Side-by-side comparison
Jamba Large 1.7 vs Command R+ (08-2024)
Cohere
Command R+ (08-2024)
🔧 Tools
{} JSON
Input / 1M
$2.5000
Output / 1M
$10.0000
| Jamba Large 1.7 | Command R+ (08-2024) | |
|---|---|---|
| Provider | AI21 | Cohere |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 256,000 | 128,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 2.0000 | 2.5000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 8.0000 | 10.0000 |
Frequently asked questions
Which is cheaper, Jamba Large 1.7 or Command R+ (08-2024)?
Jamba Large 1.7 is cheaper than Command R+ (08-2024) on a 50/50 input/output blend by about $1.25 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Jamba Large 1.7 or Command R+ (08-2024)?
Jamba Large 1.7 has the larger context window at 256k tokens versus 128k tokens for Command R+ (08-2024). That means Jamba Large 1.7 can ingest about 2.0x as much text per request.
What is the difference between Jamba Large 1.7 and Command R+ (08-2024)?
Jamba Large 1.7 comes from AI21; Command R+ (08-2024) comes from Cohere. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.