Models › OLMo-2 family

allenai Apache 2.0 out 18 months ago

1.48B parameters, text in, text out, 4K tokens of context.

Verified 2026-10-25 Rank #530 in LLMs · score 75.5 method v1 Sources 3 Downloads 30d 132.1k · #287 of 619 tracked

Can I run it?0.9GB at INT4Estimatefits a 16 GB cardmethod
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24
Do people use it?132.1kdownloads, 30 days#287 of 619 we track · top 46%+0 likes, downloads −40% this week82 likesHugging Face2026-10-24

Worth reading

Picked by rule from 6 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 64 HN pts

Mlx-community/OLMo-2-0325-32B-Instruct-4bit

OLMo 2 32B claims to be the first fully-open model to outperform GPT3.5-Turbo and GPT-4o mini.

simonwillison.net 2025-03-16 64 HN pts · 23 comments 195 words about the OLMo 2 family family
Latest · 16 months ago

OLMo 2 - a family of fully-open language models

The Olmo 3 model family offers a complete model flow with full access to training data, logs, and the entire lifecycle.

allenai.org 2025-07-09 34 HN pts · 4 comments 372 words about the OLMo 2 family family

6 best of 6 tracked

The 2 picks above, plus these 4. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. ArticleOLMo 2 32B: First fully open model to outperform GPT 3.5 and GPT 4o miniallenai.org · 2025-03-13 · official
  2. ArticleOLMo 2: The best open language model to date – Ai2allenai.org · 2024-11-28 · 2 HN pts · official
  3. Paper2 OLMo 2 Furiousarxiv.org · 2025-01-03 · 4 HN pts
  4. ArticleProbes trace an emergent jailbreak in OLMo 2 to mislabeled training datalesswrong.com · 2026-04-29 · 2 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: 13 quantized builds and 5 Spaces.

  • As a service0no API provider listed
  • On own hardware13quantized builds
  • Built on6047 fine-tunes · 12 adapters · 1 merges
  • In apps5Hugging Face Spaces

Will it fit?

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

Fits a 16 GB card at INT4

About 0.9 GB at INT4, 1.8 GB at FP8, 3.6 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.9 GB of weights (estimate; KV cache and activations extra)INT40.9 GBFP8: about 1.8 GB of weights (estimate; KV cache and activations extra)FP81.8 GBBF16: about 3.6 GB of weights (estimate; KV cache and activations extra)BF163.6 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 0.9 GB of weights (estimate; KV cache and activations extra)INT40.9 GBFP8: about 1.8 GB of weights (estimate; KV cache and activations extra)FP81.8 GBBF16: about 3.6 GB of weights (estimate; KV cache and activations extra)BF163.6 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.

Most coverage came in the first two weeks

Teal is the weights (2025-04-17), amber triangles are 5 dated articles (each links to it), grey ticks are repo commits.

DecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-05-28: 1 repo commit2025-04-30: 7 repo commits2025-04-29: 4 repo commits2025-04-28: 3 repo commits2025-04-17: 2 repo commitsMlx-community/OLMo-2-0325-32B-Instruct-4bit · 2025-03-16OLMo 2 - a family of fully-open language models · 2025-07-09OLMo 2: The best open language model to date – Ai2 · 2024-11-282 OLMo 2 Furious · 2025-01-03Probes trace an emergent jailbreak in OLMo 2 to mislabeled training data · 2026-04-29Weights 2025-04-17 · 2025-04-17Weights 2025-04-17now
DecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-05-28: 1 repo commit2025-04-30: 7 repo commits2025-04-29: 4 repo commits2025-04-28: 3 repo commits2025-04-17: 2 repo commitsMlx-community/OLMo-2-0325-32B-Instruct-4bit · 2025-03-16OLMo 2 - a family of fully-open language models · 2025-07-09OLMo 2: The best open language model to date – Ai2 · 2024-11-282 OLMo 2 Furious · 2025-01-03Probes trace an emergent jailbreak in OLMo 2 to mislabeled training data · 2026-04-29Weights 2025-04-17 · 2025-04-17Weights 2025-04-17now

What people built on it

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

73 derivatives on the Hub, most of them fine-tunes

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

13 quantized (Hugging Face model tree)47 fine-tunes (Hugging Face model tree)1 merge (Hugging Face model tree)12 adapters (Hugging Face model tree)13 quantized47 fine-tunes1 merge12 adapters
13 quantized (Hugging Face model tree)47 fine-tunes (Hugging Face model tree)1 merge (Hugging Face model tree)12 adapters (Hugging Face model tree)13 quantized47 fine-tunes1 merge12 adapters

All variants →

Reference

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

Benchmarks

11 rows

Benchmarks 11 rows

measured third-party leaderboard rowauthor-reported number from the model card or eval files (11)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 AE29.1OLMo 2 1Bmodel author2026-10-07
author-reported Avg42.7OLMo 2 1Bmodel author2026-10-07
author-reported BBH · Reason through hard problems35OLMo 2 1Bmodel author2026-10-07
author-reported DROP34.6OLMo 2 1Bmodel author2026-10-07
author-reported GSM8K · Reason through hard problems68.3OLMo 2 1Bmodel author2026-10-07
author-reported IFE70.1OLMo 2 1Bmodel author2026-10-07
author-reported MATH-500 · Reason through hard problems20.7OLMo 2 1Bmodel author2026-10-07
author-reported MMLU · Reason through hard problems40OLMo 2 1Bmodel author2026-10-07
author-reported PQA12.9OLMo 2 1Bmodel author2026-10-07
author-reported Safety87.6OLMo 2 1Bmodel author2026-10-07
author-reported TQA48.7OLMo 2 1Bmodel author2026-10-07

Use-case evidence

2 use cases

What it is good at 2 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

21 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesOlmo2ForCausalLM
Model typeolmo2
Dtypefloat32
Params by dtypeF32: 1,484,916,736
Size bandS
MoEno
Context length4,096 (config.json max_position_embeddings)
Languagesen
PapersarXiv:2501.00656
LicenseApache 2.0 (apache-2.0)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · Olmo2ForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · Olmo2ForCausalLM · 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 OLMo-2-0425-1B: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)3.6 GB · Edge (<4 GB)
FP8 (1 byte/param)1.8 GB · Edge (<4 GB)
INT4 (0.5 bytes/param)0.9 GB · Edge (<4 GB)

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

All variants

40 variants

Lineage

Original model Family: allenai/OLMo-2 73 derivatives on the Hub

finetune: 47quantized: 13merge: 1adapter: 12

Top variants (40 shown, ranked by downloads)

Relation
Quant
Size
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
allenai/OLMo-2-0425-1B-SFT finetune — — — apache-2.0 allenai 5 169.4k
allenai/OLMo-2-0425-1B-GGUF quantized GGUF — — — allenai 2 5.6k
allenai/Bolmo-1B-Stage1 finetune — 1.47B S apache-2.0 allenai 0 5k
mradermacher/OLMo-2-0425-1B-i1-GGUF quantized GGUF — — apache-2.0 mradermacher 0 2.8k
SipsaLabs/olmo-2-0425-1b-uc-v3-bpw3 finetune — — — other SipsaLabs 0 2.4k
Pinkstack/Luau-coder-v2-3B-base-32k finetune — 2.83B M apache-2.0 Pinkstack 2 1.3k
mradermacher/OLMo-2-0425-1B-GGUF quantized GGUF — — apache-2.0 mradermacher 0 1.3k
DevQuasar/allenai.OLMo-2-0425-1B-GGUF quantized GGUF — — — DevQuasar 0 1k
SakanaAI/RePo-OLMo2-1B-stage2-L5 finetune — 1.50B S apache-2.0 SakanaAI 2 822
SirSahOl/OLMo-2-0425-1B-chat-mlx-16bit finetune mlx 1.48B S apache-2.0 SirSahOl 0 724
burnedinthesky/gpt2-olmo2-1b-warm120-ot-muon-lr4e-3-tok401k-seq1024-cos-wu5-485335 merge — 124M S apache-2.0 burnedinthesky 0 511
loris3/OLMo-2-0425-1B_tulu-3-sft-olmo-2-mixture-0225_lr0.0001_seed42 adapter — — — — loris3 0 472
lewtun/tailsft-repro-olmo2-1b-tail50 finetune — 1.48B S — lewtun 0 369
lewtun/tailsft-repro-olmo2-1b-std finetune — 1.48B S — lewtun 0 358
liodon-ai/OLMo-2-0425-1B-ONNX quantized — — — other liodon-ai 0 335
lewtun/tailsft-repro-olmo2-1b-tail70 finetune — 1.48B S — lewtun 0 329
lewtun/tailsft-repro-smoke-tail50 finetune — 1.48B S — lewtun 0 328
lewtun/tailsft-repro-smoke-std finetune — 1.48B S — lewtun 0 314
DennisKoshta/upbringing-olmo2-1b-sft finetune — 1.48B S — DennisKoshta 0 293
hahaws777/OLMo-2-0425-1B-CS336A5-LowVRAM finetune — 1.48B S apache-2.0 hahaws777 0 253
smdesai/OLMo-2-0425-1B-4bit quantized -4bit 1.48B S apache-2.0 smdesai 0 162
jiosephlee/6_papers_50_epochs finetune — 1.48B S — jiosephlee 0 162
gunveersandhu/OLMo-2-0425-1B-4bit quantized -4bit 1.48B S apache-2.0 gunveersandhu 0 134
UnfaithRL/OLMo-2-0425-1B-hint_following_reward-512 finetune — 1.48B S — UnfaithRL 0 95
UnfaithRL/OLMo-2-0425-1B-hint_verbalization_reward_relaxed_v7-512 finetune — 1.48B S — UnfaithRL 0 93
UnfaithRL/OLMo-2-0425-1B-hint_verbalization_reward_relaxed_v7-1024 finetune — 1.48B S — UnfaithRL 0 88
UnfaithRL/OLMo-2-0425-1B-hint_verbalization_reward_relaxed_v7-2048 finetune — 1.48B S — UnfaithRL 0 88
thorirhrafn/IceOLMo-1B-01 finetune — 1.48B S apache-2.0 thorirhrafn 0 86
4fhct4sd/genesis-round-01-GGUF quantized GGUF — — apache-2.0 4fhct4sd 0 78
UnfaithRL/OLMo-2-0425-1B-curriculum_learning-1024 finetune — 1.48B S — UnfaithRL 0 75
UnfaithRL/OLMo-2-0425-1B-hint_following_reward_faithful_prompt-1024 finetune — 1.48B S — UnfaithRL 0 72
UnfaithRL/OLMo-2-0425-1B-hint_following_reward_faithful_prompt-512 finetune — 1.48B S — UnfaithRL 0 71
UnfaithRL/OLMo-2-0425-1B-hybrid_accuracy_hint_reward-1024 finetune — 1.48B S — UnfaithRL 0 70
UnfaithRL/OLMo-2-0425-1B-hybrid_accuracy_hint_reward-2048 finetune — 1.48B S — UnfaithRL 0 70
UnfaithRL/OLMo-2-0425-1B-hint_following_reward_faithful_prompt-2048 finetune — 1.48B S — UnfaithRL 0 70
UnfaithRL/OLMo-2-0425-1B-hybrid_accuracy_hint_reward-512 finetune — 1.48B S — UnfaithRL 0 69
UnfaithRL/OLMo-2-0425-1B-hint_following_reward-1024 finetune — 1.48B S — UnfaithRL 0 68
UnfaithRL/OLMo-2-0425-1B-hint_verbalization_reward_strict_v9-512 finetune — 1.48B S — UnfaithRL 0 68
UnfaithRL/OLMo-2-0425-1B-curriculum_learning-2048 finetune — 1.48B S — UnfaithRL 0 65
UnfaithRL/OLMo-2-0425-1B-shuffled_dataset-2048 finetune — 1.48B S — UnfaithRL 0 64

Repository changelog

17 commits

Repository changelog 17 commits

DateCommitSHA
2025-05-28 Update README.md a1847df
2025-04-30 Update README.md 1352aa4
2025-04-30 Update README.md 5af071b
2025-04-30 Update README.md f941e23
2025-04-30 Update README.md e85cd76
2025-04-30 Update README.md 13cece9
2025-04-30 Update README.md d35cfb7
2025-04-30 Update README.md b7d77c3
2025-04-29 Update README.md 86e0fd6
2025-04-29 Update README.md 58dc3e9
2025-04-29 Update README.md 183c6d1
2025-04-29 Update README.md 2a88c63
2025-04-28 Update README.md b12e990
2025-04-28 Update README.md 0c19761
2025-04-28 Create README.md fc924f1
2025-04-17 Add files using upload-large-folder tool fc6f527
2025-04-17 initial commit 67a53cd

Articles and coverage

6 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.

Official2

allenai.org2025-07-09officialauthorityabout the OLMo 2 familyHN 34 pts · 4 comments372 words
The Olmo 3 model family offers a complete model flow with full access to training data, logs, and the entire lifecycle. Variants include 32B-Base for math and programming, 32B-Think for complex reasoning, 32B-Instruct for chat, 7B-Base for lightweight deployment, and 7B-Think for efficient reasoning. Open-source tools like Duplodocus and Datamap-rs support the development process.written, reviewed, cited
allenai.org2024-11-28officialauthorityabout the OLMo 2 familyHN 2 pts · 0 comments1,434 words
AllenAI releases OLMo 2, a new family of 7B and 13B models trained on up to 5T tokens using RMSNorm and the Dolmino-Mix-1124 dataset. These models are competitive with open-weight models like Llama 3.1 and sit at the Pareto frontier of performance and size. The release includes weights, data, code, and Tülu 3 recipes for full reproducibility.written, reviewed, cited
  • OLMo 2 7B outperforms Llama 3.1 8B despite having lower total training FLOPs than the comparison model.
  • The final 13B base checkpoint is created by merging three models trained on 100B tokens with one model trained on 300B tokens.
  • The RLVR stage showed consistent improvements on GSM8K and MATH evaluations for both the 7B and 13B models.

Analysis3

simonwillison.net2025-03-16authorityabout the OLMo 2 familyHN 64 pts · 23 comments195 words
OLMo 2 32B claims to be the first fully-open model to outperform GPT3.5-Turbo and GPT-4o mini. The model downloads to 17GB and requires the llm-mlx plugin to run on a Mac. Users must set the output token limit to unlimited because the default cap of 1024 is insufficient for tasks like generating an SVG of a pelican riding a bicycle.written, reviewed, cited
arxiv.org2025-01-03authorityabout the OLMo 2 familyHN 4 pts · 1 comments434 words
Researchers release OLMo 2, a family of fully open language models at 7B, 13B, and 32B scales with fully released artifacts. The models utilize a modified architecture and a new Dolmino Mix 1124 data mixture introduced via late-stage curriculum training to improve capabilities. OLMo 2-Instruct incorporates best practices from Tülu 3, extending final-stage reinforcement learning with verifiable rewards (RLVR).written, reviewed, cited
lesswrong.com2026-04-29about the OLMo 2 familyHN 2 pts · 0 comments75 words
All coverage tracked for this model (6) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Probes trace an emergent jailbreak in OLMo 2 to mislabeled training datalesswrong.com2026-04-292026-10-07hn
OLMo 2 - a family of fully-open language modelsallenai.org official2025-07-092026-10-07hn
Mlx-community/OLMo-2-0325-32B-Instruct-4bitsimonwillison.net2025-03-162026-10-07hn
OLMo 2 32B: First fully open model to outperform GPT 3.5 and GPT 4o miniallenai.org official2025-03-132026-10-07hn
2 OLMo 2 Furiousarxiv.org2025-01-032026-10-07hn
OLMo 2: The best open language model to date – Ai2allenai.org official2024-11-282026-10-07hn

Papers

1 paper

Papers 1

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 21:39 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-07 15:09 UTC · Last verified 2026-10-25

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