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Cohere vs NVIDIA

Cohere (5 models) vs NVIDIA (11 models) - compared across composite scores, pricing, capabilities, and context windows.

Models
5
Avg Score
45
Top Model
Score: 51
Price Range
$0.150 - $10.00
per 1M output tokens
1 free2 open source256K max context
Models
11
Avg Score
40
Price Range
$0.200 - $3.60
per 1M output tokens
7 free11 open source1.0M max context

Capability Comparison

CapabilityCohereNVIDIALeader
Vision
0/53/11NVIDIA
Reasoning
1/511/11NVIDIA
Function Calling
3/510/11NVIDIA
JSON Mode
4/56/11NVIDIA
Web Search
0/50/11Tie
Streaming
5/511/11NVIDIA
Image Output
0/50/11Tie

Pricing Comparison

MetricCohereNVIDIA
Cheapest Input (per 1M tokens)$0.037
Command R7B (12-2024)
$0.050
Nemotron 3 Nano 30B A3B
Cheapest Output (per 1M tokens)$0.150$0.200
Most Expensive Input (per 1M tokens)$2.50
Command A
$0.600
Nemotron 3 Ultra
Most Expensive Output (per 1M tokens)$10.00$3.60
Free Models17
Max Context Window256K1.0M

All Cohere Models (5)

ModelScoreInput $/MOutput $/M
Command A51$2.50$10.00
Command R (08-2024)49$0.150$0.600
Command R+ (08-2024)49$2.50$10.00
North Mini Code (free)40FreeFree
Command R7B (12-2024)36$0.037$0.150

All NVIDIA Models (11)

ModelScoreInput $/MOutput $/M
Nemotron 3.5 Content Safety (free)40FreeFree
Nemotron 3 Ultra40$0.600$3.60
Nemotron 3 Ultra (batch)40$0.300$1.80
Nemotron 3 Ultra (free)40FreeFree
Nemotron 3 Nano Omni (free)40FreeFree
Nemotron 3 Super40$0.085$0.400
Nemotron 3 Super (free)40FreeFree
Nemotron 3 Nano 30B A3B40$0.050$0.200
Nemotron 3 Nano 30B A3B (free)40FreeFree
Nemotron Nano 12B 2 VL (free)40FreeFree
Nemotron Nano 9B V2 (free)40FreeFree
Frequently Asked Questions

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.

Cohere vs NVIDIA - AI Provider Comparison (2026) | LM Market Cap