cerebras/MiniMax-M2.5-REAP-172B-A10B
Cerebras Systemshuggingface.co/cerebras/MiniMax-M2.5-REAP-172B-A
Updated 10 h ago · first seen 11 Sept 2026
model_01M294XYRJ99K40PP48B619HC7
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 12 h agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
Architecture
- Architecture
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Model type
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Active parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Weights dtype
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- File size
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Library name
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Pipeline tag
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Hugging Face repo
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
Capabilities
Modalities
Modalities unavailable.
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.
- Languages
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 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: MiniMax M2.5
Papers1
- arXiv:2510.13999Active35
Timeline1
Full timeline →New model: cerebras/MiniMax-M2.5-REAP-172B-A10B (Cerebras Systems)
huggingface
Change history23
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 24 claims in force
- Release date
- 18 Feb 2026
- Openness
- open-weights
- License
- Other
- Architecture
- MiniMaxM2ForCausalLM
- Parameters
- 172.5B
- Active parameters
- 10B
- Languages
- en
- Base model
- MiniMaxAI/MiniMax-M2.5
- Quantization format
- fp8
- File size
- 173.8 GB
- Hugging Face repo
- cerebras/MiniMax-M2.5-REAP-172B-A10B
- Pipeline tag
- text-generation
- Downloads
- 120
- Likes
- 27
- Gated
- No
- Is quantized
- Yes
- Last modified
- 2026-02-18T21:17:17+00:00
- Library name
- transformers
- Downloads all time
- 2,105
- Model type
- minimax_m2
- Tags
- transformers, safetensors, minimax_m2, text-generation, minimax, MOE, pruning, compression, custom_code, en, fp8
- Weights available
- Yes
- Weights dtype
- BF16, F8_E4M3
Release daterelease_date1
Opennessopenness1
Licenselicense1
Architecturearchitecture1
Parametersparameter_count1
Active parametersactive_parameter_count1
Languageslanguages1
Base modelbase_model1
Quantization formatquant_format1
File sizefile_size_gb1
Hugging Face repohf_repo1
Pipeline tagpipeline_tag1
Model cardmodel_card_url1
Downloadsmetric.downloads1
Likesmetric.likes1
Gatedgated1
Is quantizedis_quantized1
Last modifiedlast_modified1
Library namelibrary_name1
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
23
Source tiers
T223
Freshest observation
10 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 →