🧠
Kimi K2.7 Code model by moonshotai
⭐ 57.6
🧠
Model

Kimi K2.7 Code

by moonshotai moonshotai/kimi-k2.7-code
Free2AITools Nexus Index
57.6
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 57
P: Popularity 30
R: Recency 100
Q: Quality 65
Tech Context
1058.59 Params
4.096K Ctx
Vital Performance
1.7K DL / 30D
Source β†’
Low FNI signal 57.6 FNI Score
Massive 1058.59B Params
4k Context
1.7K Downloads
H100+ ~797GB Est. VRAM
Dense KIMIK25FORCONDITIONALGENERATION Architecture
Restricted OTHER License
Model Information Summary
Entity Passport
Registry ID moonshotai/kimi-k2.7-code
License Other
Provider huggingface
πŸ’Ύ

Compute Threshold

~796.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization. [Multi-GPU / Unified Memory Required]

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{moonshotai_kimi_k2_7_code,
  author = {moonshotai},
  title = {Kimi K2.7 Code Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/moonshotai/Kimi-K2.7-Code}},
  note = {Accessed via Free2AITools.}
}
APA Style
moonshotai. (2026). Kimi K2.7 Code [Model]. Free2AITools. https://huggingface.co/moonshotai/Kimi-K2.7-Code

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download moonshotai/kimi-k2.7-code
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 57
Popularity (P) 30
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Kimi K2.7 Code: Authority (A:57), Popularity (P:30), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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πŸš€ What's Next?

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Deployment reference

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Technical Deep Dive

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
1.7KDownloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--moonshotai--kimi-k2.7-code
slug
moonshotai--kimi-k2.7-code
source
huggingface
author
moonshotai
license
Other
tags
transformers, safetensors, kimi_k25, image-feature-extraction, compressed-tensors, image-text-to-text, conversational, custom_code, license:other, region:us

βš™οΈ Technical Specs

architecture
KimiK25ForConditionalGeneration
params billions
1,058.59
context length
4,096
pipeline tag
image-text-to-text
vram gb
796.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
1,689
stars
null
forks
null

Data indexed from public sources. Updated daily.