Last refreshed 2026-05-07. Next refresh: weekly.
Why use Cogito v1 Preview Qwen-32B on Fireworks AI?
Fireworks AI offers Cogito v1 Preview Qwen-32B with pay-as-you-go pricing at $0.90/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Setup recipe
Python + curlpip install openaiexport FIREWORKS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],cogito-v1-preview-qwen-32bRequest 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="cogito-v1-preview-qwen-32b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- 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.
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.90 |
| Output tokens | $0.90 |
Capabilities
About Cogito v1 Preview Qwen-32B
Cogito v1 Preview Qwen-32B is a hybrid reasoning model fine-tuned from Qwen 2.5 32B using Iterated Distillation and Amplification (IDA). Supports direct and extended-thinking modes, tool calling, and 30+ languages.
FAQ
What does Cogito v1 Preview Qwen-32B cost on Fireworks AI?
On Fireworks AI, Cogito v1 Preview Qwen-32B costs $0.9 per 1M input tokens and $0.9 per 1M output tokens.
What is the context window for Cogito v1 Preview Qwen-32B on Fireworks AI?
Cogito v1 Preview Qwen-32B supports a 128,000 token context window on Fireworks AI.
Who created Cogito v1 Preview Qwen-32B?
Cogito v1 Preview Qwen-32B was created by Deep Cogito as part of the Cogito model family.
Is Cogito v1 Preview Qwen-32B open source?
Cogito v1 Preview Qwen-32B is open source according to the seed data.