Qwen2-7B-Instruct

7.62B parameters, text in, text out, 32K tokens of context. 1 provider serves it.

Verified 2026-10-25 Rank #99 in LLMs · score 99.2 method v1 Sources 3 Downloads 30d 183k · #259 of 619 tracked

Can I run it?4.6GB at INT4Estimatefits a 16 GB cardmethod

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

Do people use it?183kdownloads, 30 days#259 of 619 we track · top 42%+3 likes, downloads −19% this week695 likesHugging Face2026-10-24

Worth reading

Picked by rule from 10 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 29 HN pts

Alibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Model

alizila.com 2025-03-27 29 HN pts · 3 comments about the Qwen2 family family

Latest · 2 years ago

Qwen2-Math

Qwen2-Math is a series of specialized math language models built upon the Qwen2 LLMs that significantly outperforms the mathematical capabilities of open-source models and even closed-source models.

The model series primarily supports English, with bilingual English and Chinese math models scheduled for release soon.
Evaluation of multi-choice benchmarks including MMLU STEM and GaoKao problems uses a 5-shot setting instead of zero-shot.

qwenlm.github.io 2024-08-08 128 HN pts · 38 comments 5.8k words about the Qwen2 family family

10 best of 10 tracked

The 2 picks above, plus these 8. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

ArticleQwen2 LLM Releasedqwenlm.github.io · 2024-06-06 · 261 HN pts · official
CodeLlama.cpp Now Supports Qwen2-VL (Vision Language Model)github.com · 2024-12-14
ArticleQwen2 7B Instruct API & Playground | Fireworks AIfireworks.ai · undated
ArticleAn Analysis of Chinese LLM Censorship and Bias with Qwen 2 Instructhuggingface.co · 2024-06-09 · 16 HN pts
ArticleQwen2.5-Max: The Next Leap in AI Innovationmedium.com · 2025-01-29 · 17 HN pts
ArticleQwen2-7B-Instruct with TensorRT-LLM: consistently high tokens/SECinferless.com · 2024-09-05 · 1 HN pts
ArticleQwen2 Technical Reportexa.ai · 2024-07-15
ArticleQwen2-7B-Instruct – 128k context, open source | LLM Referencellmreference.com · 2024-06-07

Show all 8

Where to run it

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

#	Cheapest live row	In /1M	Out /1M	Context	Quant	Seen
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 (83 quantized builds); a big base for builders (492 fine-tunes, adapters and merges).

As a service1Featherless
On own hardware83quantized builds
Built on492131 fine-tunes · 354 adapters · 7 merges
In apps100+Hugging Face Spaces

Top Spaces running it: TIGER-Lab/Pixel-Reasoner ♥ 58 · hugging-apps/ardy ♥ 43 · CZLC/BenCzechMark ♥ 26 · neulab/Pangea ♥ 22

Will it fit?

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

Fits a 16 GB card at INT4

About 4.6 GB at INT4, 9.1 GB at FP8, 18 GB at BF16: weights only, so leave room for the KV cache.

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

The story so far

Weights, every dated article, and repo commits on one rail.

8 dated articles and 11 repo commits so far

Teal is the weights (2024-06-04), amber triangles are 8 dated articles (each links to it), grey ticks are repo commits.

What people built on it

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

575 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.

GGUF MaziyarPanahi/Qwen2-7B-Instruct-GGUF for llama.cpp, Ollama, LM Studio 11.4M downloads AWQ Qwen/Qwen2-7B-Instruct-AWQ for vLLM, SGLang 390.3k downloads

All variants →

Reference

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

Benchmarks

14 rows

Benchmarks 14 rows

measured third-party leaderboard rowauthor-reported number from the model card or eval files (14)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.

Benchmark	Value	Setting / notes	Reported by	Date
author-reported AlignBench	7.21	Chinese	model author	2026-10-07
author-reported C-Eval · Work across languages	77.2	Chinese	model author	2026-10-07
author-reported GPQA Diamond · Reason through hard problems	25.3	English	model author	2026-10-07
author-reported GSM8K · Reason through hard problems	82.3	Mathematics	model author	2026-10-07
author-reported HumanEval · Write code with agents	79.9	Coding	model author	2026-10-07
author-reported HumanEval · Write code with agents	70.3	Coding	model author	2026-10-07
author-reported LiveCodeBench · Write code with agents	26.6	Coding	model author	2026-10-07
author-reported MATH-500 · Reason through hard problems	49.6	Mathematics	model author	2026-10-07
author-reported MBPP · Write code with agents	67.2	Coding	model author	2026-10-07
author-reported MMLU · Reason through hard problems	70.5	English	model author	2026-10-07
author-reported MMLU-Pro · Reason through hard problems	44.1	English	model author	2026-10-07
author-reported MT-Bench · Chat and follow instructions	8.41	English	model author	2026-10-07
author-reported MultiPL-E · Write code with agents	59.1	Coding	model author	2026-10-07
author-reported TheroemQA	25.3	English	model author	2026-10-07

What the card says

1 cited sentence

Summary generated, cited

The model uses the Qwen2ForCausalLM architecture and supports a context length of up to 131,072 tokens.^[1]^[2]

architectures
“context length of up to 131,072 tokens”

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

6 use cases

What it is good at 6 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

Qwen2-7B-Instruct has 7.62B 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 2024-06-04, last modified 2024-08-21. (HF API, observed 2026-10-24)

Pipeline tag	text-generation
Library	transformers
Architectures	Qwen2ForCausalLM
Model type	qwen2
Dtype	bfloat16
Params by dtype	BF16: 7,615,616,512
Size band	M
MoE	no
Context length	32,768 (config.json max_position_embeddings)
Languages	en
Papers	arXiv:2309.00071
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 Qwen2-7B-Instruct: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)	18 GB · Single GPU (<24 GB)
FP8 (1 byte/param)	9.1 GB · Single GPU (<24 GB)
INT4 (0.5 bytes/param)	4.6 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/Qwen2-7B (same organization) Family: Qwen/Qwen2 575 derivatives on the Hub

Base model: Qwen/Qwen2-7B

quantized: 83finetune: 131adapter: 354merge: 7

Top variants (40 shown, ranked by downloads)

Variant	Relation	Quant	Params	Band	License	Author	Likes	Downloads
MaziyarPanahi/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	—	MaziyarPanahi	10	11.4M
Qwen/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	Qwen	185	480.9k
Qwen/Qwen2-7B-Instruct-AWQ	quantized	AWQ	7.62B	M	apache-2.0	Qwen	28	390.3k
neulab/Pangea-7B	finetune	—	7.94B	M	apache-2.0	neulab	133	178.4k
Qwen/Qwen2-7B-Instruct-GPTQ-Int4	quantized	GPTQ	7.62B	M	apache-2.0	Qwen	32	78.2k
AITeamVN/Vi-Qwen2-1.5B-RAG	finetune	—	1.54B	S	apache-2.0	AITeamVN	4	78.6k
bartowski/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	bartowski	17	50k
Qwen/Qwen2-7B-Instruct-GPTQ-Int8	quantized	GPTQ	7.62B	M	apache-2.0	Qwen	23	48.9k
legraphista/Qwen2-7B-Instruct-IMat-GGUF	quantized	GGUF	—	—	apache-2.0	legraphista	3	46.2k
QuantFactory/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	QuantFactory	4	39.6k
Tifa-RP/Tifa-7B-Qwen2-v0.1-GGUF	quantized	GGUF	—	—	apache-2.0	Tifa-RP	33	36.8k
neulab/Pangea-7B-hf	finetune	—	7.94B	M	apache-2.0	neulab	13	34k
bartowski/Qwen2-7B-Instruct-deccp-GGUF	quantized	GGUF	—	—	apache-2.0	bartowski	5	29.8k
mradermacher/Qwen2-7B-Instruct-i1-GGUF	quantized	GGUF	—	—	apache-2.0	mradermacher	0	20.6k
AITeamVN/Vi-Qwen2-7B-RAG	finetune	—	7.62B	M	apache-2.0	AITeamVN	23	17.4k
CarrotAI/Rabbit-Ko-15B-Instruct	finetune	—	15.1B	L	apache-2.0	CarrotAI	0	16.7k
TommyChien/memorag-qwen2-7b-inst	finetune	—	8.08B	M	apache-2.0	TommyChien	12	14.2k
AITeamVN/Vi-Qwen2-3B-RAG	finetune	—	3.09B	M	apache-2.0	AITeamVN	5	11.9k
lfhe/FLock-Arena-Task-10-Healers	adapter	—	—	—	—	lfhe	0	12k
CHE-72-ZLab/Alibaba-Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	CHE-72-ZLab	1	11.5k
GPT4All-Community/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	GPT4All-Community	1	11k
second-state/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	second-state	1	11k
mradermacher/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	mradermacher	0	10.4k
QuantFactory/Qwen2-7B-BD-RP-GGUF	quantized	GGUF	—	—	apache-2.0	QuantFactory	4	9.4k
qwp4w3hyb/Qwen2-7B-Instruct-iMat-GGUF	quantized	GGUF	—	—	apache-2.0	qwp4w3hyb	0	8.7k
nisten/qwenv2-7b-inst-imatrix-gguf	quantized	imatrix	—	—	apache-2.0	nisten	3	7k
OpenVINO/Qwen2-7B-Instruct-int4-ov	quantized	int4	—	—	apache-2.0	OpenVINO	0	5.3k
THUdyh/Oryx-7B	finetune	—	8.06B	M	apache-2.0	THUdyh	12	4.5k
yale-nlp/MDCure-Qwen2-7B-Instruct	finetune	—	7.62B	M	apache-2.0	yale-nlp	1	4.5k
JunHowie/Qwen2-7B-Instruct-GPTQ-Int4	quantized	GPTQ	7.62B	M	apache-2.0	JunHowie	0	4.6k
NikolayKozloff/Qwen2-7B-Instruct-Q4_K_M-GGUF	quantized	GGUF	—	—	apache-2.0	NikolayKozloff	6	4k
neulab/UIX-Qwen2	finetune	—	8.03B	M	odc-by	neulab	22	3.2k
nvidia/VideoITG-8B	merge	—	7.52B	M	other	nvidia	12	3.5k
gaianet/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	gaianet	0	4k
WaltonFuture/Diabetica-7B	finetune	—	7.62B	M	mit	WaltonFuture	10	3.2k
naver/oscar-qwen2-7B	finetune	—	—	—	cc-by-4.0	naver	3	2.8k
augmxnt/Qwen2-7B-Instruct-deccp	finetune	—	7.62B	M	apache-2.0	augmxnt	20	1.9k
NexaAI/Squid	finetune	—	8.11B	M	cc-by-nc-4.0	NexaAI	35	1.1k
featherless-ai-quants/Qwen-Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	—	featherless-ai-quants	0	2.5k
DevQuasar/Qwen2-7B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	DevQuasar	1	2.4k

Repository changelog

11 commits

changed in the last 7 daysRank band moves: 2026-10-23all changes

Repository changelog 11 commits

Date	Commit	SHA
2024-08-21	Update README.md	f2826a0
2024-06-06	update README.md	41c66b0
2024-06-06	update README.md	6b8ee6a
2024-06-06	Update README.md	332255d
2024-06-06	Update README.md	2061615
2024-06-05	Update config.json	6ddb532
2024-06-05	Update tokenizer_config.json	cbbec1d
2024-06-05	Create README.md	f1296be
2024-06-05	Create LICENSE	ab17923
2024-06-04	Initial commit	a8eaaac
2024-06-04	initial commit	de7b022

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for Qwen2-7B-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.

Provider	Model ref	Context	Quant	$/M in	$/M out	tok/s	TTFT	Tools	Status	Observed
Featherless hf	Qwen/Qwen2-7B-Instruct	—	—	—	—	—	—	—	live	2026-10-25

Articles and coverage

10 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.

Official3

Qwen2 LLM Released

qwenlm.github.io2024-06-06officialauthorityHN front pageabout the Qwen2 familyHN 261 pts · 130 comments4,713 words

Alibaba releases Qwen2, a new series of open-source models featuring five sizes ranging from 0.5B to 72B parameters. The update applies Group Query Attention to all sizes and trains on data in 27 additional languages besides English and Chinese. Specific instruction-tuned versions like Qwen2-7B-Instruct and Qwen2-72B-Instruct support extended context lengths up to 128K tokens, while smaller models adopt the Apache 2.0 license and the largest retains the Qianwen License.written, reviewed, cited

Qwen2-57B-A14B disables tie embedding because large sparse embeddings consume a large proportion of total model parameters.
Instruction-tuned models require the Needle in a Haystack task to verify correct long-context understanding beyond perplexity evaluation.
The Qwen2-72B-Instruct model performs comparably to GPT-4 in safety tests across four categories of multilingual unsafe queries.

