Models › Lumma family

FrontiersMind Apache 2.0 out 30 days ago

154M parameters, text in, labels out.

Verified 2026-10-25 Rank #0 in Decision models · score 0 method v1 Sources 3 Downloads 30d 9.2k · #513 of 619 tracked

Can I run it?0.1GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24
Do people use it?9.2kdownloads, 30 days#513 of 619 we track · below the median+0 likes, downloads +1% this week17 likesHugging Face2026-10-24

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 Spaces.

  • As a service0no API provider listed
  • On own hardware0quantized builds
  • Built on00 fine-tunes · 0 adapters · 0 merges
  • In apps3Hugging Face Spaces

Will it fit?

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

Fits a 16 GB card at INT4

About 0.1 GB at INT4, 0.2 GB at FP8, 0.4 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.1 GB of weights (estimate; KV cache and activations extra)INT40.1 GBFP8: about 0.2 GB of weights (estimate; KV cache and activations extra)FP80.2 GBBF16: about 0.4 GB of weights (estimate; KV cache and activations extra)BF160.4 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.1 GB of weights (estimate; KV cache and activations extra)INT40.1 GBFP8: about 0.2 GB of weights (estimate; KV cache and activations extra)FP80.2 GBBF16: about 0.4 GB of weights (estimate; KV cache and activations extra)BF160.4 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.

18 repo commits since the weights landed

Teal is the weights (2026-09-25), grey ticks are repo commits.

Oct2026-10-02: 1 repo commit2026-09-29: 1 repo commit2026-09-28: 1 repo commit2026-09-26: 1 repo commit2026-09-25: 14 repo commitsWeights 2026-09-25 · 2026-09-25Weights 2026-09-25now
Oct2026-10-02: 1 repo commit2026-09-29: 1 repo commit2026-09-28: 1 repo commit2026-09-26: 1 repo commit2026-09-25: 14 repo commitsWeights 2026-09-25 · 2026-09-25Weights 2026-09-25now

Reference

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

Benchmarks

6 rows

Benchmarks 6 rows

measured third-party leaderboard rowauthor-reported number from the model card or eval files (6)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 AG News0.89Lumma-Fev-0.15Bmodel author2026-10-07
author-reported Average0.63Lumma-Fev-0.15Bmodel author2026-10-07
author-reported Banking77 · Classify and make typed decisions0.47Lumma-Fev-0.15Bmodel author2026-10-07
author-reported DAIR Emotion0.68Lumma-Fev-0.15Bmodel author2026-10-07
author-reported P50 latency35.576 ms otherLumma-Fev-0.15Bmodel author2026-10-07
author-reported Typed-decisions0.49Lumma-Fev-0.15Bmodel author2026-10-07

What the card says

1 cited sentence

Summary generated, cited

The model performs text classification by returning a probability distribution for typed questions in a single forward pass.[1][2]

  1. pipeline tag
  2. “returns a probability distribution for each question in a…”

Generated 2026-10-07 15:19 UTC by parasail-gemma-4-26b-a4b-it; each numeral points at the fact it rests on. Not a verdict.

Use-case evidence

3 use cases

What it is good at 3 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

18 fields

Listed in Decision models

Facts

Pipeline tagtext-classification
Librarytransformers
ArchitecturesFevForDecision
Model typefev
Dtypebfloat16
Params by dtypeBF16: 153,249,856 · F32: 852,992
Size bandS
MoEno
Languagesen
LicenseApache 2.0 (apache-2.0)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: not in registry · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: not in registry · 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 Lumma-fev-0.1b: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)0.4 GB · Edge (<4 GB)
FP8 (1 byte/param)0.2 GB · Edge (<4 GB)
INT4 (0.5 bytes/param)0.1 GB · Edge (<4 GB)

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

Decision facts

catalog

Decision-model catalog curated

How it was madefull fine-tune of own from-scratch pretrained base
Lineage bucketO - original architecture or own base
Lineage evidencemodel card: fine-tuned from Nandi-Mini-150M "which we pre-trained from scratch"
Base modelFrontiersMind/Nandi-Mini-150M
DI 0.2.1 score1.78 (independent (DI 0.2.1 board))
ECE (board)0.1574
Median latency20.9 ms (DI board, 1x RTX PRO 6000, single process)
Hosted price (input)self-hosted/M
Contamination notes3,077 BANKING77 test items found in FrontiersMind's own decision datasets count as wrong
Sourcehttps://huggingface.co/FrontiersMind/Lumma-fev-0.1b

All variants

lineage

Lineage

Fine-tuned from FrontiersMind/Nandi-Mini-150M (same organization) Family: FrontiersMind/Lumma 0 derivatives on the Hub

Base model: FrontiersMind/Nandi-Mini-150M

Repository changelog

18 commits

Repository changelog 18 commits

DateCommitSHA
2026-10-02 Update README.md 4eb5d5c
2026-09-29 Update README.md 085f470
2026-09-28 Updated benchmarks 8094001
2026-09-26 Update README.md 32408cf
2026-09-25 Update README.md 37fccd0
2026-09-25 Update README.md 125863f
2026-09-25 Update README.md c201670
2026-09-25 Upload lumma-01b-playing-mario.mov 0b2dd33
2026-09-25 Update README.md 8c49c4d
2026-09-25 Update README.md fac8256
2026-09-25 Update README.md 55b1c8b
2026-09-25 Update README.md d27e809
2026-09-25 Upload lumma-01b-playing-mario.mp4 3208d15
2026-09-25 Update README.md 3f228ca
2026-09-25 Update README.md 98f65e7
2026-09-25 Update README.md ef8cf6e
2026-09-25 Upload lumma-fev-0.1b 2ba4653
2026-09-25 initial commit ae3220e

Similar models

3 models

Similar models

  • rlcd-modernbert-151m · 151M
    same size band (S), same task (text-classification), permissive license
  • Julia-1 · 144M
    same size band (S), same task (text-classification), permissive license
  • sokudan-ja-310m · 315M
    same size band (S), same task (text-classification), permissive license

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

Follow Lumma-fev-0.1b

Watch this model

Email alerts are not open yet; the feeds above are the same data. See feeds for the item schema.