Last refreshed 2026-06-04. Next refresh: weekly.
Why use Kimi K2.5 on Fireworks AI?
Fireworks AI offers Kimi K2.5 with pay-as-you-go pricing at $0.60/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Compare Kimi K2.5 across 10 providers to find the best fit for your use caseInput / 1M
$0.60
Output / 1M
$3.00
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install openaiAuth
export FIREWORKS_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],Model ID
accounts/fireworks/models/kimi-k2p5Request example
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-k2p5",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/kimi-k2p5", not the LLMReference slug "kimi-k2-5".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Compare Kimi K2.5 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Cloudflare Workers AI | — | — |
| Fireworks AI | $0.60 | $3.00 |
| OpenRouter | $0.44 | $2.00 |
| Together AI | $0.50 | $2.80 |
| NVIDIA NIM | — | — |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.60 |
| Output tokens | $3.00 |
Capabilities
VisionMultimodalJSON / Tool useStructured Outputs
About Kimi K2.5
Kimi K2.5 is Moonshot AI's Kimi model focused on code generation and software engineering. It offers a 256K-token context window and scores 87.9 on GPQA.
Get Started
Model Specs
Released2026-03-15
Parameters1T (MoE, 384 experts)
Context256k
ArchitectureMixture of Experts