Architecture
data/models.yaml. Every label is auditable
against the model's sources.
Specs
- Architecture
- moe
- Total params
- 1T
- Active params
- 32B
- Experts
- 384 total · 8 active
- Context window
- 256K tokens
- Attention
- mla
- Position encoding
- rope
- Pretraining tokens
- 15.0T
- Post-training
- sft, rlhf
- OSI-approved
- no
- Data released
- no
- Training code
- not released
Benchmarks
Each score carries the date it was published; we never infer or interpolate missing scores.
General reasoning
| GPQA-Diamond | 87.6 | as of 2026-01-27 | source ↗ |
Math
| AIME 2025 | 96.1 | as of 2026-01-27 | source ↗ |
Available quantizations
GGUF llama.cpp's container; the common local format, k-quants from Q2 to Q8.
runs on llama.cpp, Ollama
FP8 8-bit float, frequently a native release on Hopper / Blackwell GPUs.
runs on vLLM, SGLang, TensorRT-LLM
Verified via the Hugging Face model tree ↗. Community quantizations change over time; the families shown are those with published weights at audit time.
Notable innovations
- · Native multimodal Kimi (image, video, text)
- · 400M-parameter MoonViT vision encoder
- · Continual pretraining on ~15T mixed-modality tokens
Lineage
First multimodal Kimi in the K2 family; continual pretraining on ~15T mixed-modality tokens; adds MoonViT vision and video understanding.
Derivatives