Command R vs Llama 3.1 405B
Compare Cohere and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Command R
Llama 3.1 405B
Cost Differences
Llama 3.1 405B costs more than Command R
Feature Comparison
| Feature | Command R | Llama 3.1 405B |
|---|---|---|
| Provider | Cohere | Meta (via Together AI) |
| Input Price | $0.15/1M tokens | $3.50/1M tokens |
| Output Price | $0.60/1M tokens | $3.50/1M tokens |
| Context Window | 128,000 tokens | 128,000 tokens |
| Max Output | 4,096 tokens | 32,768 tokens |
| Category | efficient | flagship |
| Capabilities | textcode | textcodereasoning |
| Release Date | 3/11/2024 | 7/23/2024 |
Command R vs Llama 3.1 405B: Which Should You Choose?
Choosing between Command R and Llama 3.1 405B depends on your priorities: cost efficiency, context length, or raw capability. Command R is the more affordable option at $0.15/1M input tokens — 96% cheaper than Llama 3.1 405B.
These models come from different providers — Cohere and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Cohere, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Command R is a efficient model while Llama 3.1 405B is flagship. This means they're optimized for different workloads. Llama 3.1 405B targets more demanding workloads, while Command R provides a cost-effective option for everyday tasks.
Output costs matter too. Command R charges $0.60/1M output tokens vs $3.50 for Llama 3.1 405B. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Command R has the edge here at $0.60/1M output tokens.
Best Use Cases
Choose Command R when:
- • Budget is a primary concern
- • You're already using Cohere's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose Llama 3.1 405B when:
- • You need more capabilities (reasoning)
- • You need longer outputs (up to 32,768 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Command R (Cohere)
Llama 3.1 405B (Meta (via Together AI))
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