Side-by-side comparison
Cogito v2.1 671B vs Llama 3.3 Euryale 70B
Sao10K
Llama 3.3 Euryale 70B
{} JSON
Input / 1M
$0.6500
Output / 1M
$0.7500
| Cogito v2.1 671B | Llama 3.3 Euryale 70B | |
|---|---|---|
| Provider | Deep Cogito | Sao10K |
| 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 | 0.6500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 1.2500 | 0.7500 |
Frequently asked questions
Which is cheaper, Cogito v2.1 671B or Llama 3.3 Euryale 70B?
Llama 3.3 Euryale 70B is cheaper than Cogito v2.1 671B on a 50/50 input/output blend by about $0.55 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 Llama 3.3 Euryale 70B?
Llama 3.3 Euryale 70B has the larger context window at 131k tokens versus 128k tokens for Cogito v2.1 671B. That means Llama 3.3 Euryale 70B can ingest about 1.0x as much text per request.
What is the difference between Cogito v2.1 671B and Llama 3.3 Euryale 70B?
Cogito v2.1 671B comes from Deep Cogito; Llama 3.3 Euryale 70B comes from Sao10K. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.