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Models › Qwen2.5 family

Qwen2.5-7B-Instruct

Hugging Face ↗ Follow changes

Qwen Apache 2.0 out 2 years ago

7.62B parameters, text in, text out, 32K tokens of context. 2 providers serve it from $0.10 per million input tokens.

Verified 2026-10-26 07:27 UTC Rank #23 in LLMs · score 118.1 method v1 Sources 4 Downloads 30d 5.7M · #25 of 619 tracked

Changed this week: 10 new quantized builds on the Hub (442 in all).2026-10-24 · 9 new quantized builds on the Hub (441 in all).2026-10-24

Can I run it?4.6GB at INT4Estimatefits a 16 GB cardmethod
What does it cost?$0.10/1M incheapest of 1Phala2026-10-26
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-26
Do people use it?5.7Mdownloads, 30 days#25 of 619 we track · top 4%+13 likes, downloads −17% this week2,458 likesHugging Face2026-10-26

Worth reading

Picked by rule from 30 tracked pieces: the lab's own post, the most shared, a field report, the latest.

25 best of 30 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: 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-LLM: Extending the boundary of LLMs | Qwenqwenlm.github.io · undated · official
  7. ArticleQwen2.5-Coder-32B is an LLM that can code well that runs on my Macsimonwillison.net · 2024-11-13
  8. ArticleQwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1Msimonwillison.net · 2025-01-26 · 98 HN pts
  9. ArticleQwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Codingqwenlm.github.io · 2024-11-11 · official
  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. CodePerformance on Qwen2.5-7B-Instruct · Issue #42 - GitHubgithub.com · undated
  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. PaperQwen2.5 Technical Reportarxiv.org · 2025-01-03
  21. CodeQwen2.5-VL: State-of-the-art multimodal LLMgithub.com · 2025-01-30
  22. DiscussionNew Qwen2.5-Max Outperforms DeepSeek V3 in Benchmarkstwitter.com · 2025-01-28
  23. ArticleQwen2.5-7B-Instruct – 128k context, open source | LLM Referencellmreference.com · undated

Where to run it

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

#Cheapest 2In /1MOut /1MContextQuantSeen
1 Phala $0.10 $0.20 32K unknown Oct 26
2 Featherless — — — — Oct 26

All 2 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 2 API providers; heavily run locally (442 quantized builds); a big base for builders (6,225 fine-tunes, adapters and merges).

  • As a service2Featherless, Phala
  • On own hardware442quantized builds
  • Built on6,2253,219 fine-tunes · 2,837 adapters · 169 merges
  • In apps100+Hugging Face Spaces

Top Spaces running it: pliny-the-prompter/obliteratus ♥ 621 · allenai/reward-bench ♥ 438 · cvachet/pdf-chatbot ♥ 382 · alexnasa/Wan2.2-Animate-ZEROGPU ♥ 365

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.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 4.6 GB of weights (estimate; KV cache and activations extra)INT44.6 GBFP8: about 9.1 GB of weights (estimate; KV cache and activations extra)FP89.1 GBBF16: about 18 GB of weights (estimate; KV cache and activations extra)BF1618 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 4.6 GB of weights (estimate; KV cache and activations extra)INT44.6 GBFP8: about 9.1 GB of weights (estimate; KV cache and activations extra)FP89.1 GBBF16: about 18 GB of weights (estimate; KV cache and activations extra)BF1618 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.

7 dated articles and 13 repo commits so far

Teal is the weights (2024-09-16), amber triangles are 7 dated articles (each links to it), grey ticks are repo commits.

OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-01-12: 1 repo commit2024-09-25: 1 repo commit2024-09-19: 1 repo commit2024-09-18: 3 repo commits2024-09-17: 5 repo commits2024-09-16: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Show HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs · 2026-02-08Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M · 2025-01-26Civic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt data · 2026-04-25Qwen2.5 Technical Report · 2025-01-03Show HN: I made a free study tool powered by Qwen2.5 · 2025-01-28Evaluating the Performance of LLMs: A Deep Dive into qwen2.5-7b-instruct-1m | Not Quite Random · 2025-02-03Weights 2024-09-16 · 2024-09-16Weights 2024-09-16now · 2 providers
OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-01-12: 1 repo commit2024-09-25: 1 repo commit2024-09-19: 1 repo commit2024-09-18: 3 repo commits2024-09-17: 5 repo commits2024-09-16: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Show HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs · 2026-02-08Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M · 2025-01-26Civic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt data · 2026-04-25Qwen2.5 Technical Report · 2025-01-03Show HN: I made a free study tool powered by Qwen2.5 · 2025-01-28Evaluating the Performance of LLMs: A Deep Dive into qwen2.5-7b-instruct-1m | Not Quite Random · 2025-02-03Weights 2024-09-16 · 2024-09-16Weights 2024-09-16now · 2 providers

What people built on it

6,667 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

6,667 derivatives on the Hub, led by 3,219 fine-tunes

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

442 quantized (Hugging Face model tree)3,219 fine-tunes (Hugging Face model tree)169 merges (Hugging Face model tree)2,837 adapters (Hugging Face model tree)442 quantized3,219 fine-tunes169 merges2,837 adapters
442 quantized (Hugging Face model tree)3,219 fine-tunes (Hugging Face model tree)169 merges (Hugging Face model tree)2,837 adapters (Hugging Face model tree)442 quantized3,219 fine-tunes169 merges2,837 adapters
GGUF MaziyarPanahi/Qwen2.5-7B-Instruct-GGUF for llama.cpp, Ollama, LM Studio 11.8M downloads AWQ Qwen/Qwen2.5-7B-Instruct-AWQ for vLLM, SGLang 25.4M downloads

All variants →

Reference

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

What the card says

2 cited sentences

Summary generated, cited

Qwen2.5-7B-Instruct is an instruction-tuned causal language model with 7.62B parameters.[1][2] It supports a context length of up to 131,072 tokens.[3]

  1. parameters human
  2. “Type: Causal Language Models”
  3. “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

5 use cases

What it is good at 5 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: 7,615,616,512
Size bandM
MoEno
Context length32,768 (config.json max_position_embeddings)
Languagesen
PapersarXiv:2309.00071, arXiv:2407.10671
LicenseApache 2.0 (apache-2.0)
Hub snapshot2026-10-26

Servability

vLLM · SGLang

Servability

vLLM: supported · Qwen2ForCausalLM · 4b1c04e76fe9ac3ca8b7e541dd423e7d5f38dc60SGLang: supported · Qwen2ForCausalLM · 60d941293e3af27a12c6eb64e2c3e2e1a17f100f

vLLM registry (4b1c04e76fe9ac3ca8b7e541dd423e7d5f38dc60) · SGLang registry (60d941293e3af27a12c6eb64e2c3e2e1a17f100f) · 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 Qwen2.5-7B-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/Qwen2.5-7B (same organization) Family: Qwen/Qwen2.5 6,667 derivatives on the Hub

Base model: Qwen/Qwen2.5-7B

quantized: 442finetune: 3,219merge: 169adapter: 2,837

Top variants (40 shown, ranked by downloads)

Relation
Quant
Size
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
Qwen/Qwen2.5-7B-Instruct-AWQ quantized AWQ 7.62B M apache-2.0 Qwen 60 25.4M
MaziyarPanahi/Qwen2.5-7B-Instruct-GGUF quantized GGUF — — — MaziyarPanahi 11 11.8M
unsloth/Qwen2.5-7B-Instruct-unsloth-bnb-4bit quantized -bnb 7.79B M apache-2.0 unsloth 1 4.4M
unsloth/Qwen2.5-7B-Instruct-bnb-4bit quantized -bnb 7.82B M apache-2.0 unsloth 24 4.3M
Qwen/Qwen2.5-7B-Instruct-GPTQ-Int4 quantized GPTQ 7.62B M apache-2.0 Qwen 39 2.3M
unsloth/Qwen2.5-7B-Instruct finetune — 7.62B M apache-2.0 unsloth 27 2.3M
bartowski/Qwen2.5-7B-Instruct-GGUF quantized GGUF — — apache-2.0 bartowski 85 1.6M
Qwen/Qwen2.5-7B-Instruct-GGUF quantized GGUF — — apache-2.0 Qwen 200 1.3M
Gensyn/Qwen2.5-7B-Instruct finetune — 7.62B M apache-2.0 Gensyn 7 925.5k
nvidia/Eagle2.5-8B merge — 8.07B M other nvidia 51 612.4k
cooperleong00/Qwen2.5-7B-Instruct-Jailbroken finetune — 7.62B M — cooperleong00 7 367.8k
Qwen/Qwen2.5-7B-Instruct-GPTQ-Int8 quantized GPTQ 7.62B M apache-2.0 Qwen 25 303.4k
lmstudio-community/Qwen2.5-7B-Instruct-GGUF quantized GGUF — — apache-2.0 lmstudio-community 7 193.9k
Virtue-AI-HUB/VulnLLM-R-7B finetune — 7.62B M apache-2.0 Virtue-AI-HUB 249 180.6k
open-thoughts/OpenThinker3-7B finetune — 7.62B M apache-2.0 open-thoughts 138 185.6k
Orion-zhen/Qwen2.5-7B-Instruct-Uncensored finetune — 7.62B M gpl-3.0 Orion-zhen 61 172.9k
Efficient-Large-Model/Fast_dLLM_v2_7B finetune — 333K S apache-2.0 Efficient-Large-Model 34 143.1k
QuantFactory/Qwen2.5-7B-Instruct-Uncensored-GGUF quantized GGUF — — gpl-3.0 QuantFactory 33 134.2k
open-thoughts/OpenThinker-7B finetune — 7.62B M apache-2.0 open-thoughts 140 124.8k
RedHatAI/Qwen2.5-7B-Instruct-FP8-dynamic quantized -FP8 7.62B M apache-2.0 RedHatAI 1 128.2k
PokeeAI/pokee_research_7b finetune — 7.62B M apache-2.0 PokeeAI 99 117.1k
ByteDance-Seed/BAGEL-7B-MoT finetune — 14.7B L apache-2.0 ByteDance-Seed 1.2k 45.4k
huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2 finetune — 7.62B M apache-2.0 huihui-ai 71 101.5k
anton-hugging/TimeOmni-1-7B finetune — 7.62B M apache-2.0 anton-hugging 9 99k
paultimothymooney/Qwen2.5-7B-Instruct-Q4_K_M-GGUF quantized GGUF — — apache-2.0 paultimothymooney 13 90.4k
langfeng01/GiGPO-Qwen2.5-7B-Instruct-WebShop finetune — 7.62B M apache-2.0 langfeng01 0 86.2k
Video-R1/Qwen2.5-VL-7B-COT-SFT finetune — 8.29B M apache-2.0 Video-R1 2 76.9k
open-thoughts/OpenThinker2-7B finetune — 7.62B M apache-2.0 open-thoughts 19 67k
QuantFactory/Qwen2.5-7B-Instruct-abliterated-v2-GGUF quantized GGUF — — apache-2.0 QuantFactory 13 66.9k
Jurema-br/Jurema-7B finetune — 7.62B M apache-2.0 Jurema-br 78 63.2k
simplescaling/s1.1-7B finetune — 7.62B M — simplescaling 6 64.7k
llamafactory/tiny-random-qwen2.5 finetune — 4.87M S apache-2.0 llamafactory 0 43.1k
bespokelabs/Bespoke-Stratos-7B finetune — 7.62B M apache-2.0 bespokelabs 30 37.6k
richardyoung/Qwen2.5-7B-Instruct-abliterated-GGUF quantized GGUF — — apache-2.0 richardyoung 5 37.2k
nyu-visionx/Cambrian-S-7B finetune — 8.03B M apache-2.0 nyu-visionx 5 33k
chtmp223/Qwen2.5-7B-CLIPPER finetune — 7.62B M apache-2.0 chtmp223 0 32.2k
AgentFlow/agentflow-planner-7b finetune — 7.62B M mit AgentFlow 64 26.8k
Cran-May/T.E-8.1 finetune — 7.62B M cc-by-nc-sa-4.0 Cran-May 3 28.4k
OpenBuddy/openbuddy-qwen2.5llamaify-7b-v23.1-200k finetune — 7.62B M apache-2.0 OpenBuddy 5 28.2k
yaoyueduzhen/RAG-R1-mq-7b finetune — 7.62B M apache-2.0 yaoyueduzhen 2 27.3k

Repository changelog

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

Repository changelog 13 commits

DateCommitSHA
2025-01-12 Update README.md a09a354
2024-09-25 Update metadata: Add library_name to Transformers (#8) bb46c15
2024-09-19 Upload ./tokenizer_config.json with huggingface_hub acbd965
2024-09-18 update README & LICENSE 52e20a6
2024-09-18 update config.json a306ca6
2024-09-18 Update tokenizer_config.json 929d90a
2024-09-17 Update README.md ddb6b63
2024-09-17 Update README.md aa1b431
2024-09-17 Update config.json 605f111
2024-09-17 Update README.md ddbda89
2024-09-17 Create README.md 4e8250b
2024-09-16 Upload folder using huggingface_hub d1e200f
2024-09-16 initial commit 11a48c2

All providers

2 providers · 2 endpoints

Where to run 2 providers · 2 endpoints

Hosted endpoints observed for Qwen2.5-7B-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. Cheapest observed input price: $0.10/M.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Phala
openrouter
 qwen/qwen-2.5-7b-instruct 32K unknown $0.10 $0.20 — — yes live 2026-10-26
Featherless
hf
 Qwen/Qwen2.5-7B-Instruct — — — — — — — live 2026-10-26

Articles and coverage

30 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

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-LLM: Extending the boundary of LLMs | Qwen
qwenlm.github.ioofficialauthorityabout the Qwen2.5 family4,262 words

Analysis8

Show HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs
cinegraphs.ai2026-02-08HN front pageHN 101 pts · 20 comments
Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M
simonwillison.net2025-01-26authorityHN 98 pts · 2 comments627 words
Civic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt data
itsmeduncan.com2026-04-25HN 9 pts · 0 comments646 words
Performance on Qwen2.5-7B-Instruct · Issue #42 - GitHub
github.comauthority
Qwen2.5 Technical Report
arxiv.org2025-01-03authorityabout the Qwen2.5 family
Qwen2.5-7B-Instruct – 128k context, open source | LLM Reference
llmreference.com
Show HN: I made a free study tool powered by Qwen2.5
freeflashcardgenerator.com2025-01-28about the Qwen2.5 familyHN 3 pts · 0 comments
Evaluating the Performance of LLMs: A Deep Dive into qwen2.5-7b-instruct-1m | Not Quite Random
notquiterandom.com2025-02-03
All coverage tracked for this model (30) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Qwen2.5-LLM: Extending the boundary of LLMs | Qwenqwenlm.github.io official—2026-10-07exa
Performance on Qwen2.5-7B-Instruct · Issue #42 - GitHubgithub.com—2026-10-07exa
Qwen2.5-7B-Instruct – 128k context, open source | LLM Referencellmreference.com—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
Evaluating the Performance of LLMs: A Deep Dive into qwen2.5-7b-instruct-1m | Not Quite Randomnotquiterandom.com2025-02-032026-10-07exa
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, exa
Qwen2.5 Technical Reportarxiv.org2025-01-032026-10-07exa
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

  • Llama-3.1-8B-Instruct · 8.03B
    same size band (M), same task (text-generation), more providers
  • Qwen3-8B · 8.19B
    same size band (M), same task (text-generation), permissive license
  • DeepSeek-R1-Distill-Qwen-7B · 7.62B
    same size band (M), same task (text-generation), fewer providers, permissive license

Sources

4 sources

Sources

Hub snapshot: 2026-10-26 · HF API: 2026-10-26 07:13 UTC · Providers: 2026-10-26 07:26 UTC · Articles: 2026-10-26 07:27 UTC · Summary: 2026-10-07 14:59 UTC · Last verified 2026-10-26 07:27 UTC

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