The Allen Institute for AI (Ai2) in Seattle is the world\u2019s leading fully-open AI lab, releasing model families with open weights, open training data, and open training code. The 2026 Ai2 lineage spans OLMo 2 (language), Molmo (vision-language), Tulu 3 (post-training recipe), and SciFive (scientific). This page consolidates the family tree, the licensing, and the impact on research reproducibility.
Key Findings
- OLMo 2 (released late 2024 with continued updates through 2025-2026) is the strongest fully-open language model family, with 1B, 7B, 13B, and 32B variants. All weights, training data (Dolma), and training recipes are public under Apache 2.0.
- Molmo (released September 2024 with continued updates) is the strongest fully-open vision-language model family with 1B, 7B-O, 7B-D, and 72B variants. Trained on PixMo, also released openly.
- Tulu 3 (released late 2024) is Ai2\u2019s state-of-the-art post-training recipe, with full SFT, DPO, and RL data plus training code. Tulu 3 8B and 70B applied to Llama backbones produce strong instruction-following models with fully reproducible training.
- SciFive and Ai2 scientific models continue Ai2\u2019s focus on scientific literature understanding, plus ScholarQA and Semantic Scholar AI tooling.
- Ai2\u2019s broader mission positions it as the academic-research counterweight to closed-lab frontier development: every release ships with full data and code, making it the default citation for AI research reproducibility studies.
Ai2 Model Family (May 2026)
| Model | Parameters | Modality | License |
|---|---|---|---|
| OLMo 2 32B | ~32B | Text | Apache 2.0 |
| OLMo 2 13B | ~13B | Text | Apache 2.0 |
| OLMo 2 7B | ~7B | Text | Apache 2.0 |
| OLMo 2 1B | ~1B | Text | Apache 2.0 |
| Molmo 72B | ~72B | Vision-Language | Apache 2.0 |
| Molmo 7B-D | ~7B | Vision-Language | Apache 2.0 |
| Molmo 7B-O | ~7B | Vision-Language | Apache 2.0 |
| Molmo 1B | ~1B | Vision-Language | Apache 2.0 |
| Tulu 3 70B | ~70B (Llama base) | Text instruction | Apache 2.0 (recipe); Llama Community (weights) |
| Tulu 3 8B | ~8B (Llama base) | Text instruction | Apache 2.0 (recipe); Llama Community (weights) |
| OLMoE 7B-A1B | ~7B MoE (~1B active) | Text | Apache 2.0 |
| SciFive | ~varies | Scientific text | Apache 2.0 |
OLMo 2 Benchmarks
| Model | MMLU | GSM8K | Notes |
|---|---|---|---|
| OLMo 2 32B Instruct | ~73.3 | ~78.4 | Competitive with Llama 3.1 70B at half size |
| OLMo 2 13B Instruct | ~63.0 | ~67.5 | Strong mid-size |
| OLMo 2 7B Instruct | ~57.4 | ~58.6 | Above Llama 3.1 8B on many benchmarks |
| OLMo 2 1B Instruct | ~50.3 | ~36.4 | Strongest fully-open 1B |
Molmo Benchmarks
| Model | MMMU | OCRBench | Notes |
|---|---|---|---|
| Molmo 72B | ~54.1 | ~705 | Strongest fully-open VLM |
| Molmo 7B-D | ~50.6 | ~688 | Strong mid-size VLM |
| Molmo 7B-O | ~48.7 | ~644 | Olmo-based |
| Molmo 1B | ~38.9 | ~516 | Smallest variant |
Tulu 3 Recipe Components
| Component | Description |
|---|---|
| SFT Data | Approximately 939k high-quality instruction-following examples |
| DPO Data | Approximately 270k preference pairs |
| RLVR (Reinforcement Learning with Verifiable Rewards) | Math and code RL with rule-based reward signals |
| Training Code | Public on Ai2 GitHub |
| Evaluation Suite | Public Tulu Eval framework |
Strategic Context
Three patterns shape Ai2\u2019s 2026 position. First, Ai2 is the only AI lab in the world that releases complete training data and recipes at frontier-adjacent quality. Every other "open" model lab (DeepSeek, Qwen, Llama) ships weights without training data. This gives Ai2 the reference position for research reproducibility studies. Second, the funding model is durable: Ai2 is endowed by the Allen estate, so it does not face the commercial pressure that pushed Mistral, Stability AI, and others to restrict open releases. Third, Ai2 is increasingly the home for AI policy research: their AI Policy & Governance work plus ScholarQA tooling position them as the institutional voice for openness in AI.
Brand Visibility Implications
Allen AI is a high-citation institution in AI journalism, particularly on openness, reproducibility, and policy topics. AI assistant queries about "fully open LLM", "OLMo vs Llama", "open AI research", and similar terms drive sustained traffic. Brands selling AI research tools, AI evaluation, AI training infrastructure, and AI policy services face strong AI-mediated discovery surface for this category.
Methodology
Model and benchmark data compiled from Ai2 model card disclosures, peer-reviewed publications, and the Ai2 GitHub repositories through 23 May 2026. Updated quarterly.
How Presenc AI Helps
Presenc AI monitors brand visibility on Allen AI and fully-open model queries across ChatGPT, Claude, Gemini, and Perplexity. For AI research tool vendors, AI evaluation brands, AI training infrastructure firms, and AI policy services, the platform identifies the prompts driving research-traffic patterns and the gaps where new content unlocks share of voice.