Qwen3-Coder-480B-A35B-Instruct

480B parameters, 35B active (8 of 160 experts per token), text in, text out, 256K tokens of context. 4 providers serve it.

Verified 2026-10-25 Rank #123 in LLMs · score 95.3 method v1 Sources 4 Downloads 30d 55.7k · #376 of 619 tracked

Can I run it?288GB at INT4Estimateneeds a multi-GPU nodemethodCommunity: qwen3-coder-480b-a35b-instruct — Parameters, Context, Benchmarks & Pricing | AI Atlas →

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

Does it work?69.6on SWE-bench Verified#5 of 22 measuredleaderboard2025-08-05

Do people use it?55.7kdownloads, 30 days#376 of 619 we track · below the median+3 likes, downloads +32% this week1,384 likesHugging Face2026-10-24

Worth reading

Picked by rule from 18 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Most discussed · 490 HN pts

GPT-OSS vs. Qwen3 and a detailed look how things evolved since GPT-2

OpenAI released gpt-oss-120b and gpt-oss-20b, their first open-weight models since GPT-2 in 2019.

A 2025 research paper confirms Dropout results in worse downstream performance in single-epoch regimes.

magazine.sebastianraschka.com 2025-08-10 490 HN pts · 97 comments 5.2k words about the Qwen3 family family

Latest · 8 months ago

Qwen3.5 122B and 35B models offer Sonnet 4.5 performance on local computers

venturebeat.com 2026-02-28 461 HN pts · 272 comments about the Qwen3 family family

18 best of 18 tracked

The 3 picks above, plus these 15. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

ArticleQwen3-Coder-Nextqwen.ai · 2026-02-03 · 735 HN pts · official
ArticleQwen3-Max-Thinkingqwen.ai · 2026-01-26 · official
ArticleQwen3-TTS family is now open sourced: Voice design, clone, and generationqwen.ai · 2026-01-22 · official
ArticleQwen3: Think deeper, act fasterqwenlm.github.io · 2025-04-28 · 869 HN pts · official
ArticleQwen3-Coder: Agentic coding in the worldqwenlm.github.io · 2025-07-22 · 765 HN pts · official
ArticleQwen3-Nextqwen.ai · 2025-09-12 · official
ArticleQwen3-VLqwen.ai · 2025-09-23 · official
CodeQwen3-Omni: Native Omni AI model for text, image and videogithub.com · 2025-09-22
ArticleQwen3.5 397B A17B (Reasoning) vs Qwen3 Coder 480B A35B Instruct: Model Comparison | Artificial Analysisartificialanalysis.ai · undated
ArticleQwen3-Coder 480B Review (2026): Free Frontier Coder on OpenRouter — But Is It Still Worth It?toolbrain.net · 2026-08-28
CodeREADME.mdgithub.com · undated
ArticleQwen3-Coder 480B: Inside Alibaba's Agentic Coding Model | ThinkSmart.Life Researchthinksmart.life · undated
Articleqwen3-coder-480b-a35b-instruct — Parameters, Context, Benchmarks & Pricing | AI Atlasai-atlas.co · undated
ArticleQwen3-Coder-480B-A35B-Instruct – 262k context, open source | LLM Referencellmreference.com · undated
ArticleQwen3 Coder 480B A35B API Benchmarks: Latency & Costdeepinfra.com · 2026-04-03

Show all 15

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 4 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 4 API providers; 35 quantized builds for local use.

As a service4DeepInfra, Featherless, Google, Venice
On own hardware35quantized builds
Built on2014 fine-tunes · 5 adapters · 1 merges
In apps100+Hugging Face Spaces

Top Spaces running it: hadadxyz/ai ♥ 819 · umint/ai ♥ 258 · lvwerra/jupyter-agent-2 ♥ 254 · modelscope/modelscope-studio ♥ 72

Will it fit?

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

Needs an 8×80 GB node even at INT4

About 288 GB at INT4, 576 GB at FP8, 1.15 TB at BF16: weights only, so leave room for the KV cache. Every expert must be resident, so total parameters count.

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.

#5 of 22 on SWE-bench Verified so far

69.6. Each tick is a model on this site with a measured SWE-bench Verified row; author-reported numbers stay in Reference. Percent resolved. agent: OpenHands

Source · leaderboard · 2025-08-05

The story so far

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

7 dated articles and 16 repo commits so far

Teal is the weights (2025-07-22), amber triangles are 7 dated articles (each links to it), grey ticks are repo commits.

What people built on it

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

55 derivatives on the Hub, most of them quantized

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

GGUF unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF for llama.cpp, Ollama, LM Studio 225.1k downloads MLX lmstudio-community/Qwen3-Coder-480B-A35B-Instruct-MLX-6bit for Apple silicon 414.6k downloads AWQ QuantTrio/Qwen3-Coder-480B-A35B-Instruct-AWQ for vLLM, SGLang 75.2k downloads

All variants →

Reference

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

Benchmarks

2 rows

Benchmarks 2 rows

measured third-party leaderboard row (2)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 SWE-bench Verified · Write code with agents	69.6 percent resolved	agent: OpenHands	leaderboard	2025-08-05
measured SWE-bench Verified · Write code with agents	55.4 percent resolved	agent: mini-SWE-agent	leaderboard	2025-08-02

What the card says

1 cited sentence

Summary generated, cited

It features a native context length of 262,144 tokens and is released under the Apache 2.0 license.^[1]^[2]

“Context Length: 262,144 natively.”
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

24 fields

Listed in LLMs · MoE

Facts

Qwen3-Coder-480B-A35B-Instruct has 480B parameters (35B active per token). (safetensors metadata, observed 2026-10-24)
Qwen3-Coder-480B-A35B-Instruct is a mixture-of-experts model with 160 experts, routing 8 per token. (config.json, observed 2026-10-24)
Context length is 262,144 tokens (256K). (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 2025-07-22, last modified 2025-08-21. (HF API, observed 2026-10-24)

Pipeline tag	text-generation
Library	transformers
Architectures	Qwen3MoeForCausalLM
Model type	qwen3_moe
Dtype	bfloat16
Params by dtype	BF16: 480,154,875,392
Size band	XXL
MoE	yes
Experts	160
Experts per token	8
Context length	262,144 (config.json max_position_embeddings)
Papers	arXiv:2505.09388
License	Apache 2.0 (apache-2.0)
Hub snapshot	2026-10-25

Servability

vLLM · SGLang

Servability

vLLM: supported · Qwen3MoeForCausalLM · 7050ef881ff0835f6890a47db1859a24c65481d6SGLang: supported · Qwen3MoeForCausalLM · 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 Qwen3-Coder-480B-A35B-Instruct: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)	1.15 TB · Cluster (≥640 GB)
FP8 (1 byte/param)	576 GB · Multi-GPU node (<640 GB)
INT4 (0.5 bytes/param)	288 GB · Multi-GPU node (<640 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra. MoE: all experts must be resident, so total parameters count.

All variants

40 variants

Lineage

Original model Family: Qwen/Qwen3 55 derivatives on the Hub

quantized: 35finetune: 14merge: 1adapter: 5

Top variants (40 shown, ranked by downloads)

Variant	Relation	Quant	Params	Band	License	Author	Likes	Downloads
lmstudio-community/Qwen3-Coder-480B-A35B-Instruct-MLX-6bit	quantized	MLX	480B	XXL	apache-2.0	lmstudio-community	5	414.6k
lmstudio-community/Qwen3-Coder-480B-A35B-Instruct-MLX-4bit	quantized	MLX	480B	XXL	apache-2.0	lmstudio-community	4	412k
lmstudio-community/Qwen3-Coder-480B-A35B-Instruct-MLX-8bit	quantized	MLX	480B	XXL	apache-2.0	lmstudio-community	4	400.9k
unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	unsloth	180	225.1k
mlx-community/Qwen3-Coder-480B-A35B-Instruct-4bit	quantized	-4bit	480B	XXL	apache-2.0	mlx-community	19	105.5k
mlx-community/Qwen3-Coder-480B-A35B-Instruct-8bit	quantized	-8bit	480B	XXL	apache-2.0	mlx-community	0	93.3k
QuantTrio/Qwen3-Coder-480B-A35B-Instruct-AWQ	quantized	AWQ	480B	XXL	apache-2.0	QuantTrio	8	75.2k
lmstudio-community/Qwen3-Coder-480B-A35B-Instruct-GGUF	quantized	GGUF	—	—	—	lmstudio-community	1	40.6k
unsloth/Qwen3-Coder-480B-A35B-Instruct-1M-GGUF	quantized	GGUF	—	—	apache-2.0	unsloth	46	34.1k
Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-AutoRound	quantized	int4	1.93B	S	apache-2.0	Intel	9	34.2k
bartowski/Qwen_Qwen3-Coder-480B-A35B-Instruct-GGUF	quantized	GGUF	—	—	—	bartowski	5	16.3k
nvidia/Qwen3-Coder-480B-A35B-Instruct-NVFP4	quantized	NVFP4	241B	XXL	apache-2.0	nvidia	22	13.5k
ubergarm/Qwen3-Coder-480B-A35B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	ubergarm	17	7.7k
QuantTrio/Qwen3-Coder-480B-A35B-Instruct-GPTQ-Int4-Int8Mix	quantized	GPTQ	534B	XXL	apache-2.0	QuantTrio	7	7.1k
DevQuasar/Qwen.Qwen3-Coder-480B-A35B-Instruct-GGUF	quantized	GGUF	—	—	—	DevQuasar	1	7.3k
NVFP4/Qwen3-Coder-480B-A35B-Instruct-FP4	quantized	—	241B	XXL	apache-2.0	NVFP4	3	5.4k
INC4AI/Qwen3-Coder-480B-A35B-Instruct-gguf-q2ks-mixed-AutoRound	quantized	gguf	—	—	apache-2.0	INC4AI	14	3.8k
amd/Qwen3-Coder-480B-A35B-Instruct-MXFP4	quantized	MXFP4	246B	XXL	apache-2.0	amd	0	4.2k
John1604/Qwen3-Coder-480B-A35B-Instruct-gguf	quantized	gguf	—	—	apache-2.0	John1604	2	2.5k
RedHatAI/Qwen3-Coder-480B-A35B-Instruct-FP8	quantized	-FP8	480B	XXL	apache-2.0	RedHatAI	3	1.5k
tachyphylaxis/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF	quantized	GGUF	—	—	apache-2.0	tachyphylaxis	2	1.4k
unsloth/Qwen3-Coder-480B-A35B-Instruct-1M	finetune	—	480B	XXL	apache-2.0	unsloth	8	870
cerebras/Qwen3-Coder-REAP-363B-A35B	finetune	—	363B	XXL	apache-2.0	cerebras	6	751
unsloth/Qwen3-Coder-480B-A35B-Instruct	finetune	—	480B	XXL	apache-2.0	unsloth	5	761
anikifoss/Qwen3-Coder-480B-A35B-Instruct-HQ4_K	quantized	GGUF	—	—	apache-2.0	anikifoss	1	799
cerebras/Qwen3-Coder-REAP-246B-A35B	finetune	—	246B	XXL	apache-2.0	cerebras	8	432
noctrex/Qwen3-Coder-480B-A35B-Instruct-1M-MXFP4_MOE-GGUF	finetune	GGUF	—	—	—	noctrex	3	494
AmpereComputing/qwen-3-coder-a35b-480b-instruct-gguf	quantized	gguf	—	—	—	AmpereComputing	0	556
richardyoung/Qwen3-Coder-480B-GGUF	quantized	GGUF	—	—	apache-2.0	richardyoung	0	434
mradermacher/Qwen3-Coder-480B-A35B-Instruct-i1-GGUF	quantized	GGUF	—	—	apache-2.0	mradermacher	1	345
sokann/Qwen3-Coder-480B-A35B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	sokann	0	346
OPENZEKA/Qwen3-Coder-480B-A35B-Instruct-NVFP4	quantized	NVFP4	241B	XXL	apache-2.0	OPENZEKA	0	329
AbteeXAILab/lumynax-frontier-coder-qwen3-480b-a35b-gguf	quantized	gguf	—	—	apache-2.0	AbteeXAILab	0	254
Emanresu/Qwen3-Coder-480B-A35B-Instruct-GGUF	quantized	GGUF	—	—	apache-2.0	Emanresu	0	239
K168-V0JL/Omega-AI-450B	finetune	—	480B	XXL	—	K168-V0JL	0	203
exodusubuntu/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF	quantized	GGUF	—	—	apache-2.0	exodusubuntu	0	185
anirudmohan26/qwen3-480b-fused-nvfp4	quantized	nvfp4	271B	XXL	—	anirudmohan26	0	100
anirudmohan26/Qwen3-coder-480B-fused-bf16	finetune	-bf16	480B	XXL	—	anirudmohan26	0	96
dokjlahdf/Huihui-Qwen3-Coder-480B-A35B-Instruct-abliterated-GGUF	quantized	GGUF	—	—	apache-2.0	dokjlahdf	0	94
Cirrascale/Qwen3-Coder-480B-A35B-Instruct-NVFP4	quantized	NVFP4	241B	XXL	apache-2.0	Cirrascale	0	86

Repository changelog

16 commits

Repository changelog 16 commits

Date	Commit	SHA
2025-08-21	Update chat_template and tool_parser (#27)	9d90cf8
2025-08-07	Update chat_template in tokenizer_config.json (#25)	fecb593
2025-07-24	Create LICENSE	fa2f1d4
2025-07-24	Update README.md	2f1d70b
2025-07-23	Update README.md (#4)	fafbb23
2025-07-23	Update README.md	11312d1
2025-07-22	Update README.md	7103b5f
2025-07-22	Rename qwen3_xml_tool_parser.py to qwen3coder_tool_parser.py	a08e476
2025-07-22	Upload tokenizer_config.json	8476f52
2025-07-22	Upload 4 files	de5f0dd
2025-07-22	Update README.md	7dd863c
2025-07-22	Add files using upload-large-folder tool	6466868
2025-07-22	Add files using upload-large-folder tool	64add8b
2025-07-22	Add files using upload-large-folder tool	7cf2fa4
2025-07-22	Add files using upload-large-folder tool	71e6659
2025-07-22	initial commit	3db6b06

All providers

4 providers · 4 endpoints

Where to run 4 providers · 4 endpoints

Hosted endpoints observed for Qwen3-Coder-480B-A35B-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: $0.22/M.

Provider	Model ref	Context	Quant	$/M in	$/M out	tok/s	TTFT	Tools	Status	Observed
Google openrouter	qwen/qwen3-coder	256K	unknown	$0.22	$1.80	—	—	yes	status -5	2026-10-24
DeepInfra openrouter	qwen/qwen3-coder	256K	fp4	$0.30	$1.00	—	—	yes	status -2	2026-10-24
Venice openrouter	qwen/qwen3-coder	250K	fp8	$0.35	$1.50	—	—	yes	status -2	2026-10-24
Featherless hf	Qwen/Qwen3-Coder-480B-A35B-Instruct	—	—	—	—	—	—	—	live	2026-10-25

Articles and coverage

18 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

Qwen3-Coder-Next

qwen.ai2026-02-03officialauthorityHN front pageabout the Qwen3 familyHN 735 pts · 429 comments674 words

Qwen3-Coder-Next is an open-weight language model designed for coding agents and local development. The model achieves over 70% on SWE-Bench Verified using the SWE-Agent scaffold while maintaining a 3B active footprint. This small active footprint achieves SWE-Bench-Pro performance comparable to models with 10x-20x more active parameters.written, reviewed, cited

The model is built on top of Qwen3-Next-80B-A3B-Base, which adopts a novel architecture with hybrid attention and MoE.
Training includes continued pretraining on code- and agent-centric data alongside supervised fine-tuning on high-quality agent trajectories.
The model emphasizes long-horizon reasoning, tool usage, and recovery from execution failures for real-world coding agents.

Qwen3: Think deeper, act faster

qwenlm.github.io2025-04-28officialauthorityHN front pageabout the Qwen3 familyHN 869 pts · 388 comments2,139 words

Qwen3 introduces Hybrid Thinking Modes, allowing users to toggle between step-by-step reasoning and rapid responses via computational budget control. The open-weight MoE model Qwen3-235B-A22B achieves performance similar to dense models while using only 10% of the active parameters. Pre-training utilized approximately 36 trillion tokens across 119 languages, with deployment supported by SGLang and vLLM.written, reviewed, cited

Qwen3-8B and Qwen3-14B models do not use tied embeddings, unlike smaller variants.
The pre-training pipeline includes a final stage extending context length to 32K tokens.

