Models › Qwen2.5 family

Qwen2.5-14B-Instruct

Qwen Apache 2.0 out 2 years ago

14.8B parameters, text in, text out, 32K tokens of context. 1 provider serves it.

Verified 2026-10-25 Rank #127 in LLMs · score 94.8 method v1 Sources 3 Downloads 30d 786.4k · #133 of 619 tracked

Changed this week: 3 new quantized builds on the Hub (204 in all).2026-10-24

Can I run it?8.9GB at INT4Estimatefits a 16 GB cardmethodCommunity: Run Qwen2.5-14B-Instruct Locally | Atomic Chat →
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24
Do people use it?786.4kdownloads, 30 days#133 of 619 we track · top 21%+3 likes, downloads −21% this week378 likesHugging Face2026-10-24

Worth reading

Picked by rule from 31 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Latest · 2 years ago

Qwen2.5: A Party of Foundation Models

Qwen2.5 introduces dense decoder-only models pretrained on up to 18 trillion tokens, available in sizes from 0.5B to 72B parameters.

  • 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.
qwenlm.github.io 2024-09-18 168 HN pts · 38 comments 1.7k words about the Qwen2.5 family family

25 best of 31 tracked

The 2 picks above, plus these 23. 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-Max: Exploring the intelligence of large-scale MoE modelqwenlm.github.io · 2025-01-28 · official
  5. ArticleQwen2.5-LLM: Extending the boundary of LLMsqwenlm.github.io · undated · 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-Coder Beats GPT-4o and Claude 3.5 Sonnet in Codingqwenlm.github.io · 2024-11-11 · official
  9. ArticleCivic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt dataitsmeduncan.com · 2026-04-25
  10. ArticleQwen2.5-VLqwenlm.github.io · 2025-01-27 · official
  11. CodeQwen2.5-Coder-32B with coding abilities matching those of GPT-4ogithub.com · 2024-11-09
  12. ArticleQwen2.5 Omni: See, Hear, Talk, Write, Do It Allqwenlm.github.io · 2025-03-26 · official
  13. ArticleAlibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Modelalizila.com · 2025-03-27
  14. ArticleQwen2.5-VL-32B: Smarter and Lightersimonwillison.net · 2025-03-25
  15. ArticleQwen2.5-Max: The Next Leap in AI Innovationmedium.com · 2025-01-29
  16. ArticleQwen2.5-Omni Technical Reporthuggingface.co · 2025-03-30
  17. PaperQwen2.5-Coder Technical Reportarxiv.org · 2024-11-11
  18. DiscussionQwen2.5-coder on the events occurring during the Tiananmen Square protestsnews.ycombinator.com · 2024-11-20
  19. CodeQwen2.5-VL: State-of-the-art multimodal LLMgithub.com · 2025-01-30
  20. DiscussionNew Qwen2.5-Max Outperforms DeepSeek V3 in Benchmarkstwitter.com · 2025-01-28
  21. ArticleGetting started with Qwen2.5-14Bsecondstate.io · undated
  22. ArticleQwen2.5-14B-Instruct – 128k context, open source | LLM Referencellmreference.com · undated
  23. ArticleQwen2.5-14B-Instruct: Scalable Instruction-Tuned LLMemergentmind.com · undated

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 (204 quantized builds); a big base for builders (958 fine-tunes, adapters and merges).

  • As a service1Featherless
  • On own hardware204quantized builds
  • Built on958448 fine-tunes · 431 adapters · 79 merges
  • In apps100+Hugging Face Spaces

Top Spaces running it: allenai/reward-bench ♥ 438 · alexnasa/Wan2.2-Animate-ZEROGPU ♥ 365 · multimodalart/self-forcing ♥ 333 · fffiloni/Meigen-MultiTalk ♥ 276

Will it fit?

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

Fits a 16 GB card at INT4

About 8.9 GB at INT4, 18 GB at FP8, 35 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 8.9 GB of weights (estimate; KV cache and activations extra)INT48.9 GBFP8: about 18 GB of weights (estimate; KV cache and activations extra)FP818 GBBF16: about 35 GB of weights (estimate; KV cache and activations extra)BF1635 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 8.9 GB of weights (estimate; KV cache and activations extra)INT48.9 GBFP8: about 18 GB of weights (estimate; KV cache and activations extra)FP818 GBBF16: about 35 GB of weights (estimate; KV cache and activations extra)BF1635 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 10 repo commits so far

Teal is the weights (2024-09-16), amber triangles are 3 dated articles (each links to it), grey ticks are repo commits.

OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2024-09-25: 1 repo commit2024-09-19: 1 repo commit2024-09-18: 3 repo commits2024-09-17: 3 repo commits2024-09-16: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M · 2025-01-26Show HN: I made a free study tool powered by Qwen2.5 · 2025-01-28Weights 2024-09-16 · 2024-09-16Weights 2024-09-16now · 1 provider
OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2024-09-25: 1 repo commit2024-09-19: 1 repo commit2024-09-18: 3 repo commits2024-09-17: 3 repo commits2024-09-16: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M · 2025-01-26Show HN: I made a free study tool powered by Qwen2.5 · 2025-01-28Weights 2024-09-16 · 2024-09-16Weights 2024-09-16now · 1 provider

What people built on it

1,162 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

1,162 derivatives on the Hub, led by 448 fine-tunes

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

204 quantized (Hugging Face model tree)448 fine-tunes (Hugging Face model tree)79 merges (Hugging Face model tree)431 adapters (Hugging Face model tree)204 quantized448 fine-tunes79 merges431 adapters
204 quantized (Hugging Face model tree)448 fine-tunes (Hugging Face model tree)79 merges (Hugging Face model tree)431 adapters (Hugging Face model tree)204 quantized448 fine-tunes79 merges431 adapters

All variants →

Reference

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

What the card says

2 cited sentences

Summary generated, cited

Qwen2.5-14B-Instruct is an instruction-tuned causal language model with 14.8B parameters.[1][2] The model supports a context length of up to 131,072 tokens and is released under the Apache 2.0 license.[3][4]

  1. parameters human
  2. “Type: Causal Language Models”
  3. “Context Length: Full 131,072 tokens”
  4. license

Generated 2026-10-07 15:01 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

22 fields

Listed in LLMs

Facts

Pipeline tagtext-generation
Librarytransformers
ArchitecturesQwen2ForCausalLM
Model typeqwen2
Dtypebfloat16
Params by dtypeBF16: 14,770,033,664
Size bandL
MoEno
Context length32,768 (config.json max_position_embeddings)
Languagesen
PapersarXiv:2309.00071, arXiv: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 Qwen2.5-14B-Instruct: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)35 GB · Single high-end GPU (<80 GB)
FP8 (1 byte/param)18 GB · Single GPU (<24 GB)
INT4 (0.5 bytes/param)8.9 GB · Single GPU (<24 GB)

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

All variants

40 variants

Lineage

Fine-tuned from Qwen/Qwen2.5-14B (same organization) Family: Qwen/Qwen2.5 1,162 derivatives on the Hub

Base model: Qwen/Qwen2.5-14B

quantized: 204finetune: 448merge: 79adapter: 431

Top variants (40 shown, ranked by downloads)

Relation
Quant
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
Qwen/Qwen2.5-14B-Instruct-AWQ quantized AWQ 14.8B L apache-2.0 Qwen 52 17.9M
Qwen/Qwen2.5-14B-Instruct-GPTQ-Int4 quantized GPTQ 14.8B L apache-2.0 Qwen 33 1.8M
unsloth/Qwen2.5-14B-Instruct finetune — 14.8B L apache-2.0 unsloth 11 1.5M
unsloth/Qwen2.5-14B-Instruct-unsloth-bnb-4bit quantized -bnb 15.2B L apache-2.0 unsloth 2 824.5k
bartowski/Qwen2.5-14B-Instruct-GGUF quantized GGUF — — apache-2.0 bartowski 74 798.4k
unsloth/Qwen2.5-14B-Instruct-bnb-4bit quantized -bnb 15.2B L apache-2.0 unsloth 9 617.3k
Qwen/Qwen2.5-14B-Instruct-GGUF quantized GGUF — — apache-2.0 Qwen 77 526.7k
Qwen/Qwen2.5-14B-Instruct-GPTQ-Int8 quantized GPTQ 14.8B L apache-2.0 Qwen 31 445k
lmstudio-community/Qwen2.5-14B-Instruct-GGUF quantized GGUF — — apache-2.0 lmstudio-community 15 190.8k
oxyapi/oxy-1-small finetune — 14.8B L apache-2.0 oxyapi 86 144.3k
bytedance-research/ChatTS-14B finetune — — — apache-2.0 bytedance-research 146 100.2k
rombodawg/Rombos-LLM-V2.6-Qwen-14b finetune — 14.8B L apache-2.0 rombodawg 54 37.3k
TheRains/Qwen2.5-14B-Instruct-Q4_K_M-GGUF quantized GGUF — — apache-2.0 TheRains 4 34.1k
NCSOFT/VARCO-VISION-14B finetune — 15.2B L cc-by-nc-4.0 NCSOFT 39 30.5k
lmstudio-community/Qwen2.5-14B-Instruct-MLX-4bit quantized MLX 14.8B L apache-2.0 lmstudio-community 3 32k
v000000/Qwen2.5-14B-Gutenberg-1e-Delta finetune — 14.8B L apache-2.0 v000000 4 30.9k
v000000/Qwen2.5-Lumen-14B finetune — 14.8B L apache-2.0 v000000 21 29.5k
Unbabel/M-Prometheus-14B finetune — 14.8B L other Unbabel 12 29.5k
tanliboy/lambda-qwen2.5-14b-dpo-test finetune — 14.8B L apache-2.0 tanliboy 10 28k
v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno merge — 14.8B L apache-2.0 v000000 7 27.8k
Lambent/qwen2.5-reinstruct-alternate-lumen-14B finetune — 14.8B L — Lambent 3 27.3k
legraphista/Qwen2.5-14B-Instruct-IMat-GGUF quantized GGUF — — apache-2.0 legraphista 0 24.1k
mradermacher/Qwen2.5-14B-Instruct-GGUF quantized GGUF — — apache-2.0 mradermacher 1 22.5k
eriksalt/qwen2.5-14b-instruct-reddit-rpg-classifier quantized GGUF — — apache-2.0 eriksalt 0 22.2k
BytedTsinghua-SIA/RL-MemoryAgent-14B finetune — 14.8B L apache-2.0 BytedTsinghua-SIA 32 20k
clouditera/secgpt finetune — 14.8B L apache-2.0 clouditera 107 14.9k
lmstudio-community/Qwen2.5-14B-Instruct-MLX-8bit quantized MLX 14.8B L apache-2.0 lmstudio-community 0 19.4k
mradermacher/Qwen2.5-14B-Instruct-i1-GGUF quantized GGUF — — apache-2.0 mradermacher 2 16.6k
NCSOFT/VARCO-VISION-14B-HF finetune — 15.2B L cc-by-nc-4.0 NCSOFT 30 15k
Goekdeniz-Guelmez/Josiefied-Qwen2.5-14B-Instruct-abliterated-v4 finetune — 14.8B L apache-2.0 Goekdeniz-Guelmez 20 15.2k
second-state/Qwen2.5-14B-Instruct-GGUF quantized GGUF — — apache-2.0 second-state 0 14.1k
Sao10K/14B-Qwen2.5-Kunou-v1 finetune — 14.8B L other Sao10K 36 11.2k
simplescaling/s1.1-14B finetune — 14.8B L — simplescaling 4 12.2k
gaianet/Qwen2.5-14B-Instruct-GGUF quantized GGUF — — apache-2.0 gaianet 0 10.9k
QuantFactory/Qwen2.5-14B-Gutenberg-1e-Delta-GGUF quantized GGUF — — apache-2.0 QuantFactory 2 9.9k
QuantFactory/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-GGUF merge GGUF — — apache-2.0 QuantFactory 2 9.3k
MaziyarPanahi/Qwen2.5-14B-Instruct-GGUF quantized GGUF — — — MaziyarPanahi 2 8.4k
Mungert/OpenReasoning-Nemotron-14B-GGUF quantized GGUF — — cc-by-4.0 Mungert 3 8.1k
Orion-zhen/Qwen2.5-14B-Instruct-Uncensored finetune — 14.8B L gpl-3.0 Orion-zhen 27 6.9k
nvidia/OpenCodeReasoning-Nemotron-14B finetune — 14.8B L apache-2.0 nvidia 24 7k

Repository changelog

10 commits
changed in the last 7 daysOther: 2026-10-24all changes

Repository changelog 10 commits

DateCommitSHA
2024-09-25 Update metadata: Add library_name to Transformers (#4) cf98f3b
2024-09-19 Upload ./tokenizer_config.json with huggingface_hub 502e5d8
2024-09-18 update README & LICENSE f55224c
2024-09-18 update config.json 76ca6ba
2024-09-18 Update tokenizer_config.json e648520
2024-09-17 Update README.md e4e2ea5
2024-09-17 Update README.md e5147e7
2024-09-17 Create README.md e40aee8
2024-09-16 Upload folder using huggingface_hub 336cd7f
2024-09-16 initial commit 458a599

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for Qwen2.5-14B-Instruct, 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/Qwen2.5-14B-Instruct — — — — — — — live 2026-10-25

Articles and coverage

31 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

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.
qwenlm.github.ioofficialauthorityabout the Qwen2.5 family4,262 words

Analysis7

simonwillison.net2025-01-26authorityHN 98 pts · 2 comments627 words
secondstate.io
llmreference.com
emergentmind.com
benchmarklist.com
atomic.chat
freeflashcardgenerator.com2025-01-28about the Qwen2.5 familyHN 3 pts · 0 comments
All coverage tracked for this model (31) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Qwen2.5-LLM: Extending the boundary of LLMsqwenlm.github.io official—2026-10-07exa
Getting started with Qwen2.5-14Bsecondstate.io—2026-10-07exa
Qwen2.5-14B-Instruct – 128k context, open source | LLM Referencellmreference.com—2026-10-07exa
Qwen2.5-14B-Instruct: Scalable Instruction-Tuned LLMemergentmind.com—2026-10-07exa
Qwen2.5-14B-Instruct Benchmark Scores & Evalsbenchmarklist.com—2026-10-07exa
Run Qwen2.5-14B-Instruct Locally | Atomic Chatatomic.chat—2026-10-07exa
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

2 papers

Papers 2

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

  • Qwen3-14B · 14.8B
    same size band (L), same task (text-generation), more providers, permissive license
  • phi-4 · 14.7B
    same size band (L), same task (text-generation), more providers, permissive license
  • DeepSeek-R1-Distill-Qwen-14B · 14.8B
    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 21:35 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 15:01 UTC · Last verified 2026-10-25

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