AllenAI: Olmo 3.1 32B Instruct✓ Catalog verified
Olmo 3.1 32B Instruct is a large-scale, 32-billion-parameter instruction-tuned language model engineered for high-performance conversational AI, multi-turn dialogue, and practical instruction following. As part of the Olmo 3.1 family, this variant emphasizes responsiveness to complex user directions and robust chat interactions while retaining strong capabilities on reasoning and coding benchmarks. Developed by Ai2 under the Apache 2.0 license, Olmo 3.1 32B Instruct reflects the Olmo initiative’s commitment to openness and transparency.
Overview
Olmo 3.1 32B Instruct is a large-scale, 32-billion-parameter instruction-tuned language model engineered for high-performance conversational AI, multi-turn dialogue, and practical instruction following. As part of the Olmo 3.1 family, this variant emphasizes responsiveness to complex user directions and robust chat interactions while retaining strong capabilities on reasoning and coding benchmarks. Developed by Ai2 under the Apache 2.0 license, Olmo 3.1 32B Instruct reflects the Olmo initiative’s commitment to openness and transparency.
Access: available through the official Allenai API. Context window: 66K.
Specifications
| API identifier | allenai/olmo-3.1-32b-instruct |
| Provider | Allenai |
| Model type | Text LLM |
| Context window | 66K catalog |
| Input modalities | text |
| Output modalities | text |
| Released | Jan 6, 2026 |
| Moderated | No |
| Architecture modality | text->text |
API defaults
{
"top_p": 0.95,
"temperature": 0.6,
"frequency_penalty": null
}Pricing
Live pricing components for allenai/olmo-3.1-32b-instruct as published in the catalog.
| Pricing component | Raw unit price | Normalized | Unit |
|---|---|---|---|
| Prompt tokens | $2e-7 | $0.20 / 1M | Per input token |
| Completion tokens | $6e-7 | $0.60 / 1M | Per output token |
| Request fee | N/A | N/A | Per request |
| Image fee | N/A | N/A | Per image unit |
| Web search fee | N/A | N/A | Per search request |
Cost calculator
Estimate monthly spend from your own token volumes.
Estimated Total Cost
$0.22Calculated from current list pricing in the ModelsAtlas catalog.Capabilities
| Capability | Status | What it means |
|---|---|---|
| Visual Understanding | Not advertised | Image and document analysis support |
| Audio Processing | Not advertised | Speech and voice aligned flows |
| Tool Calling | ✓ Supported | Supports tools / function calling |
| Self-Hosting | Not advertised | Deploy outside managed APIs |
Capability signals
Directional signals derived from model metadata and capability tags — not official benchmark submissions.
Quick start
Call AllenAI: Olmo 3.1 32B Instruct through an OpenAI-compatible client.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="allenai/olmo-3.1-32b-instruct",
messages=[{"role": "user", "content": "Explain quantum physics."}]
)
print(response.choices[0].message.content)Alternatives
Closest models by context window from a different provider.
| Model | Provider | Context | Input /1M | Actions |
|---|---|---|---|---|
| Google: Nano Banana 2 (Gemini 3.1 Flash Image Preview) | 66K | $0.50 | View → | |
| Google: Nano Banana Pro (Gemini 3 Pro Image Preview) | 66K | $2.00 | View → |
Sources & attribution
Pricing and metadata are maintained in the ModelsAtlas catalog.
Frequently asked questions
How much does AllenAI: Olmo 3.1 32B Instruct cost?
$0.20 per 1M input tokens and $0.60 per 1M output tokens on the official Allenai API.
What is the context window of AllenAI: Olmo 3.1 32B Instruct?
AllenAI: Olmo 3.1 32B Instruct supports up to 66K tokens of context.
Does AllenAI: Olmo 3.1 32B Instruct support tool / function calling?
Yes, AllenAI: Olmo 3.1 32B Instruct supports tool / function calling — you can register tools and the model will emit structured tool calls.
How do I access AllenAI: Olmo 3.1 32B Instruct?
Use the official Allenai API with the model id `allenai/olmo-3.1-32b-instruct`. See the Quick start section above for code examples.