Models › GOT-OCR-2.0 family

stepfun-ai Apache 2.0 out 23 months ago

561M parameters, images and text in, text out.

Verified 2026-10-25 Rank #766 in LLMs · score 71.2 method v1 Sources 3 Downloads 30d 22.9k · #446 of 619 tracked

Can I run it?0.3GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24
Do people use it?22.9kdownloads, 30 days#446 of 619 we track · below the median243 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: 15 Spaces.

  • As a service0no API provider listed
  • On own hardware0quantized builds
  • Built on31 fine-tunes · 2 adapters · 0 merges
  • In apps15Hugging Face Spaces

Top Spaces running it: yonigozlan/GOT-OCR-Transformers ♥ 83 · Ansemin101/Markit_v2 ♥ 2 · Um34ER/bazaar-bridge-ocr ♥ 2 · Sensei13k/OCR ♥ 1

Will it fit?

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

Fits a 16 GB card at INT4

About 0.3 GB at INT4, 0.7 GB at FP8, 1.3 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.3 GB of weights (estimate; KV cache and activations extra)INT40.3 GBFP8: about 0.7 GB of weights (estimate; KV cache and activations extra)FP80.7 GBBF16: about 1.3 GB of weights (estimate; KV cache and activations extra)BF161.3 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.3 GB of weights (estimate; KV cache and activations extra)INT40.3 GBFP8: about 0.7 GB of weights (estimate; KV cache and activations extra)FP80.7 GBBF16: about 1.3 GB of weights (estimate; KV cache and activations extra)BF161.3 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.

15 repo commits since the weights landed

Teal is the weights (2024-11-22), grey ticks are repo commits.

DecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-01-31: 1 repo commit2025-01-30: 3 repo commits2025-01-27: 1 repo commit2025-01-24: 2 repo commits2025-01-21: 1 repo commit2025-01-06: 1 repo commit2024-11-29: 1 repo commit2024-11-25: 1 repo commit2024-11-22: 4 repo commitsWeights 2024-11-22 · 2024-11-22Weights 2024-11-22now
DecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-01-31: 1 repo commit2025-01-30: 3 repo commits2025-01-27: 1 repo commit2025-01-24: 2 repo commits2025-01-21: 1 repo commit2025-01-06: 1 repo commit2024-11-29: 1 repo commit2024-11-25: 1 repo commit2024-11-22: 4 repo commitsWeights 2024-11-22 · 2024-11-22Weights 2024-11-22now

What people built on it

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

3 derivatives on the Hub, most of them adapters

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

1 fine-tune (Hugging Face model tree)2 adapters (Hugging Face model tree)1 fine-tune2 adapters
1 fine-tune (Hugging Face model tree)2 adapters (Hugging Face model tree)1 fine-tune2 adapters

All variants →

Reference

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

What the card says

1 cited sentence

Summary generated, cited

The model supports various tasks including plain document, scene text, and formatted document OCR under an Apache 2.0 license.[1][2]

  1. “plain document OCR, scene text OCR, formatted document OCR”
  2. license

Generated 2026-10-07 15:15 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

19 fields

Listed in LLMs

Facts

Pipeline tagimage-text-to-text
Librarytransformers
ArchitecturesGotOcr2ForConditionalGeneration
Model typegot_ocr2
Dtypebfloat16
Params by dtypeBF16: 560,528,640
Size bandS
MoEno
Languagesmultilingual
PapersarXiv:2409.01704, arXiv:2405.14295, arXiv:2312.06109
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 GOT-OCR-2.0-hf: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)1.3 GB · Edge (<4 GB)
FP8 (1 byte/param)0.7 GB · Edge (<4 GB)
INT4 (0.5 bytes/param)0.3 GB · Edge (<4 GB)

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

All variants

3 variants

Lineage

Original model Family: stepfun-ai/GOT-OCR-2.0 3 derivatives on the Hub

finetune: 1adapter: 2

Top variants (3 shown, ranked by downloads)

Relation
3 rows
Variant Relation Quant Params Band License Author Likes Downloads
huggingface-mic/got_ocr2-mic finetune — 13.0M S — huggingface-mic 0 258
CharanS247/got-ocr2-telugu-handwritten adapter — — — apache-2.0 CharanS247 0 127
nicogptai/bhcerhbvhfrbhvtrhbbtvr adapter — — — apache-2.0 nicogptai 0 0

Repository changelog

15 commits
changed in the last 7 daysNew on the watch list: 2026-10-24all changes

Repository changelog 15 commits

DateCommitSHA
2025-01-31 Update preprocessor_config.json d3017ef
2025-01-30 Update README.md f445e41
2025-01-30 Update README.md 4a5190b
2025-01-30 Upload GotOcr2ForConditionalGeneration 813b588
2025-01-27 Upload GotOcr2ForConditionalGeneration 1e806a7
2025-01-24 Upload GotOcr2ForConditionalGeneration 6be64fb
2025-01-24 Upload GotOcr2ForConditionalGeneration b6e5417
2025-01-21 Upload GotOcr2ForConditionalGeneration c3255ae
2025-01-06 Upload GotOcr2ForConditionalGeneration da2e9d4
2024-11-29 Upload GotOcr2ForConditionalGeneration b42a53f
2024-11-25 Upload GotOcr2ForConditionalGeneration 74b7f49
2024-11-22 Upload processor 5015eba
2024-11-22 Upload tokenizer d4780c5
2024-11-22 Upload GotOcr2ForConditionalGeneration d6273bc
2024-11-22 initial commit f57d36f

Papers

3 papers

Papers 3

arXiv links found in the model card and its tags. "Peer-reviewed" is shown only with evidence: a published venue in OpenAlex (measured) or the authors' own journal reference on arXiv (reported).

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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:43 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:15 UTC · Last verified 2026-10-25

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