Command R vs Llama 3.3 70B
Compare Cohere and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Command R
Llama 3.3 70B
Cost Differences
Llama 3.3 70B costs more than Command R
Feature Comparison
| Feature | Command R | Llama 3.3 70B |
|---|---|---|
| Provider | Cohere | Meta (via Together AI) |
| Input Price | $0.15/1M tokens | $0.88/1M tokens |
| Output Price | $0.60/1M tokens | $0.88/1M tokens |
| Context Window | 128,000 tokens | 131,072 tokens |
| Max Output | 4,096 tokens | 4,096 tokens |
| Category | efficient | standard |
| Capabilities | textcode | textcode |
| Release Date | 3/11/2024 | 12/6/2024 |
Command R vs Llama 3.3 70B: Which Should You Choose?
Choosing between Command R and Llama 3.3 70B depends on your priorities: cost efficiency, context length, or raw capability. Command R is the more affordable option at $0.15/1M input tokens — 83% cheaper than Llama 3.3 70B. Meanwhile, Llama 3.3 70B offers a significantly larger context window at 131,072 tokens vs 128,000 for Command R.
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 3.3 70B is standard. This means they're optimized for different workloads. Llama 3.3 70B 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 $0.88 for Llama 3.3 70B. 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 3.3 70B when:
- • You need a larger context window (131,072 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 3.3 70B (Meta (via Together AI))
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