moonshotai/Kimi-K2-Instruct

text-generation model by moonshotai

Open original source ↗

From the publisher

Model card & documentation

Source preview

Read the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.

📰  Tech Blog     |     📄  Paper Kimi K2 is a state-of-the-art mixture-of-experts (MoE) language model with 32 billion activated parameters and 1 trillion total parameters. Trained with the Muon optimizer, Kimi K2 achieves exceptional performance across frontier knowledge, reasoning, and coding tasks while being meticulously optimized for agentic capabilities. Benchmark Metric Kimi K2 Instruct DeepSeek-V3-0324 Qwen3-235B-A22B (non-thinking) Claude Sonnet 4 (w/o extended thinking) Claude Opus 4 (w/o extended thinking) GPT-4.1 Gemini 2.5 Flash Preview (05-20) Coding Tasks LiveCodeBench v6(Aug 24 - May 25) Pass@1 53.7 46.9 37.0 48.5 47.4 44.7 44.7 OJBench Pass@1 27.1 24.0 11.3 15.3 19.6 19.5 19.5 MultiPL-E Pass@1 85.7 83.1 78.2 88.6 89.6 86.7 85.6 SWE-bench Verified (Agentless Coding) Single Patch w/o Test (Acc) 51.8 36.6 39.4 50.2 53.0 40.8 32.6 SWE-bench Verified (Agentic Coding) Single Attempt (Acc) 65.8 38.8 34.4 72.7 72.5 54.6 — Multiple Attempts (Acc) 71.6 — — 80.2 79.4 — — SWE-bench…

moonshotai/Kimi-K2-Instruct on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-10-31T21:17:26.790Z

Inside the original model card — Document outline
  1. 0. Changelog
  2. 2025.8.11
  3. 2025.7.18
  4. 2025.7.15
  5. 1. Model Introduction
  6. Key Features
  7. Model Variants
  8. 2. Model Summary
  9. 3. Evaluation Results
  10. Instruction model evaluation results
  11. Base model evaluation results
  12. 4. Deployment

Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.

Links from the model card

References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.

Documentation belongs to its respective authors. Reported project/model license: other. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

moonshotai/Kimi-K2-Instruct is a text-generation model repository published by moonshotai on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
text-generation
Library
transformers
Recent downloads (30 days)
320,159
Cumulative likes
3,008
Hugging Face trending score
1
Reported safetensors parameters
1,026,408,235,864
Architecture
DeepseekV3ForCausalLM
License
other
Access
Not gated by Hugging Face
Created
2025-07-11T00:55:12.000Z
Last modified
2026-04-23T02:08:36.000Z

Compatibility and lineage

Language coverage was not reported.

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

Use and evaluate

Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.

No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.

Model card and usage instructions

Model files and configuration

Community discussion

Source and freshness

Source: Hugging Face Hub. Metadata observed 2026-11-01T06:50:33.901Z. Daily imports are snapshots, not real-time monitoring.

Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.

Open original source

Related models

openai-community/gpt2

Qwen/Qwen3-0.6B

Qwen/Qwen3-14B

Qwen/Qwen3-4B

Qwen/Qwen3-8B

deepseek-ai/DeepSeek-V3.2