Fireworks RFT now available! Fine-tune open models that outperform frontier models. Try today

Model Library
/Moonshot AI/Kimi K2 Instruct 0905
fireworks/kimi-k2-instruct-0905

    Kimi K2 0905 is an updated version of Kimi K2, a state-of-the-art mixture-of-experts (MoE) language model with 32 billion activated parameters and 1 trillion total parameters. Kimi K2 0905 has improved coding abilities, a longer context window, and agentic tool use, and a longer (262K) context window.

    Kimi K2 Instruct 0905 API Features

    Fine-tuning

    Docs

    Kimi K2 Instruct 0905 can be customized with your data to improve responses. Fireworks uses LoRA to efficiently train and deploy your personalized model

    Serverless

    Docs

    Immediately run model on pre-configured GPUs and pay-per-token

    On-demand Deployment

    Docs

    On-demand deployments give you dedicated GPUs for Kimi K2 Instruct 0905 using Fireworks' reliable, high-performance system with no rate limits.

    Available Serverless

    Run queries immediately, pay only for usage

    $0.60 / $2.50
    Per 1M Tokens (input/output)

    Kimi K2 Instruct 0905 FAQs

    What is Kimi K2 Instruct 0905 and who developed it?

    Kimi K2 Instruct 0905 is a state-of-the-art mixture-of-experts (MoE) language model developed by Moonshot AI. It features 32 billion activated parameters out of 1 trillion total parameters, offering enhanced performance for agentic tasks and long-context reasoning.

    What applications and use cases does Kimi K2 Instruct 0905 excel at?

    Kimi K2 Instruct 0905 is optimized for:

    • Code assistance and agentic coding tasks
    • Frontend programming
    • Conversational AI
    • Tool-augmented interaction
    • Long-context reasoning (256K tokens)
    • Enterprise-grade retrieval-augmented generation (RAG)
    What is the maximum context length for Kimi K2 Instruct 0905?

    The model supports a maximum context length of 262,144 tokens on Fireworks.

    What is the usable context window for Kimi K2 Instruct 0905?

    The model's usable context window is 256,000 tokens.

    Does Kimi K2 Instruct 0905 support quantized formats (4-bit/8-bit)?

    Yes. Multiple quantized versions are available.

    What is the default temperature of Kimi K2 Instruct 0905 on Fireworks AI?

    The default temperature of Kimi K2 Instruct 0905 is 0.6.

    How many parameters does Kimi K2 Instruct 0905 have?
    • Total parameters: 1 trillion
    • Activated parameters per forward pass: 32 billion
    Is fine-tuning supported for Kimi K2 Instruct 0905?

    Yes. Fireworks supports fine-tuning Kimi K2 Instruct 0905 using LoRA for parameter-efficient adaptation.

    What license governs commercial use of Kimi K2 Instruct 0905?

    Kimi K2 Instruct 0905 is released under a Modified MIT License.

    Metadata

    State
    Ready
    Created on
    9/4/2025
    Kind
    Base model
    Provider
    Moonshot AI
    Hugging Face
    Kimi-K2-Instruct-0905

    Specification

    Calibrated
    Yes
    Mixture-of-Experts
    Yes
    Parameters
    1T

    Supported Functionality

    Fine-tuning
    Supported
    Serverless
    Supported
    Serverless LoRA
    Not supported
    Context Length
    262.1k tokens
    Function Calling
    Supported
    Embeddings
    Not supported
    Rerankers
    Not supported
    Support image input
    Not supported