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Qwen3.6 35B A3B

Qwenfamily · Qwen3.6huggingface.co/Qwen/Qwen3.6-35B-A3B

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...

Open in Graph
data quality72

Updated 5 h ago · first seen 11 Sept 2026

model_01M294WW00HFKTBSY2DM4THGPV

Overview

Identity

Canonical model
Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
Official checkpoints
official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
Artifacts
7 quantizations0 official · 7 third-partySeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
Provider deployments
1
API aliases
qwen/qwen3.6-35b-a3bqwen3-6-35b-a3bqwen3-6-35b-a3b-non-reasoningIdentifiers under which providers and evaluators refer to this model.
Folded evaluation variants
1Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Open weights— weights downloadable under Apache-2.0; commercial use allowed; redistribution allowed; derivatives allowed; 4 dimensions unknown.

Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.

  • Weights

    Yes

  • Inference code

    —

  • Training code

    —

  • Training data

    —

  • Dataset

    —

  • Commercial use

    Yes

  • Redistribution

    Yes

  • Derivatives

    Yes

Licence: Apache License 2.0 (permissive · SPDX Apache-2.0 · stated as “apache-2.0”)

dimensions marked null are unknown, not false

Key facts

Release date

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium

Model card
huggingface.co/Qwen/Qwen3.6-35B-A3B

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 h agomedium

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 15 h agomedium

Architecture

Architecture

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Model type

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 h agomedium

Active parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 15 h agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Library name

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 15 h agomedium

Hugging Face repo

Source:OpenRouter public model & pricing listingT2observed 15 h agomedium

Capabilities

Modalities

Modalities
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Input
imagetextvideo
Output
text

Capabilities

  • Tool calling

    Yes

    OpenRouter public model & pricing listing · T2

  • Structured output

    Yes

    OpenRouter public model & pricing listing · T2

  • Reasoning

    Yes

    Artificial Analysis · T2

  • Vision

    Yes

    OpenRouter public model & pricing listing · T2

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:OpenRouter public model & pricing listingT2observed 15 h agomedium

Max output

Source:OpenRouter public model & pricing listingT2observed 15 h agomedium

Tokenizer

Source:OpenRouter public model & pricing listingT2observed 15 h agomedium

Benchmarks36

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

Benchmark results grouped by comparability group
Benchmark · groupBest scoreTrustConfigurationResultsvs leaderEvaluatedSource
Terminal-Benchagentic · accuracy · variant=hard · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvarianthardreasoningonconditions differ across rows → partially comparable4−31.1 ptvs gpt-5.6-solobs. 12 Sept 2026artificialanalysis.aiT2
Terminal-Benchagentic · accuracy · variant=v4.0 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv4.0reasoningonconditions differ across rows → partially comparable2non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
Terminal-Benchagentic · accuracy · variant=v2.1 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv2.1reasoningonconditions differ across rows → partially comparable4non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
τ²-benchagentic · pass^1 · variant=Telecom · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantTelecomreasoningonconditions differ across rows → partially comparable2non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
τ²-benchagentic · pass^1 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysis2−3.80 ptvs Z.ai GLM 5.2obs. 11 Sept 2026artificialanalysis.aiT2
SciCodecoding · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable2−26.5 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
Artificial Analysis Intelligence Indexcomposite · indexIndependentreasoningonversion4.3conditions differ across rows → partially comparable4−34.6vs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
IFBenchinstruction-following · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable4−19.0 ptvs Grok 4.3obs. 12 Sept 2026artificialanalysis.aiT2
Humanity's Last Examknowledge · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable4−36.9 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
MMMU-Promultimodal · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable4−11.8 ptvs gpt-6-astraobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantDiamondreasoningonconditions differ across rows → partially comparable2non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=GPQA Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantGPQA Diamond2−12.1 ptvs gpt-6-astraobs. 11 Sept 2026artificialanalysis.aiT2

Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 36 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →

Providers & Pricing1

All offers in the price terminal →
Provider deployments, cheapest output first
ProviderContextInput / 1MCached inOutput / 1MStatusObservedSource
OpenRoutercheapest outputqwen/qwen3.6-35b-a3b262.1Kout 235.9K$0.05active2 h agosince 11 Sept 2026openrouter.aiT2

USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 1 provider

Output price history of Qwen3.6 35B A3B$0$0.20$0.40$0.60$0.80$1$1.2Sept 26Sept 26Sept 26Sept 26Sept 26OpenRouter: first observed → $0.90 · 11 Sept 2026
  • OpenRouter
  • OpenRouterfirst observed $0.9011 Sept 2026

Input price · USD / 1M tokens 1 provider

Input price history of Qwen3.6 35B A3B$0$0.02$0.04$0.06$0.08$0.10$0.12Sept 26Sept 26Sept 26Sept 26Sept 26OpenRouter: first observed → $0.10 · 11 Sept 2026
  • OpenRouter
  • OpenRouterfirst observed $0.1011 Sept 2026

Hardware fit37

Estimated

36 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit—21.2 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit—21.2 GB est.Yes
Apple M2 Ultra4bit—21.2 GB est.Yes
Apple M1 Ultra4bit—21.2 GB est.Yes
Apple M3 Max4bit—21.2 GB est.Yes
Apple M4 Max4bit—21.2 GB est.Yes
Mac Studio (Apple M5 Max)4bit—21.2 GB est.Yes
MacBook Pro (Apple M5 Max)4bit—21.2 GB est.Yes
Apple M2 Max4bit—21.2 GB est.Yes
Apple M1 Max4bit—21.2 GB est.Yes
Apple M4 Pro4bit—21.2 GB est.Yes
Mac mini (Apple M5 Pro)4bit—21.2 GB est.Yes
MacBook Pro (Apple M5 Pro)4bit—21.2 GB est.Yes
Apple M3 Pro4bit—21.2 GB est.Yes
Apple M1 Pro4bit—21.2 GB est.Yes
Apple M2 Pro4bit—21.2 GB est.Yes
Apple M44bit—21.2 GB est.Yes
iMac (Apple M4)4bit—21.2 GB est.Yes
Mac mini (Apple M6)4bit—21.2 GB est.Yes
MacBook Air (Apple M5)4bit—21.2 GB est.Yes
MacBook Pro (Apple M5)4bit—21.2 GB est.Yes
Apple M24bit—21.2 GB est.Yes
Apple M34bit—21.2 GB est.Yes
NVIDIA GeForce RTX 30904bit24 GB21.2 GB est.Yes
NVIDIA GeForce RTX 40904bit24 GB21.2 GB est.Yes
NVIDIA GeForce RTX 50904bit32 GB21.2 GB est.Yes
NVIDIA A100 80GB4bit80 GB21.2 GB est.Yes
NVIDIA H100 SXM4bit80 GB21.2 GB est.Yes
NVIDIA H100 NVL4bit94 GB21.2 GB est.Yes
NVIDIA DGX Spark4bit128 GB21.2 GB est.Yes
NVIDIA H2004bit141 GB21.2 GB est.Yes
NVIDIA H200 NVL4bit141 GB21.2 GB est.Yes
NVIDIA B2004bit180 GB21.2 GB est.Yes
AMD Instinct MI300X4bit192 GB21.2 GB est.Yes
AMD Instinct MI325X4bit256 GB21.2 GB est.Yes
NVIDIA DGX B2004bit1,440 GB21.2 GB est.Yes
Apple M14bit—21.2 GB est.No
Assumptions (7)
  • Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead (or the observed artifact file size when one is recorded).
  • bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
  • KV cache: 2 × layers × kv_heads × head_dim × 2 bytes × context × batch when the architecture is known; otherwise 0.5 GB per 8 192 tokens (× batch), independent of architecture (GQA/MLA models need less).
  • A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
  • Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
  • Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
  • Multi-GPU: device memories are summed; interconnect bandwidth, tensor-parallel replication and pipeline bubbles are not modelled.

Lineage

Open in Graph →
Explicit derived_from / fine_tuned_from / distilled_from relations stated by sources; artifacts collapsed by kind.
DESCENDANTS 0 · ARTIFACTS7 quantizationsartifacts · collapsed7 quantizations — artifacts · collapsedQwen3.6 35B A3B36B params · this modelQwen3.6 35B A3B — 36B params · this model

    Versions & Artifacts7

    Version history

    Context windowfirst observation only

    11 Sept 2026current

    Licensefirst observation only

    11 Sept 2026current

    Max outputfirst observation only

    11 Sept 2026current

    Opennessfirst observation only

    11 Sept 2026current

    Parametersfirst observation only

    11 Sept 2026current

    Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.

    Artifacts 7

    quantizations 7

    Timeline21

    Full timeline →

    Change history

    Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
    1 claims · 1 propertiesShow all properties

    Downloads all timemetric.downloads_all_time1

    Claim history for Downloads all time
    ValueValid from → toStatusSourceConfidenceExtractor
    27,245,155 → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

    Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

    Provenance

    Attributed facts

    44

    Source tiers

    T244

    Freshest observation

    5 h ago

    Conflicts

    None

    Source documents 12

    Source documents
    SourceDocumentTypeTierLast observedSnapshots
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/unsloth/Qwen3.6-35B-A3B-MTP-GGUF model_pageT2· Quality secondary5 min ago5
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF model_pageT2· Quality secondary5 min ago5
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/unsloth/Qwen3.6-35B-A3B-NVFP4 model_pageT2· Quality secondary5 min ago5
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/Qwen/Qwen3.6-35B-A3B-FP8 model_pageT2· Quality secondary12 min ago6
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/nvidia/Qwen3.6-35B-A3B-NVFP4 model_pageT2· Quality secondary15 min ago5
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/Intel/Qwen3.6-35B-A3B-int4-mixed-AutoRound model_pageT2· Quality secondary27 min ago5
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/bartowski/Qwen_Qwen3.6-35B-A3B-GGUF model_pageT2· Quality secondary39 min ago6
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=Qwen&p=0&sort=downloads listingT2· Quality secondary46 min ago8
    OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary2 h ago11
    Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary5 h ago2
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/Qwen/Qwen3.6-35B-A3B/raw/main/README.md model_cardT2· Quality secondary8 h ago1
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/Qwen/Qwen3.6-35B-A3B model_pageT2· Quality secondary9 h ago4

    Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

    Data quality (72/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →