Models / Deep CogitoCogito / / Cogito v2 preview - 109B MoE API
Cogito v2 preview - 109B MoE API

Cogito 109B MoE leverages mixture-of-experts architecture to deliver advanced reasoning capabilities with computational efficiency. This hybrid model excels at both direct responses and complex reasoning tasks while maintaining multimodal capabilities through innovative transfer learning.
Cogito v2 preview - 109B MoE API Usage
Endpoint
curl -X POST "https://api.together.xyz/v1/chat/completions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE",
"messages": [
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
}'
curl -X POST "https://api.together.xyz/v1/images/generations" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE",
"prompt": "Draw an anime style version of this image.",
"width": 1024,
"height": 768,
"steps": 28,
"n": 1,
"response_format": "url",
"image_url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"
}'
curl -X POST https://api.together.xyz/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE",
"messages": [{
"role": "user",
"content": [
{"type": "text", "text": "Describe what you see in this image."},
{"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
]
}],
"max_tokens": 512
}'
curl -X POST https://api.together.xyz/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE",
"messages": [{
"role": "user",
"content": "Given two binary strings `a` and `b`, return their sum as a binary string"
}]
}'
curl -X POST https://api.together.xyz/v1/rerank \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE",
"query": "What animals can I find near Peru?",
"documents": [
"The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
"The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
"The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
"The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
],
"top_n": 2
}'
curl -X POST https://api.together.xyz/v1/embeddings \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph.",
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE"
}'
curl -X POST https://api.together.xyz/v1/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
"prompt": "A horse is a horse",
"max_tokens": 32,
"temperature": 0.1,
"safety_model": "deepcogito/cogito-v2-preview-llama-109B-MoE"
}'
curl --location 'https://api.together.ai/v1/audio/generations' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer $TOGETHER_API_KEY' \
--output speech.mp3 \
--data '{
"input": "Today is a wonderful day to build something people love!",
"voice": "helpful woman",
"response_format": "mp3",
"sample_rate": 44100,
"stream": false,
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE"
}'
curl -X POST "https://api.together.xyz/v1/audio/transcriptions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-F "model=deepcogito/cogito-v2-preview-llama-109B-MoE" \
-F "language=en" \
-F "response_format=json" \
-F "timestamp_granularities=segment"
from together import Together
client = Together()
response = client.chat.completions.create(
model="deepcogito/cogito-v2-preview-llama-109B-MoE",
messages=[
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
)
print(response.choices[0].message.content)
from together import Together
client = Together()
imageCompletion = client.images.generate(
model="deepcogito/cogito-v2-preview-llama-109B-MoE",
width=1024,
height=768,
steps=28,
prompt="Draw an anime style version of this image.",
image_url="https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
)
print(imageCompletion.data[0].url)
from together import Together
client = Together()
response = client.chat.completions.create(
model="deepcogito/cogito-v2-preview-llama-109B-MoE",
messages=[{
"role": "user",
"content": [
{"type": "text", "text": "Describe what you see in this image."},
{"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
]
}]
)
print(response.choices[0].message.content)
from together import Together
client = Together()
response = client.chat.completions.create(
model="deepcogito/cogito-v2-preview-llama-109B-MoE",
messages=[
{
"role": "user",
"content": "Given two binary strings `a` and `b`, return their sum as a binary string"
}
],
)
print(response.choices[0].message.content)
from together import Together
client = Together()
query = "What animals can I find near Peru?"
documents = [
"The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
"The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
"The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
"The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations.",
]
response = client.rerank.create(
model="deepcogito/cogito-v2-preview-llama-109B-MoE",
query=query,
documents=documents,
top_n=2
)
for result in response.results:
print(f"Relevance Score: {result.relevance_score}")
from together import Together
client = Together()
response = client.embeddings.create(
model = "deepcogito/cogito-v2-preview-llama-109B-MoE",
input = "Our solar system orbits the Milky Way galaxy at about 515,000 mph"
)
from together import Together
client = Together()
response = client.completions.create(
model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
prompt="A horse is a horse",
max_tokens=32,
temperature=0.1,
safety_model="deepcogito/cogito-v2-preview-llama-109B-MoE",
)
print(response.choices[0].text)
from together import Together
client = Together()
speech_file_path = "speech.mp3"
response = client.audio.speech.create(
model="deepcogito/cogito-v2-preview-llama-109B-MoE",
input="Today is a wonderful day to build something people love!",
voice="helpful woman",
)
response.stream_to_file(speech_file_path)
from together import Together
client = Together()
response = client.audio.transcribe(
model="deepcogito/cogito-v2-preview-llama-109B-MoE",
language="en",
response_format="json",
timestamp_granularities="segment"
)
print(response.text)
import Together from 'together-ai';
const together = new Together();
const completion = await together.chat.completions.create({
model: 'deepcogito/cogito-v2-preview-llama-109B-MoE',
messages: [
{
role: 'user',
content: 'What are some fun things to do in New York?'
}
],
});
console.log(completion.choices[0].message.content);
import Together from "together-ai";
const together = new Together();
async function main() {
const response = await together.images.create({
model: "deepcogito/cogito-v2-preview-llama-109B-MoE",
width: 1024,
height: 1024,
steps: 28,
prompt: "Draw an anime style version of this image.",
image_url: "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
});
console.log(response.data[0].url);
}
main();
import Together from "together-ai";
const together = new Together();
const imageUrl = "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png";
async function main() {
const response = await together.chat.completions.create({
model: "deepcogito/cogito-v2-preview-llama-109B-MoE",
messages: [{
role: "user",
content: [
{ type: "text", text: "Describe what you see in this image." },
{ type: "image_url", image_url: { url: imageUrl } }
]
}]
});
console.log(response.choices[0]?.message?.content);
}
main();
import Together from "together-ai";
const together = new Together();
async function main() {
const response = await together.chat.completions.create({
model: "deepcogito/cogito-v2-preview-llama-109B-MoE",
messages: [{
role: "user",
content: "Given two binary strings `a` and `b`, return their sum as a binary string"
}]
});
console.log(response.choices[0]?.message?.content);
}
main();
import Together from "together-ai";
const together = new Together();
const query = "What animals can I find near Peru?";
const documents = [
"The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
"The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
"The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
"The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
];
async function main() {
const response = await together.rerank.create({
model: "deepcogito/cogito-v2-preview-llama-109B-MoE",
query: query,
documents: documents,
top_n: 2
});
for (const result of response.results) {
console.log(`Relevance Score: ${result.relevance_score}`);
}
}
main();
import Together from "together-ai";
const together = new Together();
const response = await client.embeddings.create({
model: 'deepcogito/cogito-v2-preview-llama-109B-MoE',
input: 'Our solar system orbits the Milky Way galaxy at about 515,000 mph',
});
import Together from "together-ai";
const together = new Together();
async function main() {
const response = await together.completions.create({
model: "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
prompt: "A horse is a horse",
max_tokens: 32,
temperature: 0.1,
safety_model: "deepcogito/cogito-v2-preview-llama-109B-MoE"
});
console.log(response.choices[0]?.text);
}
main();
import Together from 'together-ai';
const together = new Together();
async function generateAudio() {
const res = await together.audio.create({
input: 'Today is a wonderful day to build something people love!',
voice: 'helpful woman',
response_format: 'mp3',
sample_rate: 44100,
stream: false,
model: 'deepcogito/cogito-v2-preview-llama-109B-MoE',
});
if (res.body) {
console.log(res.body);
const nodeStream = Readable.from(res.body as ReadableStream);
const fileStream = createWriteStream('./speech.mp3');
nodeStream.pipe(fileStream);
}
}
generateAudio();
import Together from "together-ai";
const together = new Together();
const response = await together.audio.transcriptions.create(
model: "deepcogito/cogito-v2-preview-llama-109B-MoE",
language: "en",
response_format: "json",
timestamp_granularities: "segment"
});
console.log(response)
This is a hybrid reasoning model. To enable thinking mode, pass the following parameter with your request to the model:
"chat_template_kwargs": {"enable_thinking": true}
Here's an example cURL request with thinking enabled:
curl -X POST "https://api.together.xyz/v1/chat/completions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE",
"temperature": 0.6,
"chat_template_kwargs": {"enable_thinking": true},
"messages": [
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
}'
Here's an example Python request with thinking enabled:
from together import Together
client = Together()
chat_template_kwargs = {"enable_thinking": True}
response = client.chat.completions.create(
model="deepcogito/cogito-v2-preview-llama-109B-MoE"",
extra_body={"chat_template_kwargs": chat_template_kwargs},
messages=[
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
)
print(response.choices[0].message.content)
How to use Cogito v2 preview - 109B MoE
Model details
This is a hybrid reasoning model. To enable thinking mode, pass the following parameter with your request to the model:
"chat_template_kwargs": {"enable_thinking": true}
Here's an example cURL request with thinking enabled:
curl -X POST "https://api.together.xyz/v1/chat/completions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepcogito/cogito-v2-preview-llama-109B-MoE",
"temperature": 0.6,
"chat_template_kwargs": {"enable_thinking": true},
"messages": [
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
}'
Here's an example Python request with thinking enabled:
from together import Together
client = Together()
chat_template_kwargs = {"enable_thinking": True}
response = client.chat.completions.create(
model="deepcogito/cogito-v2-preview-llama-109B-MoE"",
extra_body={"chat_template_kwargs": chat_template_kwargs},
messages=[
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
)
print(response.choices[0].message.content)
Architecture Overview:
• 109B MoE mixture-of-experts architecture with intelligent routing
• Strong reasoning capabilities in the Cogito model family
• Advanced policy improvement for both reasoning and non-reasoning modes
Training Methodology:
• Dual-mode training improving both standard and reasoning performance
• Signal-based training for thinking process optimization
• Advanced distillation techniques preventing reasoning meandering
Performance Characteristics:
• Excellent reasoning performance in 109B MoE parameter class
• Efficient inference with optimized reasoning chains
• Strong performance across diverse reasoning benchmarks
Prompting Cogito v2 preview - 109B MoE
Applications & Use Cases
Complex Reasoning Tasks:
• Multi-step mathematical proofs and scientific analysis
• Logical reasoning requiring expert knowledge activation
• Research synthesis across multiple domains
Multimodal Analysis:
• Image comparison and visual reasoning tasks
• Document analysis with text and visual components
• Educational content requiring cross-modal understanding
Efficiency-Critical Applications:
• Real-time reasoning with computational constraints
• Batch processing of diverse reasoning tasks
• Scalable AI applications requiring expert-level performance
Model Provider:
Deep Cogito
Type:
Chat
Variant:
Parameters:
109B MoE
Deployment:
✔ Serverless
✔ On-Demand Dedicated
✔ Monthly Reserved
Quantization
Context length:
Pricing:
Check pricing
Run in playground
Deploy model
Quickstart docs
Quickstart docs
Serverless
On-Demand Dedicated
Monthly Reserved
Looking for production scale? Deploy on a dedicated endpoint
Deploy Cogito v2 preview - 109B MoE on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.
