Using Kimi K2 Instruct 0905 on Fireworks AI
Implementation guide · Kimi K2 · Moonshot AI
ServerlessOpen Source
Fireworks AI exposes Kimi K2 Instruct 0905 through model ID accounts/fireworks/models/kimi-k2-instruct-0905. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-04. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/kimi-k2-instruct-0905— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
FIREWORKS_API_KEYModel ID
accounts/fireworks/models/kimi-k2-instruct-0905Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/kimi-k2-instruct-0905",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.60 |
| Output tokens | $2.50 |
Capabilities
No model capability flags are currently sourced.
About Kimi K2 Instruct 0905
Kimi K2 Instruct 0905 is Moonshot AI's Kimi K2 model. It offers a 131K-token context window.
Model Specs
Released2025-09-05
Parameters1T total, 32B active (MoE)
Context131k
ArchitectureDecoder Only