Updated 2 h ago · first seen 12 Sept 2026
model_01M29XNQ2TQ7KDSRE9803GYZ1J
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:Qwen — official blogT2observed 10 h agomediumLLM-extracted
- Status
Source:Qwen — official blogT2observed 10 h agomediumLLM-extracted
- Version
Source:Qwen — official blogT2observed 10 h agomediumLLM-extracted
- Paper
Source:Qwen — official blogT2observed 10 h agomediumLLM-extracted
Architecture
- Parameters
Source:Qwen — official blogT2observed 10 h agomediumLLM-extracted
Capabilities
Modalities
- Modalities
- imagetext
- Input
- imagetext
- Output
- text
Capabilities
Tool calling
Unavailable
Structured output
Unavailable
Reasoning
Yes
Qwen — official blog · T2
Vision
Yes
Qwen — official blog · T2
Audio
Unavailable
Fine-tuning available
Unavailable
No structured attributes yet.
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).
Timeline1
Full timeline →Change history
Parametersparameter_count1
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
13
Source tiers
T213
Freshest observation
10 h ago
Conflicts
None
Source documents 1
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 →