Intel/Qwen3.8-Flash-Next-W4A16-AutoRound
Updated 9 h ago · first seen 11 Sept 2026
model_01M294YS470NKPRW92DN4R86MW
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 11 h agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
Architecture
- Architecture
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
- Model type
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
- Parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
- Weights dtype
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
- File size
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
- Library name
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
- Pipeline tag
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
- Hugging Face repo
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium
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 →- ancestor: Qwen3.8 Flash
Papers1
- arXiv:2309.05516Active35
Timeline1
Full timeline →New model: Intel/Qwen3.8-Flash-Next-W4A16-AutoRound (Intel)
huggingface
Change history21
Viewing AI Atlas as of 12 Sept 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →Attributes as of 12 Sept 2026 22 claims in force
- Release date
- 28 Aug 2026
- Openness
- open-weights
- License
- Other
- Architecture
- Qwen4ExpForConditionalGeneration
- Parameters
- 75.4B
- Base model
- Qwen/Qwen3.8-Flash-Next
- File size
- 181.2 GB
- Hugging Face repo
- Intel/Qwen3.8-Flash-Next-W4A16-AutoRound
- Pipeline tag
- image-text-to-text
- Downloads
- 30,761
- Likes
- 19
- Gated
- No
- Last modified
- 2026-08-31T13:34:32+00:00
- Library name
- transformers
- License name
- qwen-community-1.0
- License url
- LICENSE
- Downloads all time
- 30,761
- Model type
- qwen4_exp
- Tags
- transformers, safetensors, qwen4_exp, image-text-to-text, 4-bit, auto-round
- Weights available
- Yes
- Weights dtype
- BF16, F16, I32, I64
Release daterelease_date1
Opennessopenness1
Licenselicense1
Architecturearchitecture1
Parametersparameter_count1
Base modelbase_model1
File sizefile_size_gb1
Hugging Face repohf_repo1
Pipeline tagpipeline_tag1
Model cardmodel_card_url1
Downloadsmetric.downloads1
Likesmetric.likes1
Gatedgated1
Last modifiedlast_modified1
Library namelibrary_name1
License namelicense_name1
License urllicense_url1
Downloads all timemetric.downloads_all_time1
Model typemodel_type1
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
21
Source tiers
T221
Freshest observation
9 h ago
Conflicts
None
Source documents 3
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (53/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →