Qwen3 VL 8B Instruct
Qwenhuggingface.co/Qwen/Qwen3-VL-8B-Instruct
Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...
Updated 8 h ago · first seen 11 Sept 2026
model_01M294WWAD8V5ZJY2EYQWD4RF8
Overview
Identity
Identity block not returned by the API for this entity.
Openness
Openness not classified yet — no sourced evidence to place this model in the ontology.
Key facts
- Release date
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 10 h agomedium
- Status
Source:Artificial AnalysisT2observed 13 h agomedium
- Model card
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
- 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
- imagetext
- Input
- imagetext
- Output
- text
Capabilities
Tool calling
Yes
OpenRouter public model & pricing listing · T2
Structured output
Yes
OpenRouter public model & pricing listing · T2
Reasoning
No
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 12 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
- Tokenizer
Source:OpenRouter public model & pricing listingT2observed 15 h agomedium
Benchmarks7
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
No benchmark results recorded
Providers & Pricing1
All offers in the price terminal →USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.
Price history
Output price · USD / 1M tokens 1 provider
- OpenRouter
- OpenRouterfirst observed $0.45511 Sept 2026
Input price · USD / 1M tokens 1 provider
- OpenRouter
- OpenRouterfirst observed $0.11711 Sept 2026
Hardware fit37
Assumptions (6)
- Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead.
- bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
- KV cache approximated at 0.5 GB per 8 192 tokens of context, 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).
Lineage
Open in Graph →Papers4
- arXiv:2505.09388Active35
- arXiv:2502.13923Active35
- arXiv:2409.12191Active35
- arXiv:2308.12966Active35
Timeline13
Full timeline →Qwen3 VL 8B Instruct: context length changed from 256000 to 262144
Context window256K tokens→262.1K tokensopenrouterQwen3 VL 8B Instruct scores 2.27% on Terminal-Bench
artificial_analysisQwen3 VL 8B Instruct scores 29.24% on τ²-bench
artificial_analysisQwen3 VL 8B Instruct scores 47.34% on MMMU-Pro
artificial_analysisQwen3 VL 8B Instruct scores 32.31% on IFBench
artificial_analysisQwen3 VL 8B Instruct scores 2.69% on Humanity's Last Exam
artificial_analysisQwen3 VL 8B Instruct scores 42.73% on GPQA
artificial_analysisQwen3 VL 8B Instruct scores 7.26 on Artificial Analysis Intelligence Index
artificial_analysisQwen3 VL 8B Instruct: context length changed from 262144 to 256000
Context window262.1K tokens→256K tokensartificial_analysisQwen3 VL 8B Instruct: release date changed from 2025-10-11 to 2025-10-14
Release date11 Oct 2025→14 Oct 2025openrouterQwen3 VL 8B Instruct: release date changed from 2025-10-14 to 2025-10-11
Release date14 Oct 2025→11 Oct 2025huggingfaceOpenRouter lists Qwen3 VL 8B Instruct at $0.117 in / $0.455 out per 1M tokens
openrouter
Change history42
Viewing AI Atlas as of 12 Mar 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →Qwen3 VL 8B Instruct was not yet in AI Atlas on 12 Mar 2026
Release daterelease_date6
Statusstatus1
Opennessopenness1
Licenselicense1
Architecturearchitecture1
Parametersparameter_count1
Context windowcontext_length3
Max outputmax_output_tokens1
Modalitiesmodalities1
Input modalitiesmodalities_input1
Output modalitiesmodalities_output1
Tokenizertokenizer1
File sizefile_size_gb1
Hugging Face repohf_repo1
Pipeline tagpipeline_tag1
Model cardmodel_card_url1
Downloadsmetric.downloads1
Likesmetric.likes2
Descriptiondescription1
Gatedgated1
Hf inference providershf_inference_providers1
Last modifiedlast_modified1
Library namelibrary_name1
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second1
Downloads all timemetric.downloads_all_time1
Model typemodel_type1
Openrouter idopenrouter_id1
Reasoningreasoning1
Structured outputstructured_output1
Supported parameterssupported_parameters1
Tool callingtool_calling1
Visionvision1
Weights dtypeweights_dtype1
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
35
Source tiers
T235
Freshest observation
8 h ago
Conflicts
None
Source documents 6
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (68/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →