Side-by-side comparison
Cogito v2.1 671B vs R1 Distill Llama 70B
DeepSeek
R1 Distill Llama 70B
{} JSON
Input / 1M
$0.7000
Output / 1M
$0.8000
| Cogito v2.1 671B | R1 Distill Llama 70B | |
|---|---|---|
| Provider | Deep Cogito | DeepSeek |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 128,000 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | json_mode | json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 1.2500 | 0.7000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 1.2500 | 0.8000 |
Frequently asked questions
Which is cheaper, Cogito v2.1 671B or R1 Distill Llama 70B?
R1 Distill Llama 70B is cheaper than Cogito v2.1 671B on a 50/50 input/output blend by about $0.5 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, Cogito v2.1 671B or R1 Distill Llama 70B?
R1 Distill Llama 70B has the larger context window at 131k tokens versus 128k tokens for Cogito v2.1 671B. That means R1 Distill Llama 70B can ingest about 1.0x as much text per request.
What is the difference between Cogito v2.1 671B and R1 Distill Llama 70B?
Cogito v2.1 671B comes from Deep Cogito; R1 Distill Llama 70B comes from DeepSeek. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.