Command R+ vs Gemini Embedding 2
Compare Cohere and Google AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Command R+
Gemini Embedding 2
Cost Differences
Gemini Embedding 2 costs less than Command R+
Feature Comparison
| Feature | Command R+ | Gemini Embedding 2 |
|---|---|---|
| Provider | Cohere | |
| Input Price | $2.50/1M tokens | $0.20/1M tokens |
| Output Price | $10.00/1M tokens | $0.20/1M tokens |
| Context Window | 128,000 tokens | 8,192 tokens |
| Max Output | 4,096 tokens | 3,072 tokens |
| Category | flagship | embedding |
| Capabilities | textcodereasoning | textvisionaudiovideoembeddings |
| Release Date | 4/4/2024 | 3/10/2026 |
Command R+ vs Gemini Embedding 2: Which Should You Choose?
Choosing between Command R+ and Gemini Embedding 2 depends on your priorities: cost efficiency, context length, or raw capability. Gemini Embedding 2 is the more affordable option at $0.20/1M input tokens — 92% cheaper than Command R+. Meanwhile, Command R+ offers a significantly larger context window at 128,000 tokens vs 8,192 for Gemini Embedding 2.
These models come from different providers — Cohere and Google — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Cohere, switching to Googleinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Command R+ is a flagship model while Gemini Embedding 2 is embedding. This means they're optimized for different workloads. Command R+ is built for complex tasks that require deeper reasoning, while Gemini Embedding 2 offers better value for routine operations.
Output costs matter too. Command R+ charges $10.00/1M output tokens vs $0.20 for Gemini Embedding 2. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Gemini Embedding 2 has the edge here at $0.20/1M output tokens.
Multimodal capabilities: Gemini Embedding 2 supports vision (image inputs) while Command R+ is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Command R+ when:
- • You need a larger context window (128,000 tokens)
- • You need longer outputs (up to 4,096 tokens)
- • You're already using Cohere's API ecosystem
Choose Gemini Embedding 2 when:
- • Budget is a primary concern
- • You need more capabilities (vision, audio, video, embeddings)
- • You're already using Google's API ecosystem
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Command R+ (Cohere)
Gemini Embedding 2 (Google)
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