Updated 1 h ago · first seen 12 Sept 2026
model_01M29XX06S62ZY3F3F2AV8X2P8
Overview
Identity
- Canonical model
- Yesidentity confidence: highOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- None recordedofficial_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- None recorded
- API aliases
- NoneIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable; 7 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
—
Redistribution
—
Derivatives
—
dimensions marked null are unknown, not false
Key facts
- Status
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
- Version
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
- Official page
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
- Paper
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
- Repository
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
Architecture
- Architecture
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
- Parameters
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
- Active parameters
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
- Mixture of experts
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
Capabilities
Modalities
- Modalities
- text
- Input
- text
- Output
- text
Capabilities
Tool calling
Yes
DeepSeek — site & API docs · T2
Structured output
Unavailable
Reasoning
Yes
DeepSeek — site & API docs · T2
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:DeepSeek — site & API docsT2observed 11 h agomediumLLM-extracted
Hardware fit37
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.
Versions & Artifacts0
Version history
Context windowfirst observation only
11 Sept 2026current
Opennessfirst observation only
11 Sept 2026current
Parametersfirst observation only
11 Sept 2026current
Statusfirst 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 0
No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.
Change history
Architecturearchitecture1
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
19
Source tiers
T219
Freshest observation
1 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 (59/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →