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Models › Qwen2.5 family

Qwen2.5-Coder-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 $0.010 per million input tokens.

Verified 2026-10-25 Rank #68 in LLMs · score 104.5 method v1 Sources 3 Downloads 30d 1.4M · #87 of 619 tracked

Changed this week: 9 new quantized builds on the Hub (269 in all).2026-10-24 · 8 new quantized builds on the Hub (268 in all).2026-10-24 · 1 new provider: Nscale.2026-10-23

Can I run it?4.6GB at INT4Estimatefits a 16 GB cardmethod
What does it cost?$0.010/1M incheapest of 1Nscale2026-10-25
Can I use it?Apache 2.0Permissive; patent grantlicence file2026-10-24
Do people use it?1.4Mdownloads, 30 days#87 of 619 we track · top 14%+12 likes, downloads −6% this week844 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.

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

25 best of 33 tracked

The 3 picks above, plus these 22. 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. ArticleQwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1Msimonwillison.net · 2025-01-26 · 98 HN pts
  7. ArticleQwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Codingqwenlm.github.io · 2024-11-11 · 23 HN pts · official
  8. PaperQwen2.5-Coder Technical Report - arXivarxiv.org · undated
  9. PaperQwen2.5-Coder Technical Reportarxiv.org · undated
  10. ArticleCivic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt dataitsmeduncan.com · 2026-04-25 · 9 HN pts
  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 · 21 HN pts
  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. ArticleQwen2.5-Coder-7B Instruct: Precision Code 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 2In /1MOut /1MContextQuantSeen
1 Nscale $0.010 $0.030 128K — Oct 25
2 Featherless — — — — Oct 25

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 (269 quantized builds); a big base for builders (1,436 fine-tunes, adapters and merges).

  • As a service2Featherless, Nscale
  • On own hardware269quantized builds
  • Built on1,436488 fine-tunes · 828 adapters · 120 merges
  • In apps100+Hugging Face Spaces

Top Spaces running it: pliny-the-prompter/obliteratus ♥ 621 · embedl/hfviewer ♥ 181 · Bhaskar2611/Code_Generator_best ♥ 30 · yasserrmd/ReadMeForge ♥ 9

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 20 repo commits so far

Teal is the weights (2024-09-17), amber triangles are 7 dated articles (each links to it), grey ticks are repo commits.

OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-01-12: 1 repo commit2024-11-18: 1 repo commit2024-11-12: 1 repo commit2024-11-11: 1 repo commit2024-11-09: 2 repo commits2024-11-08: 1 repo commit2024-09-25: 1 repo commit2024-09-20: 1 repo commit2024-09-19: 2 repo commits2024-09-18: 7 repo commits2024-09-17: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Qwen2.5-Coder-32B is an LLM that can code well that runs on my Mac · 2024-11-13Show 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 · 2025-01-26Qwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Coding · 2024-11-11Civic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt data · 2026-04-25Qwen2.5-Coder-32B with coding abilities matching those of GPT-4o · 2024-11-09Weights 2024-09-17 · 2024-09-17Weights 2024-09-17now · 2 providers
OctNovDecJanFebMarAprMayJunJulAugSepOctNovDecJanFebMarAprMayJunJulAugSepOct2025-01-12: 1 repo commit2024-11-18: 1 repo commit2024-11-12: 1 repo commit2024-11-11: 1 repo commit2024-11-09: 2 repo commits2024-11-08: 1 repo commit2024-09-25: 1 repo commit2024-09-20: 1 repo commit2024-09-19: 2 repo commits2024-09-18: 7 repo commits2024-09-17: 2 repo commitsQwen2.5: A Party of Foundation Models · 2024-09-18Qwen2.5-Coder-32B is an LLM that can code well that runs on my Mac · 2024-11-13Show 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 · 2025-01-26Qwen2.5-Coder Beats GPT-4o and Claude 3.5 Sonnet in Coding · 2024-11-11Civic-SLM is a domain-specialized fine-tune of Qwen2.5-7B for U.S. govt data · 2026-04-25Qwen2.5-Coder-32B with coding abilities matching those of GPT-4o · 2024-11-09Weights 2024-09-17 · 2024-09-17Weights 2024-09-17now · 2 providers

What people built on it

1,705 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

1,705 derivatives on the Hub, led by 828 adapters

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

269 quantized (Hugging Face model tree)488 fine-tunes (Hugging Face model tree)120 merges (Hugging Face model tree)828 adapters (Hugging Face model tree)269 quantized488 fine-tunes120 merges828 adapters
269 quantized (Hugging Face model tree)488 fine-tunes (Hugging Face model tree)120 merges (Hugging Face model tree)828 adapters (Hugging Face model tree)269 quantized488 fine-tunes120 merges828 adapters
GGUF Qwen/Qwen2.5-Coder-7B-Instruct-GGUF for llama.cpp, Ollama, LM Studio 2.3M downloads MLX lmstudio-community/Qwen2.5-Coder-7B-Instruct-MLX-4bit for Apple silicon 156.7k downloads GPTQ Qwen/Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 for vLLM, SGLang 7.8M downloads

All variants →

Reference

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

What the card says

2 cited sentences

Summary generated, cited

Qwen2.5-Coder-7B-Instruct is a 7.62B parameter causal language model fine-tuned for code-specific tasks.[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 15:00 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:2409.12186, arXiv: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-Coder-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-Coder-7B (same organization) Family: Qwen/Qwen2.5 1,705 derivatives on the Hub

Base model: Qwen/Qwen2.5-Coder-7B

quantized: 269finetune: 488adapter: 828merge: 120

Top variants (40 shown, ranked by downloads)

Relation
Quant
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
Qwen/Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 quantized GPTQ 7.62B M apache-2.0 Qwen 23 7.8M
Qwen/Qwen2.5-Coder-7B-Instruct-AWQ quantized AWQ 7.62B M apache-2.0 Qwen 36 7.2M
nomic-ai/nomic-embed-code finetune — 7.07B M apache-2.0 nomic-ai 124 3.1M
Orion-zhen/Qwen2.5-Coder-7B-Instruct-AWQ quantized AWQ 7.62B M apache-2.0 Orion-zhen 1 2.4M
Qwen/Qwen2.5-Coder-7B-Instruct-GGUF quantized GGUF — — apache-2.0 Qwen 577 2.3M
bartowski/Qwen2.5-Coder-7B-Instruct-GGUF quantized GGUF — — apache-2.0 bartowski 74 1.4M
unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit quantized -bnb 7.82B M apache-2.0 unsloth 13 1.1M
unsloth/Qwen2.5-Coder-7B-Instruct finetune — 7.62B M apache-2.0 unsloth 13 632.6k
lmstudio-community/Qwen2.5-Coder-7B-Instruct-GGUF quantized GGUF — — apache-2.0 lmstudio-community 34 350.8k
bartowski/Qwen2.5.1-Coder-7B-Instruct-GGUF quantized GGUF — — apache-2.0 bartowski 128 249.9k
SWE-bench/SWE-agent-LM-7B finetune — 7.62B M apache-2.0 SWE-bench 8 250.5k
lmstudio-community/Qwen2.5-Coder-7B-Instruct-MLX-4bit quantized MLX 7.62B M apache-2.0 lmstudio-community 7 156.7k
unsloth/Qwen2.5-Coder-7B-Instruct-128K-GGUF quantized GGUF — — apache-2.0 unsloth 46 130.1k
nomic-ai/CodeRankLLM finetune — 7.61B M mit nomic-ai 23 110.6k
Snowflake/Arctic-Text2SQL-R1-7B finetune — 7.62B M apache-2.0 Snowflake 81 104.3k
Qwen/Qwen2.5-Coder-7B-Instruct-GPTQ-Int8 quantized GPTQ 7.62B M apache-2.0 Qwen 13 88.8k
vectionlabs/VL-1-Coder finetune — 7.62B M apache-2.0 vectionlabs 16 80k
unsloth/Qwen2.5-Coder-7B-Instruct-GGUF quantized GGUF — — apache-2.0 unsloth 23 57.9k
lmstudio-community/Qwen2.5-Coder-7B-Instruct-MLX-8bit quantized MLX 7.62B M apache-2.0 lmstudio-community 1 54.6k
OpenVINO/Qwen2.5-Coder-7B-Instruct-int8-ov quantized int8 — — apache-2.0 OpenVINO 1 37.8k
open-r1/OlympicCoder-7B finetune — 7.62B M apache-2.0 open-r1 185 23.4k
microsoft/NextCoder-7B finetune — 7.62B M mit microsoft 42 29k
MadeAgents/Hammer2.1-7b finetune — 7.61B M cc-by-nc-4.0 MadeAgents 35 25.4k
Tesslate/UIGEN-T1-7B-q8_0-GGUF quantized q8_0 — — apache-2.0 Tesslate 205 14.3k
AI-MO/Kimina-Autoformalizer-7B finetune — 7.62B M apache-2.0 AI-MO 21 21.2k
CISCai/Qwen2.5-Coder-7B-Instruct-SOTA-GGUF quantized GGUF — — apache-2.0 CISCai 0 21.8k
legraphista/Qwen2.5-Coder-7B-Instruct-IMat-GGUF quantized GGUF — — apache-2.0 legraphista 0 21.3k
second-state/Qwen2.5-Coder-7B-Instruct-GGUF quantized GGUF — — apache-2.0 second-state 0 20.8k
outflanknl/Dante-7B finetune — 7.62B M apache-2.0 outflanknl 29 19.1k
ggml-org/Qwen2.5-Coder-7B-Instruct-Q8_0-GGUF quantized Q8_0 — — apache-2.0 ggml-org 5 18.9k
OpenHands/openhands-lm-7b-v0.1 finetune — 7.62B M mit OpenHands 82 12.1k
Mungert/NextCoder-7B-GGUF quantized GGUF — — mit Mungert 7 14.2k
Mungert/nomic-embed-code-GGUF quantized GGUF — — apache-2.0 Mungert 1 14k
Kondara/Qwen2.5-Coder-7B-Instruct-Q4_K_M-GGUF quantized GGUF — — apache-2.0 Kondara 6 12k
mradermacher/Qwen2.5-Coder-7B-Instruct-i1-GGUF quantized GGUF — — apache-2.0 mradermacher 2 11.8k
mlc-ai/Qwen2.5-Coder-7B-Instruct-q4f32_1-MLC quantized — — — — mlc-ai 0 11.7k
Mungert/UIGEN-T2-7B-GGUF adapter GGUF — — apache-2.0 Mungert 2 11.4k
Tesslate/UIGEN-T2-7B adapter — 7.62B M apache-2.0 Tesslate 59 7k
Mungert/OlympicCoder-7B-GGUF quantized GGUF — — apache-2.0 Mungert 4 9.7k
gaianet/Qwen2.5-Coder-7B-Instruct-GGUF quantized GGUF — — apache-2.0 gaianet 0 9.5k

Repository changelog

20 commits
changed in the last 7 daysNew providers: 2026-10-23Other: 2026-10-24, 2026-10-24all changes

Repository changelog 20 commits

DateCommitSHA
2025-01-12 Update README.md c03e6d3
2024-11-18 update tokenizer_config.json,config.json,generation_config.json 0eb6b1e
2024-11-12 update README.md 4bbe56d
2024-11-11 Update README.md 1a90645
2024-11-09 Update README.md 0194b90
2024-11-09 Update config.json 014013f
2024-11-08 Update README.md bc87297
2024-09-25 Update README.md 7b148ce
2024-09-20 Update README.md (#4) e16f322
2024-09-19 Update README.md (#3) 3030861
2024-09-19 Upload ./tokenizer_config.json with huggingface_hub 0b044f5
2024-09-18 update README & config.json 6862201
2024-09-18 update README & config.json d619c0c
2024-09-18 update README & LICENSE 484fdb9
2024-09-18 Upload LICENSE dcc04bb
2024-09-18 Update README.md a4295b0
2024-09-18 Create README.md (#1) b94130e
2024-09-18 Update tokenizer_config.json 8d20e2b
2024-09-17 Upload folder using huggingface_hub 6ab006b
2024-09-17 initial commit 512a76b

All providers

2 providers · 2 endpoints

Where to run 2 providers · 2 endpoints

Hosted endpoints observed for Qwen2.5-Coder-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: $0.01/M.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Nscale
hf
 Qwen/Qwen2.5-Coder-7B-Instruct 128K — $0.01 $0.03 142.8 400 ms no live 2026-10-25
Featherless
hf
 Qwen/Qwen2.5-Coder-7B-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.

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-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

Analysis8

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.
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
Qwen2.5-Coder Technical Report - arXiv
arxiv.orgauthorityabout the Qwen2.5 family14,816 words
Qwen2.5 Coder 7B - Intelligence, Performance & Price Analysis
artificialanalysis.aiauthority
Qwen2.5-Coder Technical Report
arxiv.orgauthorityabout the Qwen2.5 family14,825 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
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
All coverage tracked for this model (33) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Qwen2.5-Coder Technical Report - arXivarxiv.org—2026-10-07exa
Qwen2.5 Coder 7B - Intelligence, Performance & Price Analysisartificialanalysis.ai—2026-10-07exa
Qwen2.5-Coder Technical Reportarxiv.org—2026-10-07exa
Qwen2.5-Coder-7B Instruct: Precision Code LLMemergentmind.com—2026-10-07exa
Qwen 2.5 Coder 7B | Open Laboratoryopenlaboratory.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
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, exa
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
Qwen2.5-Coder Technical Reportexa.ai2024-09-182026-10-07exa
Qwen2.5-Coder Technical Report [Quick Review]liner.com2024-09-182026-10-07exa
qwen / qwen2.5-coder-7b-instructdocs.api.nvidia.com2024-03-112026-10-07exa

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).

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  • DeepSeek-R1-Distill-Qwen-7B · 7.62B
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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · HF API: 2026-10-24 21:33 UTC · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:45 UTC · Summary: 2026-10-07 15:00 UTC · Last verified 2026-10-25

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