Qwen3-Coder: Agentic coding in the world

qwenlm.github.io2025-07-22officialauthorityHN front pageabout the Qwen3 familyHN 765 pts · 366 comments958 words

Analysis7

Qwen3.5 122B and 35B models offer Sonnet 4.5 performance on local computers

venturebeat.com2026-02-28HN front pageabout the Qwen3 familyHN 461 pts · 272 comments

GPT-OSS vs. Qwen3 and a detailed look how things evolved since GPT-2

magazine.sebastianraschka.com2025-08-10authorityHN front pageabout the Qwen3 familyHN 490 pts · 97 comments5,195 words

OpenAI released gpt-oss-120b and gpt-oss-20b, their first open-weight models since GPT-2 in 2019. The 20B model can run on a consumer GPU with up to 16 GB of RAM, and the 120B model can run on a single H100 with 80 GB of RAM or newer hardware. The models utilize MXFP4 optimization to fit onto single GPUs.written, reviewed, cited

A 2025 research paper confirms Dropout results in worse downstream performance in single-epoch regimes.

Qwen3.5 397B A17B (Reasoning) vs Qwen3 Coder 480B A35B Instruct: Model Comparison | Artificial Analysis

artificialanalysis.aiauthority

Qwen3-Coder 480B Review (2026): Free Frontier Coder on OpenRouter — But Is It Still Worth It?

toolbrain.net2026-08-28about the Qwen3 family

README.md

github.comauthorityabout the Qwen3 family

Show HN: Qwen3-Coder API – 480B open-source code LLM

netmind.ai2025-07-24HN 3 pts · 1 comments

Qwen3-Coder 480B: Inside Alibaba's Agentic Coding Model | ThinkSmart.Life Research

thinksmart.lifeabout the Qwen3 family

All coverage tracked for this model (18) — append-only, nothing is ever removed

Title	Source	Published	First seen	Signals
Qwen3.5 397B A17B (Reasoning) vs Qwen3 Coder 480B A35B Instruct: Model Comparison \| Artificial Analysis	artificialanalysis.ai	—	2026-10-07	exa
README.md	github.com	—	2026-10-07	exa
Qwen3-Coder 480B: Inside Alibaba's Agentic Coding Model \| ThinkSmart.Life Research	thinksmart.life	—	2026-10-07	exa
qwen3-coder-480b-a35b-instruct — Parameters, Context, Benchmarks & Pricing \| AI Atlas	ai-atlas.co	—	2026-10-07	exa
Qwen3-Coder-480B-A35B-Instruct – 262k context, open source \| LLM Reference	llmreference.com	—	2026-10-07	exa
Qwen3-Coder 480B Review (2026): Free Frontier Coder on OpenRouter — But Is It Still Worth It?	toolbrain.net	2026-08-28	2026-10-07	exa
Qwen3 Coder 480B A35B API Benchmarks: Latency & Cost	deepinfra.com	2026-04-03	2026-10-07	exa
Qwen3.5 122B and 35B models offer Sonnet 4.5 performance on local computers	venturebeat.com	2026-02-28	2026-10-07	hn
Qwen3-Coder-Next	qwen.ai official	2026-02-03	2026-10-07	hn
Qwen3-Max-Thinking	qwen.ai official	2026-01-26	2026-10-07	hn
Qwen3-TTS family is now open sourced: Voice design, clone, and generation	qwen.ai official	2026-01-22	2026-10-07	hn
Qwen3-VL	qwen.ai official	2025-09-23	2026-10-07	hn
Qwen3-Omni: Native Omni AI model for text, image and video	github.com	2025-09-22	2026-10-07	hn
Qwen3-Next	qwen.ai official	2025-09-12	2026-10-07	hn
GPT-OSS vs. Qwen3 and a detailed look how things evolved since GPT-2	magazine.sebastianraschka.com	2025-08-10	2026-10-07	hn
Show HN: Qwen3-Coder API – 480B open-source code LLM	netmind.ai	2025-07-24	2026-10-07	hn
Qwen3-Coder: Agentic coding in the world	qwenlm.github.io official	2025-07-22	2026-10-07	hn
Qwen3: Think deeper, act faster	qwenlm.github.io official	2025-04-28	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).

Qwen3 Technical Report this model

An Yang, Anfeng Li, Baosong Yang +57 · 2025-05-14 · PDF · HF paper page (349 upvotes)

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Sources

4 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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