LLM Reference

OLMo 3.1 32B Instruct

Released
2026-02-01
Last refreshed
2026-04-27
Status
Researched 45d ago
Open SourceCommercial use allowedCodingAgentsClassificationJSON / Tool use

OLMo 3.1 32B Instruct has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Use it for

  • Teams evaluating coding, agents, and classification
  • Workloads that can use a 64k context window

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Vision or document-understanding workloads
  • Teams that need a tracked hosted API route today
Specifications
Family
OLMo
Released
2026-02-01
Context
64k
Parameters
32B
Architecture
Decoder Only
Knowledge cutoff
2024-12
Specialization
general
Openness
Open source
License
Apache 2.0(OSI)Commercial use allowed
Training
pretrained
Created by

Advocating for open science and source

Seattle, Washington, United States
Founded 2014
Website
Pricing

No tracked provider token pricing is available yet.

About

OLMo 3.1 32B Instruct is Allen Institute for AI's large-scale 32B instruction-tuned model engineered for high performance across language understanding, reasoning, and coding tasks.

OLMo 3.1 32B Instruct is an open-source model in the OLMo family. The structured metadata tracks a 64k-token context window, function calling, tool use, and structured outputs. Headline tracked benchmarks include AIME 2024 67.8, AIME 2025 57.9, and Google-Proof Q&A 48.6.

Top use-case fit: coding, agents, and build tasks

Coding

2 relevant benchmarks in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Classification

1 relevant benchmark in the decision map.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Capabilities

Function CallingTool UseStructured Outputs

Benchmark peer barsfor Coding

Benchmark scores(7)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
AIME 202467.8AIME 2024 (accuracy)https://huggingface.co/allenai/Olmo-3.1-32B-Instruct
AIME 202557.9AIME 2025 (accuracy)https://huggingface.co/allenai/Olmo-3.1-32B-Instruct
Google-Proof Q&A48.6GPQA (accuracy)https://huggingface.co/allenai/Olmo-3.1-32B-Instruct
HumanEval86.7HumanEval (pass@1)https://huggingface.co/allenai/Olmo-3.1-32B-Instruct
LiveCodeBench54.7LiveCodeBench v3 (accuracy)https://huggingface.co/allenai/Olmo-3.1-32B-Instruct
MATH-50093.4MATH benchmark (accuracy)https://huggingface.co/allenai/Olmo-3.1-32B-Instruct
Massive Multitask Language Understanding80.9From official HuggingFace model card (accuracy)https://huggingface.co/allenai/Olmo-3.1-32B-Instruct

Migration checks

No linked migration route is available for this model yet.