Cohere (4 models) vs NVIDIA (9 models) - compared across composite scores, pricing, capabilities, and context windows.
| Capability | Cohere | NVIDIA | Leader |
|---|---|---|---|
Vision | 0/4 | 2/9 | NVIDIA |
Reasoning | 0/4 | 9/9 | NVIDIA |
Function Calling | 2/4 | 9/9 | NVIDIA |
JSON Mode | 4/4 | 6/9 | NVIDIA |
Web Search | 0/4 | 0/9 | Tie |
Streaming | 4/4 | 9/9 | NVIDIA |
Image Output | 0/4 | 0/9 | Tie |
| Metric | Cohere | NVIDIA |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.037 Command R7B (12-2024) | $0.040 Nemotron Nano 9B V2 |
| Cheapest Output (per 1M tokens) | $0.150 | $0.160 |
| Most Expensive Input (per 1M tokens) | $2.50 Command A | $0.100 Nemotron 3 Super |
| Most Expensive Output (per 1M tokens) | $10.00 | $0.450 |
| Free Models | 0 | 5 |
| Max Context Window | 256K | 262K |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Command A | 51 | $2.50 | $10.00 |
| Command R+ (08-2024) | 49 | $2.50 | $10.00 |
| Command R (08-2024) | 49 | $0.150 | $0.600 |
| Command R7B (12-2024) | 36 | $0.037 | $0.150 |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Llama 3.3 Nemotron Super 49B V1.5 | 61 | $0.100 | $0.400 |
| Nemotron 3 Nano Omni (free) | 40 | Free | Free |
| Nemotron 3 Super (free) | 40 | Free | Free |
| Nemotron 3 Super | 40 | $0.090 | $0.450 |
| Nemotron 3 Nano 30B A3B (free) | 40 | Free | Free |
| Nemotron 3 Nano 30B A3B | 40 | $0.050 | $0.200 |
| Nemotron Nano 12B 2 VL (free) | 40 | Free | Free |
| Nemotron Nano 9B V2 (free) | 40 | Free | Free |
| Nemotron Nano 9B V2 | 40 | $0.040 | $0.160 |
Compare any two AI providers side-by-side.
Cohere's pricing strategy appears optimized for enterprise customers willing to pay premium rates, with their cheapest model at $0.150/M tokens versus NVIDIA's free tier covering 4 models. The price gap is most extreme at the high end where Cohere charges $10.00/M tokens (Command R+ 08-2024) while NVIDIA's most expensive model costs just $1.80/M tokens despite offering similar 256K+ context windows.
NVIDIA's open-source approach enables broader capability implementation across their 11-model portfolio, with function calling available in models ranging from their top-scoring Nemotron 3 Nano 30B down to smaller variants. Cohere's smaller 4-model lineup focuses on their Command series, limiting function calling to just 2 models despite this being a critical enterprise feature.
Cohere has chosen to specialize in text-only models (0/4 vision support) while NVIDIA offers vision in 2/11 models, suggesting different market positioning strategies. This gap is particularly notable given that both providers target enterprise customers who increasingly need multimodal capabilities for document processing and visual understanding tasks.
Cohere's value proposition centers on managed enterprise deployments with only 1/4 models open source, targeting organizations that prioritize vendor support over customization flexibility. NVIDIA's 100% open-source portfolio appeals to teams wanting full control, evidenced by their 91% reasoning capability coverage (10/11 models) that enables custom fine-tuning for specialized tasks.
The 6K token difference between Cohere's 256K (Command R+ 08-2024) and NVIDIA's 262K maximum represents just 2.3% more capacity, essentially negligible for most use cases. Both providers clearly target long-context applications like document analysis and multi-turn conversations, though NVIDIA achieves this across a broader range of models at 10-50x lower prices.