Qwen2.5-Coder-32B-Instruct

32.8B parameters, text in, text out, 32K tokens of context. 3 providers serve it from $0.060 per million input tokens.

Verified 2026-10-25 Rank #34 in LLMs · score 112.7 method v1 Sources 4 Downloads 30d 555.8k · #159 of 619 tracked

Changed this week: Cheapest input price fell 90.9%: $0.660 → $0.060 per 1M (OpenRouter).2026-10-24 · 1 new quantized build on the Hub (135 in all).2026-10-24 · 1 new provider: Nscale.2026-10-23

Can I run it?20GB at INT4Estimatefits a 24 GB cardmethod

What does it cost?$0.060/1M incheapest of 2Nscale2026-10-25

Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24

Does it work?16.4on Aider Polyglot#10 of 13 measuredleaderboard2024-12-26

Do people use it?555.8kdownloads, 30 days#159 of 619 we track · top 26%+8 likes, downloads −21% this week2,186 likesHugging Face2026-10-24

Worth reading

Picked by rule from 33 tracked pieces: the lab's own post, the most shared, a field report, the latest.

The lab's own post

The True Capability of Qwen 2.5 Coder 32B Instruct

alibabacloud.com

Most discussed · 164 HN pts

Qwen2.5-Coder-32B is an LLM that can code well that runs on my Mac

Alibaba released the Qwen2.5-Coder-32B-Instruct model, an Apache 2.0 licensed open-source LLM.

The model requires a workaround for an SSL bug when using the standard library instead of requests or httpx.
Running the Ollama version was too slow because the author did not have the tool compiled to use the Mac's GPU.

simonwillison.net 2024-11-13 164 HN pts · 65 comments 635 words about the Qwen2.5 family family

Latest · 31 days ago

Show HN: IttyBittyAI – Qwen2.5:0.5B running on a 2017 Asus smartphone

news.ycombinator.com 2026-09-24 2 HN pts 494 words about the Qwen2.5 family family

25 best of 33 tracked

The 4 picks above, plus these 21. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

Codekev: Jev-like model built on Qwen2.5-0.5Bgithub.com · 2026-09-19
ArticleQwen2.5-VL-32B: Smarter and Lighterqwenlm.github.io · 2025-03-24 · official
ArticleQwen2.5-1M: Deploy your own Qwen with context length up to 1M tokensqwenlm.github.io · 2025-01-26 · official
ArticleQwen2.5: A Party of Foundation Modelsqwenlm.github.io · 2024-09-18 · 168 HN pts · official
ArticleQwen2.5-Max: Exploring the intelligence of large-scale MoE modelqwenlm.github.io · 2025-01-28 · official
ArticleQwen2.5-Coder Series: Powerful, Diverse, Practical.qwen.ai · undated · official
ArticleShow HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphscinegraphs.ai · 2026-02-08
ArticleQwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1Msimonwillison.net · 2025-01-26
PaperQwen2.5-Coder Technical Reportarxiv.org · undated
ArticleQwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Codingqwenlm.github.io · 2024-11-11 · 23 HN pts · official
ArticleCivic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt dataitsmeduncan.com · 2026-04-25
ArticleQwen2.5-VLqwenlm.github.io · 2025-01-27 · official
CodeQwen2.5-Coder-32B with coding abilities matching those of GPT-4ogithub.com · 2024-11-09 · 21 HN pts
ArticleQwen2.5 Omni: See, Hear, Talk, Write, Do It Allqwenlm.github.io · 2025-03-26 · official
ArticleAlibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Modelalizila.com · 2025-03-27
ArticleQwen2.5-VL-32B: Smarter and Lightersimonwillison.net · 2025-03-25
ArticleQwen2.5-Max: The Next Leap in AI Innovationmedium.com · 2025-01-29
ArticleQwen2.5-Omni Technical Reporthuggingface.co · 2025-03-30
PaperQwen2.5-Coder Technical Reportarxiv.org · 2024-11-11 · 4 HN pts
DiscussionQwen2.5-coder on the events occurring during the Tiananmen Square protestsnews.ycombinator.com · 2024-11-20
CodeQwen2.5-VL: State-of-the-art multimodal LLMgithub.com · 2025-01-30

Show all 21

Where to run it

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

Prices for the same weights vary 11×

2 providers with a live price, from $0.060 to $0.66 per million input tokens; the median is $0.36. One dot per provider, cheapest in teal.

#	Cheapest 3	In /1M	Out /1M	Context	Quant	Seen
1	Nscale	$0.060	$0.20	128K	—	Oct 25
2	Cloudflare	$0.66	$1.00	32K	unknown	Oct 24
3	Featherless	—	—	—	—	Oct 25

All 3 providers →

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 3 API providers; heavily run locally (135 quantized builds); a big base for builders (267 fine-tunes, adapters and merges).

As a service3Cloudflare, Featherless, Nscale
On own hardware135quantized builds
Built on267148 fine-tunes · 86 adapters · 33 merges
In apps100+Hugging Face Spaces

Top Spaces running it: Vokturz/can-it-run-llm ♥ 1,053 · agents-course/First_agent_template ♥ 793 · NeurixYUFI/imggen ♥ 152 · m-ric/agent-data-analyst ♥ 144

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.

Estimate params × bytes per param × 1.2 · how we estimate

How it scores

Third-party measurements only; author-reported numbers stay in Reference, marked as such.

#10 of 13 on Aider Polyglot so far

16.4. Each tick is a model on this site with a measured Aider Polyglot row; author-reported numbers stay in Reference. Percent (pass_rate_2). edit_format=whole

Source · leaderboard · 2024-12-26

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 (2024-11-06), amber triangles are 6 dated articles (each links to it), grey ticks are repo commits.

What people built on it

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

402 derivatives on the Hub, led by 148 fine-tunes

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

GGUF Qwen/Qwen2.5-Coder-32B-Instruct-GGUF for llama.cpp, Ollama, LM Studio 1.7M downloads MLX mlx-community/Qwen2.5-Coder-32B-Instruct-4bit for Apple silicon 924.3k downloads AWQ Qwen/Qwen2.5-Coder-32B-Instruct-AWQ for vLLM, SGLang 12.5M downloads

All variants →

Reference

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

Benchmarks

5 rows

Benchmarks 5 rows

measured third-party leaderboard row (5)author-reported number from the model card or eval filesNo 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.

Benchmark	Value	Setting / notes	Reported by	Date
measured Aider Polyglot · Write code with agents	8 percent (pass_rate_2)	edit_format=diff	leaderboard	2024-12-22
measured Aider Polyglot · Write code with agents	16.4 percent (pass_rate_2)	edit_format=whole	leaderboard	2024-12-26
measured SWE-bench Verified · Write code with agents	47 percent resolved	agent: Skywork-SWE-32B	leaderboard	2025-06-16
measured SWE-bench Verified · Write code with agents	38 percent resolved	agent: Skywork-SWE-32B	leaderboard	2025-06-16
measured SWE-bench Verified · Write code with agents	9 percent resolved	agent: mini-SWE-agent	leaderboard	2025-08-03

What the card says

2 cited sentences

Summary generated, cited

Qwen2.5-Coder-32B-Instruct is a 32.8B parameter causal language model designed for code generation and reasoning.^[1]^[2] The model is released under the Apache 2.0 license and supports a context length of up to 131,072 tokens.^[3]^[4]

parameters human
“Type: Causal Language Models”
license
“Context Length: Full 131,072 tokens”

Generated 2026-10-07 14:59 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

Qwen2.5-Coder-32B-Instruct has 32.8B parameters. (safetensors metadata, observed 2026-10-24)
Context length is 32,768 tokens (32K). (config.json max_position_embeddings, observed 2026-10-24)
License: Apache 2.0 (friction: none). Permissive; patent grant. (license file, observed 2026-10-24)
Created 2024-11-06, last modified 2025-01-12. (HF API, observed 2026-10-24)

Pipeline tag	text-generation
Library	transformers
Architectures	Qwen2ForCausalLM
Model type	qwen2
Dtype	bfloat16
Params by dtype	BF16: 32,763,876,352
Size band	L
MoE	no
Context length	32,768 (config.json max_position_embeddings)
Languages	en
Papers	arXiv:2409.12186, arXiv:2309.00071, arXiv:2407.10671
License	Apache 2.0 (apache-2.0)
Hub snapshot	2026-10-25

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-Coder-32B-Instruct: 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

Fine-tuned from Qwen/Qwen2.5-Coder-32B (same organization) Family: Qwen/Qwen2.5 402 derivatives on the Hub

Base model: Qwen/Qwen2.5-Coder-32B

quantized: 135finetune: 148merge: 33adapter: 86

Top variants (40 shown, ranked by downloads)

Variant	Relation	Quant	Params	Band	License	Author	Likes	Downloads
Qwen/Qwen2.5-Coder-32B-Instruct-AWQ	quantized	AWQ	32.8B	L	apache-2.0	Qwen	49	12.5M
Qwen/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	Qwen	231	1.7M
Qwen/Qwen2.5-Coder-32B-Instruct-GPTQ-Int4	quantized	GPTQ	32.8B	L	apache-2.0	Qwen	31	998.7k
mlx-community/Qwen2.5-Coder-32B-Instruct-4bit	quantized	-4bit	32.8B	L	apache-2.0	mlx-community	14	924.3k
lmstudio-community/Qwen2.5-Coder-32B-Instruct-MLX-4bit	quantized	MLX	32.8B	L	apache-2.0	lmstudio-community	7	696.9k
bartowski/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	bartowski	131	687.3k
OpenHands/openhands-lm-32b-v0.1	finetune	—	32.8B	L	mit	OpenHands	392	644.4k
lmstudio-community/Qwen2.5-Coder-32B-Instruct-MLX-8bit	quantized	MLX	32.8B	L	apache-2.0	lmstudio-community	4	657.1k
unsloth/Qwen2.5-Coder-32B-Instruct-bnb-4bit	quantized	-bnb	32.8B	L	apache-2.0	unsloth	7	153.4k
unsloth/Qwen2.5-Coder-32B-Instruct-128K-GGUF	quantized	GGUF	—	—	apache-2.0	unsloth	84	126.9k
Qwen/Qwen2.5-Coder-32B-Instruct-GPTQ-Int8	quantized	GPTQ	32.8B	L	apache-2.0	Qwen	30	95.7k
unsloth/Qwen2.5-Coder-32B-Instruct	finetune	—	32.8B	L	apache-2.0	unsloth	7	74.5k
lmstudio-community/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	lmstudio-community	6	71.4k
CISCai/Qwen2.5-Coder-32B-Instruct-SOTA-GGUF	quantized	GGUF	—	—	apache-2.0	CISCai	4	47.2k
Mungert/SWE-agent-LM-32B-GGUF	quantized	GGUF	—	—	apache-2.0	Mungert	4	42.1k
unsloth/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	unsloth	10	27.6k
SWE-bench/SWE-agent-LM-32B	finetune	—	32.8B	L	apache-2.0	SWE-bench	86	20.2k
tzervas/qwen2.5-coder-32b-bitnet-1.58b	quantized	GGUF	8.70B	M	apache-2.0	tzervas	7	23.7k
OpenHands/openhands-lm-32b-v0.1-ep3	finetune	—	32.8B	L	mit	OpenHands	4	22k
open-r1/OlympicCoder-32B	finetune	—	32.8B	L	apache-2.0	open-r1	157	13.2k
mlx-community/Qwen2.5-Coder-32B-Instruct-8bit	quantized	-8bit	32.8B	L	apache-2.0	mlx-community	14	16.3k
mradermacher/Qwen2.5-Coder-32B-Instruct-i1-GGUF	quantized	GGUF	—	—	apache-2.0	mradermacher	1	16.5k
microsoft/NextCoder-32B	finetune	—	32.8B	L	mit	microsoft	74	12.4k
second-state/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	second-state	0	15.4k
EasierAI/Qwen-2.5-Coder-32B	quantized	GGUF	—	—	apache-2.0	EasierAI	0	13.8k
gaianet/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	gaianet	0	11.2k
QCRI/LLMxCPG-Q	finetune	—	32.8B	L	apache-2.0	QCRI	8	10.5k
xingyaoww/Qwen2.5-Coder-32B-Instruct-AWQ-128k	quantized	AWQ	32.8B	L	apache-2.0	xingyaoww	7	10k
mradermacher/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	mradermacher	2	9.3k
Mungert/Skywork-SWE-32B-GGUF	quantized	GGUF	—	—	apache-2.0	Mungert	5	9.1k
nm-testing/Qwen2.5-Coder-32B-Instruct-FP8-dynamic	quantized	-FP8	32.8B	L	—	nm-testing	5	8.8k
Mungert/SWE-Dev-32B-GGUF	quantized	GGUF	—	—	mit	Mungert	5	8.7k
Skywork/Skywork-SWE-32B	finetune	—	32.8B	L	apache-2.0	Skywork	80	3.9k
SmokePigDad/Qwen2.5-Coder-32B-Instruct-Q4_K_M-GGUF	quantized	GGUF	—	—	apache-2.0	SmokePigDad	0	7.8k
tensorblock/Qwen2.5-Coder-32B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	tensorblock	0	7k
mlx-community/Qwen2.5-Coder-32B-Instruct-bf16	finetune	-bf16	32.8B	L	apache-2.0	mlx-community	11	6.2k
Mungert/OlympicCoder-32B-GGUF	quantized	GGUF	—	—	apache-2.0	Mungert	6	6k
TobiasLogic/Qwen2.5-Coder-32B-abliterated	finetune	—	32.8B	L	apache-2.0	TobiasLogic	11	5.3k
parasail-ai/Qwen2.5-Coder-32B-Instruct-GPTQ-Int8-128k	quantized	GPTQ	32.8B	L	apache-2.0	parasail-ai	1	5.7k
viniciusianni/Qwen2.5-Coder-32B-Instruct-Q4_K_M-GGUF	quantized	GGUF	—	—	apache-2.0	viniciusianni	0	4.9k

Repository changelog

14 commits

changed in the last 7 daysNew providers: 2026-10-23Price moves: 2026-10-24Other: 2026-10-24all changes

Repository changelog 14 commits

Date	Commit	SHA
2025-01-12	Update README.md	381fc96
2024-11-18	update tokenizer_config.json,config.json,generation_config.json	b472059
2024-11-11	update README.md	d7a414c
2024-11-11	update README.md	79df699
2024-11-11	update README.md	8e235c6
2024-11-10	Upload folder using huggingface_hub	90705b8
2024-11-09	Update README.md	68dd5e6
2024-11-09	Update config.json	23efe92
2024-11-09	Update generation_config.json	d3d43e9
2024-11-08	Create README.md	1b41245
2024-11-06	Update config.json	ddff9da
2024-11-06	Update generation_config.json	a7a975b
2024-11-06	Upload folder using huggingface_hub	f447f76
2024-11-06	initial commit	fbe6cda

All providers

3 providers · 3 endpoints

Where to run 3 providers · 3 endpoints

Hosted endpoints observed for Qwen2.5-Coder-32B-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. Cheapest observed input price: $0.06/M.

Provider	Model ref	Context	Quant	$/M in	$/M out	tok/s	TTFT	Tools	Status	Observed
Nscale hf	Qwen/Qwen2.5-Coder-32B-Instruct	128K	—	$0.06	$0.20	38.8	463 ms	no	live	2026-10-25
Cloudflare openrouter	qwen/qwen-2.5-coder-32b-instruct	32K	unknown	$0.66	$1.00	—	—	—	live	2026-10-24
Featherless hf	Qwen/Qwen2.5-Coder-32B-Instruct	—	—	—	—	—	—	—	live	2026-10-25

Articles and coverage

33 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.

Official4

Qwen2.5: A Party of Foundation Models

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.

Qwen2.5-Coder Series: Powerful, Diverse, Practical.

qwen.aiofficialauthorityabout the Qwen2.5 family1,328 words

Qwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Coding

qwenlm.github.io2024-11-11officialauthorityabout the Qwen2.5 familyHN 23 pts · 0 comments1,210 words

The True Capability of Qwen 2.5 Coder 32B Instruct

alibabacloud.comofficial

Analysis5

Qwen2.5-Coder-32B is an LLM that can code well that runs on my Mac

simonwillison.net2024-11-13authorityHN front pageabout the Qwen2.5 familyHN 164 pts · 65 comments635 words

Alibaba released the Qwen2.5-Coder-32B-Instruct model, an Apache 2.0 licensed open-source LLM. The 32B model runs on a 64GB MacBook Pro M2 via Ollama or MLX, fetching a 20GB quantized file. On MLX, it achieved 10.016 tokens-per-sec generation speed with 32.685 GB peak memory usage.written, reviewed, cited

The model requires a workaround for an SSL bug when using the standard library instead of requests or httpx.
Running the Ollama version was too slow because the author did not have the tool compiled to use the Mac's GPU.

Qwen2.5-Coder Technical Report

arxiv.orgauthorityabout the Qwen2.5 family14,816 words

Qwen2.5 Coder 32B - Intelligence, Performance & Price ...

artificialanalysis.aiauthority

Qwen2.5-Coder-32B with coding abilities matching those of GPT-4o

github.com2024-11-09authorityabout the Qwen2.5 familyHN 21 pts · 6 comments1,815 words

Qwen2.5-Coder Technical Report

arxiv.org2024-11-11authorityabout the Qwen2.5 familyHN 4 pts · 0 comments

Community1

Show HN: IttyBittyAI – Qwen2.5:0.5B running on a 2017 Asus smartphone

news.ycombinator.com2026-09-24about the Qwen2.5 familyHN 2 pts · 0 comments494 words

