Cohere Command A vs NotebookLM
Which one should you pick? Here's the full breakdown.
Cohere Command A
Cohere's enterprise-multilingual flagship -- 111B params, 256K context, runs on 2x H100. 23 languages. CC-BY-NC 4.0 on weights (research / non-commercial), commercial requires Cohere enterprise contract. Follow-ups: Command A Reasoning + Command A Vision
NotebookLM
Google's free research assistant that turns your documents into an AI you can query -- and a podcast you can listen to
| Category | Cohere Command A | NotebookLM |
|---|---|---|
| Ease of Use | 6.5 | 8.0 |
| Output Quality | 8.5 | 7.0 |
| Value | 7.0 | 9.5 |
| Features | 8.0 | 6.5 |
| Overall | 7.5 | 7.8 |
Pricing Comparison
| Feature | Cohere Command A | NotebookLM |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Which Should You Pick?
Pick Cohere Command A if...
- ✓Higher output quality (8.5 vs 7)
- ✓More features (8 vs 6.5)
Mid-size to large enterprises needing a multilingual open-weight model with low-ish infrastructure requirements (2x H100 for full model). Especially good for retrieval-augmented generation over internal document stores, multi-language customer support, and workflows touching Asian / Middle Eastern / African languages where Command A's coverage materially beats Llama or Mistral. Also a strong pick for teams already in Cohere's enterprise ecosystem.
Visit Cohere Command APick NotebookLM if...
- ✓Easier to use (8 vs 6.5)
- ✓Better value for money (9.5/10)
Students researching papers, professionals who need to quickly digest long documents, and anyone who wants to turn a pile of PDFs into something they can query and listen to.
Visit NotebookLMOur Verdict
Cohere Command A and NotebookLM are extremely close overall. Your choice comes down to specific needs -- Cohere Command A is better for mid-size to large enterprises needing a multilingual open-weight model with low-ish infrastructure requirements (2x h100 for full model), while NotebookLM works best for students researching papers, professionals who need to quickly digest long documents, and anyone who wants to turn a pile of pdfs into something they can query and listen to.