Qwen2-Math

qwenlm.github.io2024-08-08officialauthorityHN front pageabout the Qwen2 familyHN 128 pts · 38 comments5,833 words

Qwen2-Math is a series of specialized math language models built upon the Qwen2 LLMs that significantly outperforms the mathematical capabilities of open-source models and even closed-source models. The largest model, Qwen2-Math-72B-Instruct, is evaluated on benchmarks including GSM8K, Math, and MMLU-STEM using few-shot chain-of-thought prompting. Instruction tuning combines a dense reward signal with a binary signal via Rejection Sampling and reinforcement learning with Group Relative Policy Optimization (GRPO) after SFT.written, reviewed, cited

The model series primarily supports English, with bilingual English and Chinese math models scheduled for release soon.
Evaluation of multi-choice benchmarks including MMLU STEM and GaoKao problems uses a 5-shot setting instead of zero-shot.
Performance reporting for complex competition evaluations includes Greedy, Maj@64, RM@64, and RM@256 metrics.

An Analysis of Chinese LLM Censorship and Bias with Qwen 2 Instruct

huggingface.co2024-06-09authorityabout the Qwen2 familyHN 16 pts · 6 comments3,368 words

Qwen 2 Instruct models operate under an Apache 2.0 license but exhibit unique government-mandated alignment with significantly (>80%) fewer refusals in Chinese than English. The deccp dataset documents these behaviors, showing that responses to sensitive topics often include defensive nationalist propaganda or warnings rather than standard refusals. While the models are competitive on benchmarks, their output varies wildly in tone depending on the language used.written, reviewed, cited

Qwen2-72B-Instruct ranks just below Llama-3-70b-Instruct on the ChatArena Leaderboard several days after release.
The deccp dataset contains approximately 95 refusal questions used to evaluate Qwen2 Instructs censorship behavior.

Analysis6

Qwen2 7B Instruct API & Playground | Fireworks AI

fireworks.aiauthority98 words

Fireworks AI provides the Qwen2 7B Instruct model under the Apache 2.0 license for on-demand deployment with no rate limits. The model features a default context length of 32,768 tokens, extendable to 131,072 tokens using YaRN extrapolation techniques. While optimized for instruction-following and code generation, streaming responses and function calling are not supported for this model.written, reviewed, cited

Alibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Model

alizila.com2025-03-27about the Qwen2 familyHN 29 pts · 3 comments

Qwen2.5-Max: The Next Leap in AI Innovation

medium.com2025-01-29about the Qwen2 familyHN 17 pts · 4 comments

Qwen2-7B-Instruct with TensorRT-LLM: consistently high tokens/SEC

inferless.com2024-09-05HN 1 pts · 1 comments913 words

Qwen2-7B-Instruct – 128k context, open source | LLM Reference

llmreference.com2024-06-07263 words

Qwen2 Technical Report

exa.ai2024-07-15about the Qwen2 family220 words

All coverage tracked for this model (10) — append-only, nothing is ever removed

Title	Source	Published	First seen	Signals
Qwen2 7B Instruct API & Playground \| Fireworks AI	fireworks.ai	—	2026-10-07	exa
Alibaba Qwen2.5-Omni-7B: Open Source End-to-End Multimodal AI Model	alizila.com	2025-03-27	2026-10-07	hn
Qwen2.5-Max: The Next Leap in AI Innovation	medium.com	2025-01-29	2026-10-07	hn
Llama.cpp Now Supports Qwen2-VL (Vision Language Model)	github.com	2024-12-14	2026-10-07	hn
Qwen2-7B-Instruct with TensorRT-LLM: consistently high tokens/SEC	inferless.com	2024-09-05	2026-10-07	hn
Qwen2-Math	qwenlm.github.io official	2024-08-08	2026-10-07	hn
Qwen2 Technical Report	exa.ai	2024-07-15	2026-10-07	exa
An Analysis of Chinese LLM Censorship and Bias with Qwen 2 Instruct	huggingface.co	2024-06-09	2026-10-07	hn
Qwen2-7B-Instruct – 128k context, open source \| LLM Reference	llmreference.com	2024-06-07	2026-10-07	exa
Qwen2 LLM Released	qwenlm.github.io official	2024-06-06	2026-10-07	hn

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).

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)

Similar models

3 models

Similar models

Llama-3.1-8B-Instruct · 8.03B
same size band (M), same task (text-generation), more providers
Qwen2.5-7B-Instruct · 7.62B
same size band (M), same task (text-generation), more providers, permissive license
Qwen3-8B · 8.19B
same size band (M), same task (text-generation), more providers, permissive license

Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:34 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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