All coverage tracked for this model (33) — append-only, nothing is ever removed

Title	Source	Published	First seen	Signals
Qwen2.5-Coder Series: Powerful, Diverse, Practical.	qwen.ai official	—	2026-10-07	exa
Qwen2.5-Coder Technical Report	arxiv.org	—	2026-10-07	exa
Qwen2.5 Coder 32B - Intelligence, Performance & Price ...	artificialanalysis.ai	—	2026-10-07	exa
The True Capability of Qwen 2.5 Coder 32B Instruct	alibabacloud.com official	—	2026-10-07	exa
Qwen2.5-Coder-32B is an LLM that can code well that runs on ...	simonw.substack.com	—	2026-10-07	exa
Show HN: IttyBittyAI – Qwen2.5:0.5B running on a 2017 Asus smartphone	news.ycombinator.com	2026-09-24	2026-10-07	hn
kev: Jev-like model built on Qwen2.5-0.5B	github.com	2026-09-19	2026-10-07	hn
Civic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt data	itsmeduncan.com	2026-04-25	2026-10-07	hn
Show HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs	cinegraphs.ai	2026-02-08	2026-10-07	hn
Qwen2.5-Omni Technical Report	huggingface.co	2025-03-30	2026-10-07	hn
Alibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Model	alizila.com	2025-03-27	2026-10-07	hn
Qwen2.5 Omni: See, Hear, Talk, Write, Do It All	qwenlm.github.io official	2025-03-26	2026-10-07	hn
Qwen2.5-VL-32B: Smarter and Lighter	simonwillison.net	2025-03-25	2026-10-07	hn
Qwen2.5-VL-32B: Smarter and Lighter	qwenlm.github.io official	2025-03-24	2026-10-07	hn
Qwen2.5-Plus	chat.qwenlm.ai	2025-01-31	2026-10-07	hn
Qwen2.5-VL: State-of-the-art multimodal LLM	github.com	2025-01-30	2026-10-07	hn
Qwen2.5-Max: The Next Leap in AI Innovation	medium.com	2025-01-29	2026-10-07	hn
New Qwen2.5-Max Outperforms DeepSeek V3 in Benchmarks	twitter.com	2025-01-28	2026-10-07	hn
Qwen2.5-Max: Exploring the intelligence of large-scale MoE model	qwenlm.github.io official	2025-01-28	2026-10-07	hn
Show HN: I made a free study tool powered by Qwen2.5	freeflashcardgenerator.com	2025-01-28	2026-10-07	hn
Qwen2.5-VL	qwenlm.github.io official	2025-01-27	2026-10-07	hn
Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M	simonwillison.net	2025-01-26	2026-10-07	hn
Qwen2.5-1M: Deploy your own Qwen with context length up to 1M tokens	qwenlm.github.io official	2025-01-26	2026-10-07	hn
Qwen2.5-coder on the events occurring during the Tiananmen Square protests	news.ycombinator.com	2024-11-20	2026-10-07	hn
Qwen2.5-Coder-32B is an LLM that can code well that runs on my Mac	simonwillison.net	2024-11-13	2026-10-07	hn
Qwen2.5-Coder-32B: The Open-Weight Coding Model That Matched GPT-4o — Redeep	redeep.blog	2024-11-12	2026-10-07	exa
Qwen2.5-Coder Technical Report	arxiv.org	2024-11-11	2026-10-07	hn
Qwen2.5 Coder	ollama.com	2024-11-11	2026-10-07	hn
Qwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Coding	qwenlm.github.io official	2024-11-11	2026-10-07	hn
Qwen2.5-Coder-32B-Instruct Review — Benchmarks, Pricing & AI Panel Verdict \| TopReviewed.ai	topreviewed.ai	2024-11-11	2026-10-07	exa
Qwen2.5-Coder-32B with coding abilities matching those of GPT-4o	github.com	2024-11-09	2026-10-07	hn
Guide how to use a local LLM Qwen2.5-coder-7B as an autocompelte in VSCode	eamag.me	2024-10-29	2026-10-07	hn
Qwen2.5: A Party of Foundation Models	qwenlm.github.io official	2024-09-18	2026-10-07	hn

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).

Qwen2 Technical Report this model

An Yang, Baosong Yang, Binyuan Hui +59 · 2024-07-15 · PDF · HF paper page (176 upvotes)
Qwen2.5-Coder Technical Report this model

Binyuan Hui, Jian Yang, Zeyu Cui +21 · 2024-09-18 · PDF · HF paper page (160 upvotes)
YaRN: Efficient Context Window Extension of Large Language Models cited in card

Bowen Peng, Jeffrey Quesnelle, Honglu Fan +1 · 2023-08-31 · PDF · HF paper page (88 upvotes)

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Sources

4 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:32 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 14:59 UTC · Last verified 2026-10-25

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