reference original sources for validation. This tool will allow professionals to extract, analyze, and summarize SPE technical content to reduce decision-making time.written, reviewed, cited

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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:44 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:19 UTC · Last verified 2026-10-25

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