Allen AIChat
Olmo 3.1 32B Think (Free)
olmo-3.1-32b-think:freeOlmo 3.1 32B Think is a 32B-parameter reasoning model built for complex, multi-step logic and advanced instruction following. It improves on earlier Olmo versions with stronger performance on difficult tasks and more refined reasoning. Released by AI2 under Apache 2.0, it remains fully open, with transparent weights, code, and training process.
- Context
- 65.5K tokens
- Endpoint
Pricing
Input$0 / 1M
Output$0 / 1M
Cache Write$0 / 1M
Cache Read$0 / 1M
Prompt cache writes and reads are included at no additional cost.
Quick Start
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Endpoint:
python
from openai import OpenAI client = OpenAI( api_key="YOUR_API_KEY", base_url="https://api.apertis.ai/v1") response = client.chat.completions.create( model="olmo-3.1-32b-think:free", messages=[ {"role": "user", "content": "Hello!"} ], max_tokens=1024, temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(# model="olmo-3.1-32b-think:free",# messages=[{"role": "user", "content": "Hello!"}],# extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )Supported Parameters
API docsCommon7 params
modelmessagesmax_tokenstemperaturetop_pstreamtoolsExtended4 params
reasoning_effortstream_optionsthinkingextra_bodyCursor IDE Model IDs
Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.
Compare with Other Models
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Olmo 3.1 32B Instruct
Olmo 3.1 32B Instruct is a 32B-parameter instruction-tuned model optimized for conversational AI and multi-turn dialogue. It focuses on strong instruction following and responsive chat behavior while maintaining solid reasoning and coding performance. Released by AI2 under Apache 2.0, it is fully open and transparent.
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Olmo 3 32B Think
Olmo 3.1 32B Think is a 32B-parameter reasoning model built for complex, multi-step logic and advanced instruction following. It improves on earlier Olmo versions with more refined reasoning and stronger performance on challenging evaluations, and — as part of AI2’s open initiative — it's fully transparent and released under Apache 2.0 with open weights, code, and training details.
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