Updated 1 h ago · first seen 11 Sept 2026
model_01M29DV4DKDBPPS82CHKF70QR4
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 under CC-BY-NC-4.0; commercial use restricted; 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
No
Redistribution
Yes
Derivatives
Yes
Licence: Creative Commons Attribution-NonCommercial 4.0 (creative-commons · SPDX CC-BY-NC-4.0 · stated as “CC BY-NC 4.0”)
dimensions marked null are unknown, not false
Key facts
- Release date
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
- Status
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
- Version
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
Architecture
- Architecture
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
- Parameters
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
- Active parameters
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
- Mixture of experts
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
Capabilities
Modalities
- Modalities
- text
- Input
- text
- Output
- text
Capabilities
Tool calling
Unavailable
Structured output
Unavailable
Reasoning
Unavailable
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
No capability flags have been observed from a source yet — we do not infer them.
- Context window
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
- Max output
Source:Cohere — docs & blogT2observed 10 h agomediumLLM-extracted
- Languages
Source:Cohere — docs & blogT2observed 10 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
Openness4 changes
11 Sept 2026→12 Sept 2026→12 Sept 2026→12 Sept 2026→12 Sept 2026current
Context windowfirst observation only
11 Sept 2026current
Licensefirst observation only
11 Sept 2026current
Max outputfirst 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.
Timeline2
Full timeline →North Small Translate: openness changed from restricted-weights to open-weights
Opennessrestricted-weights→open-weightscohere
Change history
Weights availableweights_available1
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
22
Source tiers
T222
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 (62/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →