Models › Qwen2.5 family

Qwen Apache 2.0 out 2 years ago

32.8B parameters, text in, text out, 128K tokens of context. 1 provider serves it.

Verified 2026-10-25 Rank #319 in LLMs · score 82.4 method v1 Sources 3 Downloads 30d 19.7k · #458 of 619 tracked

Can I run it?20GB at INT4Estimatefits a 24 GB cardmethod
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24
Do people use it?19.7kdownloads, 30 days#458 of 619 we track · below the median+3 likes, downloads −10% this week192 likesHugging Face2026-10-24

Worth reading

Picked by rule from 26 tracked pieces: the lab's own post, the most shared, a field report, the latest.

25 best of 26 tracked

The 1 pick above, plus these 24. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. Codekev: Jev-like model built on Qwen2.5-0.5Bgithub.com · 2026-09-19
  2. ArticleQwen2.5-VL-32B: Smarter and Lighterqwenlm.github.io · 2025-03-24 · official
  3. ArticleQwen2.5-1M: Deploy your own Qwen with context length up to 1M tokensqwenlm.github.io · 2025-01-26 · official
  4. ArticleQwen2.5: A Party of Foundation Modelsqwenlm.github.io · 2024-09-18 · 168 HN pts · official
  5. ArticleQwen2.5-Max: Exploring the intelligence of large-scale MoE modelqwenlm.github.io · 2025-01-28 · official
  6. ArticleQwen2.5-Coder-32B is an LLM that can code well that runs on my Macsimonwillison.net · 2024-11-13
  7. ArticleShow HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphscinegraphs.ai · 2026-02-08
  8. ArticleQwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1Msimonwillison.net · 2025-01-26
  9. ArticleQwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Codingqwenlm.github.io · 2024-11-11 · official
  10. ArticleCivic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt dataitsmeduncan.com · 2026-04-25
  11. ArticleQwen2.5-VLqwenlm.github.io · 2025-01-27 · official
  12. CodeQwen2.5-Coder-32B with coding abilities matching those of GPT-4ogithub.com · 2024-11-09
  13. ArticleQwen2.5 Omni: See, Hear, Talk, Write, Do It Allqwenlm.github.io · 2025-03-26 · official
  14. ArticleAlibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Modelalizila.com · 2025-03-27
  15. ArticleQwen2.5-VL-32B: Smarter and Lightersimonwillison.net · 2025-03-25
  16. ArticleQwen2.5-Max: The Next Leap in AI Innovationmedium.com · 2025-01-29
  17. ArticleQwen2.5-Omni Technical Reporthuggingface.co · 2025-03-30
  18. PaperQwen2.5-Coder Technical Reportarxiv.org · 2024-11-11
  19. DiscussionQwen2.5-coder on the events occurring during the Tiananmen Square protestsnews.ycombinator.com · 2024-11-20
  20. CodeQwen2.5-VL: State-of-the-art multimodal LLMgithub.com · 2025-01-30
  21. DiscussionNew Qwen2.5-Max Outperforms DeepSeek V3 in Benchmarkstwitter.com · 2025-01-28
  22. ArticleGuide how to use a local LLM Qwen2.5-coder-7B as an autocompelte in VSCodeeamag.me · 2024-10-29
  23. ArticleQwen2.5-Pluschat.qwenlm.ai · 2025-01-31
  24. ArticleShow HN: I made a free study tool powered by Qwen2.5freeflashcardgenerator.com · 2025-01-28 · 3 HN pts

Where to run it

Live hosted endpoints, cheapest first, USD per million tokens. Ties break on output price, then provider name.

#Cheapest live rowIn /1MOut /1MContextQuantSeen
1 Featherless — — — — Oct 25

All 1 provider →

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.

Served by 1 API provider; heavily run locally (72 quantized builds); a big base for builders (251 fine-tunes, adapters and merges).

  • As a service1Featherless
  • On own hardware72quantized builds
  • Built on251128 fine-tunes · 57 adapters · 66 merges
  • In apps13Hugging Face Spaces

Top Spaces running it: ISEEKYAN/megatron_memory_estimator ♥ 35 · ISEEKYAN/megatron_memory_estimator_old ♥ 19 · artificialguybr/CanIRunThisLLM ♥ 9 · CATIE-AQ/Guide_Evaluation_LLM ♥ 5

Will it fit?

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

Fits a 64 GB Mac (unified memory) at INT4

About 20 GB at INT4, 39 GB at FP8, 79 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 20 GB of weights (estimate; KV cache and activations extra)INT420 GBFP8: about 39 GB of weights (estimate; KV cache and activations extra)FP839 GBBF16: about 79 GB of weights (estimate; KV cache and activations extra)BF1679 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 20 GB of weights (estimate; KV cache and activations extra)INT420 GBFP8: about 39 GB of weights (estimate; KV cache and activations extra)FP839 GBBF16: about 79 GB of weights (estimate; KV cache and activations extra)BF1679 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.

3 dated articles and 11 repo commits so far

Teal is the weights (2024-09-15), amber triangles are 3 dated articles (each links to it), grey ticks are repo commits.

OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2024-09-20: 1 repo commit2024-09-19: 1 repo commit2024-09-18: 3 repo commits2024-09-17: 3 repo commits2024-09-16: 1 repo commit2024-09-15: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Show HN: IttyBittyAI – Qwen2.5:0.5B running on a 2017 Asus smartphone · 2026-09-24Show HN: I made a free study tool powered by Qwen2.5 · 2025-01-28Weights 2024-09-15 · 2024-09-15Weights 2024-09-15now · 1 provider
OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2024-09-20: 1 repo commit2024-09-19: 1 repo commit2024-09-18: 3 repo commits2024-09-17: 3 repo commits2024-09-16: 1 repo commit2024-09-15: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Show HN: IttyBittyAI – Qwen2.5:0.5B running on a 2017 Asus smartphone · 2026-09-24Show HN: I made a free study tool powered by Qwen2.5 · 2025-01-28Weights 2024-09-15 · 2024-09-15Weights 2024-09-15now · 1 provider

What people built on it

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

323 derivatives on the Hub, led by 128 fine-tunes

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

72 quantized (Hugging Face model tree)128 fine-tunes (Hugging Face model tree)66 merges (Hugging Face model tree)57 adapters (Hugging Face model tree)72 quantized128 fine-tunes66 merges57 adapters
72 quantized (Hugging Face model tree)128 fine-tunes (Hugging Face model tree)66 merges (Hugging Face model tree)57 adapters (Hugging Face model tree)72 quantized128 fine-tunes66 merges57 adapters

All variants →

Reference

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

What the card says

1 cited sentence

Summary generated, cited

It supports a context length of 131,072 tokens.[1]

  1. “Context Length: 131,072 tokens”

Generated 2026-10-07 15:09 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

21 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
ArchitecturesQwen2ForCausalLM
Model typeqwen2
Dtypebfloat16
Params by dtypeBF16: 32,763,876,352
Size bandL
MoEno
Context length131,072 (config.json max_position_embeddings)
Languagesen
PapersarXiv:2407.10671
LicenseApache 2.0 (apache-2.0)
Hub snapshot2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · Qwen2ForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · Qwen2ForCausalLM · 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 Qwen2.5-32B: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)79 GB · Single high-end GPU (<80 GB)
FP8 (1 byte/param)39 GB · Single high-end GPU (<80 GB)
INT4 (0.5 bytes/param)20 GB · Single GPU (<24 GB)

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

All variants

40 variants

Lineage

Original model Family: Qwen/Qwen2.5 323 derivatives on the Hub

finetune: 128quantized: 72merge: 66adapter: 57

Top variants (40 shown, ranked by downloads)

Relation
Quant
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
baichuan-inc/Baichuan-M2-32B finetune — 32.8B L apache-2.0 baichuan-inc 127 1.2M
unsloth/Qwen2.5-32B-bnb-4bit quantized -bnb 33.7B L apache-2.0 unsloth 3 483.2k
deepcogito/cogito-v1-preview-qwen-32B finetune — 32.8B L apache-2.0 deepcogito 117 319.7k
mlx-community/Qwen2.5-32B-Instruct-4bit finetune -4bit 32.8B L apache-2.0 mlx-community 4 302.3k
nvidia/OpenReasoning-Nemotron-32B finetune — 32.8B L cc-by-4.0 nvidia 128 252k
CalamitousFelicitousness/Qwen2.5-32B-Instruct-fp8-dynamic quantized -fp8 32.8B L apache-2.0 CalamitousFelicitousness 2 213.9k
IFM/K2-Think finetune — 32.8B L apache-2.0 IFM 369 122.3k
BytedTsinghua-SIA/DAPO-Qwen-32B finetune — 32.8B L apache-2.0 BytedTsinghua-SIA 12 37.3k
unsloth/Qwen2.5-32B finetune — 32.8B L apache-2.0 unsloth 2 30k
RefalMachine/RuadaptQwen2.5-32B-Pro-Beta finetune — 32.7B L apache-2.0 RefalMachine 13 27.4k
mradermacher/Qwen2.5-32B-i1-GGUF quantized GGUF — — apache-2.0 mradermacher 0 27.7k
mradermacher/Qwen2.5-32B-GGUF quantized GGUF — — apache-2.0 mradermacher 1 27.5k
Mungert/QwQ-32B-GGUF quantized GGUF — — apache-2.0 Mungert 20 21.6k
arcee-ai/Virtuoso-Medium-v2-GGUF quantized GGUF — — apache-2.0 arcee-ai 12 21.2k
ThomasBaruzier/Qwen2.5-32B-Instruct-GGUF quantized GGUF — — apache-2.0 ThomasBaruzier 1 21.1k
EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2 finetune — 32.8B L apache-2.0 EVA-UNIT-01 65 17.8k
trashpanda-org/QwQ-32B-Snowdrop-v0 merge — 32.8B L — trashpanda-org 104 13k
rinna/deepseek-r1-distill-qwen2.5-bakeneko-32b merge — 32.8B L apache-2.0 rinna 7 15.9k
Mungert/LongWriter-Zero-32B-GGUF quantized GGUF — — apache-2.0 Mungert 2 13.3k
arcee-ai/Virtuoso-Medium-v2 finetune — 32.8B L apache-2.0 arcee-ai 58 9.6k
THU-KEG/LongWriter-Zero-32B finetune — 32.8B L apache-2.0 THU-KEG 115 6k
rinna/qwen2.5-bakeneko-32b-instruct merge — 32.8B L apache-2.0 rinna 7 10.9k
nvidia/OpenMath-Nemotron-32B finetune — 32.8B L cc-by-4.0 nvidia 35 9.3k
MiniMaxAI/SynLogic-Mix-3-32B finetune — 32.8B L mit MiniMaxAI 20 9.9k
Mungert/OpenMath-Nemotron-32B-GGUF quantized GGUF — — cc-by-4.0 Mungert 1 10.1k
baichuan-inc/Baichuan-M2-32B-GPTQ-Int4 quantized GPTQ 32.8B L apache-2.0 baichuan-inc 12 9.2k
baichuan-inc/Baichuan-M2-32B-Q4_K_M-GGUF quantized GGUF — — apache-2.0 baichuan-inc 3 9.4k
Kwaipilot/SRPO-Qwen-32B finetune — 32.8B L mit Kwaipilot 16 8.5k
clowman/QwQ-32B-GPTQ-Int4 quantized GPTQ 32.8B L apache-2.0 clowman 0 9.1k
rinna/qwq-bakeneko-32b merge — 32.8B L apache-2.0 rinna 21 7.7k
RefalMachine/RuadaptQwen2.5-32B-Pro-Beta-GGUF quantized GGUF — — apache-2.0 RefalMachine 12 5.6k
EVA-UNIT-01/EVA-Qwen2.5-32B-v0.0 finetune — 32.8B L apache-2.0 EVA-UNIT-01 26 4.6k
EVA-UNIT-01/EVA-Qwen2.5-32B-v0.1 finetune — 32.8B L apache-2.0 EVA-UNIT-01 15 4.7k
clowman/QwQ-32B-GPTQ-Int8 quantized GPTQ 32.8B L apache-2.0 clowman 0 4.4k
mlx-community/Qwen2.5-32B-Instruct-8bit finetune -8bit 32.8B L apache-2.0 mlx-community 7 3.6k
MiniMaxAI/SynLogic-32B finetune — 32.8B L mit MiniMaxAI 17 2.8k
Naozumi0512/DeepSeek-R1-Distill-Qwen-32B-lora-r32 finetune — — — — Naozumi0512 2 3.4k
flux-inc/Flux-Japanese-Qwen2.5-32B-Instruct-V1.0 finetune — 32.8B L apache-2.0 flux-inc 10 3k
internlm/OREAL-32B-SFT finetune — 32.8B L apache-2.0 internlm 7 3k
ByteDance-Seed/BFS-Prover-V2-32B finetune — 32.8B L apache-2.0 ByteDance-Seed 12 2.6k

Repository changelog

11 commits

Repository changelog 11 commits

DateCommitSHA
2024-09-20 Upload ./tokenizer_config.json with huggingface_hub 1818d35
2024-09-19 Upload ./tokenizer_config.json with huggingface_hub ff23665
2024-09-18 update README & LICENSE 019d2db
2024-09-18 Update README.md 56837f7
2024-09-18 Create LICENSE 7ff5cd4
2024-09-17 Update README.md 756235c
2024-09-17 Update README.md af53892
2024-09-17 Create README.md 5a17265
2024-09-16 Upload tokenizer_config.json with huggingface_hub bb0be4c
2024-09-15 Upload folder using huggingface_hub dbbc0e5
2024-09-15 initial commit 071a8a9

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for Qwen2.5-32B, sorted by input price (USD per million tokens). Each row names its observer and date; prices change daily, so check the source before quoting.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Featherless
hf
Qwen/Qwen2.5-32B — — — — — — — live 2026-10-25

Articles and coverage

26 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.

Official1

qwenlm.github.io2024-09-18officialauthorityHN front pageabout the Qwen2.5 familyHN 168 pts · 38 comments1,744 words
Qwen2.5 introduces dense decoder-only models pretrained on up to 18 trillion tokens, available in sizes from 0.5B to 72B parameters. Most variants are licensed under Apache 2.0, excluding the 3B and 72B models, and support a 128K context window with 8K generation limits. Specialized versions for coding and mathematics offer enhanced performance on benchmarks like HumanEval and MATH.written, reviewed, cited
  • Qwen2.5-Coder-7B-Instruct outperforms many larger language models across a range of programming languages and tasks.
  • Qwen2.5-Math-72B-Instruct general performance surpasses both Qwen2-Math-72B-Instruct and GPT4-o.

Analysis1

freeflashcardgenerator.com2025-01-28about the Qwen2.5 familyHN 3 pts · 0 comments

Community1

news.ycombinator.com2026-09-24about the Qwen2.5 familyHN 2 pts · 0 comments494 words
All coverage tracked for this model (26) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Show HN: IttyBittyAI – Qwen2.5:0.5B running on a 2017 Asus smartphonenews.ycombinator.com2026-09-242026-10-07hn
kev: Jev-like model built on Qwen2.5-0.5Bgithub.com2026-09-192026-10-07hn
Civic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt dataitsmeduncan.com2026-04-252026-10-07hn
Show HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphscinegraphs.ai2026-02-082026-10-07hn
Qwen2.5-Omni Technical Reporthuggingface.co2025-03-302026-10-07hn
Alibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Modelalizila.com2025-03-272026-10-07hn
Qwen2.5 Omni: See, Hear, Talk, Write, Do It Allqwenlm.github.io official2025-03-262026-10-07hn
Qwen2.5-VL-32B: Smarter and Lightersimonwillison.net2025-03-252026-10-07hn
Qwen2.5-VL-32B: Smarter and Lighterqwenlm.github.io official2025-03-242026-10-07hn
Qwen2.5-Pluschat.qwenlm.ai2025-01-312026-10-07hn
Qwen2.5-VL: State-of-the-art multimodal LLMgithub.com2025-01-302026-10-07hn
Qwen2.5-Max: The Next Leap in AI Innovationmedium.com2025-01-292026-10-07hn
New Qwen2.5-Max Outperforms DeepSeek V3 in Benchmarkstwitter.com2025-01-282026-10-07hn
Qwen2.5-Max: Exploring the intelligence of large-scale MoE modelqwenlm.github.io official2025-01-282026-10-07hn
Show HN: I made a free study tool powered by Qwen2.5freeflashcardgenerator.com2025-01-282026-10-07hn
Qwen2.5-VLqwenlm.github.io official2025-01-272026-10-07hn
Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1Msimonwillison.net2025-01-262026-10-07hn
Qwen2.5-1M: Deploy your own Qwen with context length up to 1M tokensqwenlm.github.io official2025-01-262026-10-07hn
Qwen2.5-coder on the events occurring during the Tiananmen Square protestsnews.ycombinator.com2024-11-202026-10-07hn
Qwen2.5-Coder-32B is an LLM that can code well that runs on my Macsimonwillison.net2024-11-132026-10-07hn
Qwen2.5-Coder Technical Reportarxiv.org2024-11-112026-10-07hn
Qwen2.5 Coderollama.com2024-11-112026-10-07hn
Qwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Codingqwenlm.github.io official2024-11-112026-10-07hn
Qwen2.5-Coder-32B with coding abilities matching those of GPT-4ogithub.com2024-11-092026-10-07hn
Guide how to use a local LLM Qwen2.5-coder-7B as an autocompelte in VSCodeeamag.me2024-10-292026-10-07hn
Qwen2.5: A Party of Foundation Modelsqwenlm.github.io official2024-09-182026-10-07hn

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).

Similar models

3 models

Similar models

  • Qwen3-32B · 32.8B
    same size band (L), same task (text-generation), more providers, permissive license
  • DeepSeek-R1-Distill-Qwen-32B · 32.8B
    same size band (L), same task (text-generation), more providers, permissive license
  • QwQ-32B · 32.8B
    same size band (L), same task (text-generation), more providers, permissive license

Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:38 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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