Olmo 3 32B Think

Allen AI chatreasoning

API ID: allenai/olmo-3-32b-think-20251121

Input Price
$0.15
/1M tokens
Output Price
$0.50
/1M tokens

About Olmo 3 32B Think

Olmo 3 32B Think is a large-scale, 32-billion-parameter model purpose-built for deep reasoning, complex logic chains and advanced instruction-following scenarios. Its capacity enables strong performance on demanding evaluation tasks and highly nuanced conversational reasoning. Developed by Ai2 under the Apache 2.0 license, Olmo 3 32B Think embodies the Olmo initiative’s commitment to openness, offering full transparency across weights, code and training methodology.

💰
Price Ranking
#755 lowest price among 1240 Chat models

Model Specifications

Context Length
66k
Max Output
66k
Release Date
2025-11-21
Capabilities
chat reasoning
Input Modalities
text
Output Modalities
text

Best For

  • Complex reasoning, math problems, multi-step logic
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)
  • Simple Q&A (cheaper models available)

💰 Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.22
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$6.75
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$9.38
/month
500 analyses/day, ~2k tokens each

Allen AI Model Lineup

Compare all models from Allen AI to find the best fit

Model Input Output Context Capabilities
Olmo 3 32B Think Current $0.15 $0.50 66k chat reasoning
Llama 3.1 Tulu 3 405B Free Free - chat
Llama 3.1 Tulu 3 405B Free Free - chat
OLMo 7B Instruct Free Free 2k chat
OLMo 7B Instruct Free Free 2k chat
Olmo 2 32B Instruct $0.05 $0.20 128k chat tool_use

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🚀 Quick Start

Get started with Olmo 3 32B Think API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="allenai/olmo-3-32b-think-20251121",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)