Side-by-side comparison
Sonar Deep Research vs Llama 3.1 70B Hanami x1
Sao10K
Llama 3.1 70B Hanami x1
Input / 1M
$3.0000
Output / 1M
$3.0000
| Sonar Deep Research | Llama 3.1 70B Hanami x1 | |
|---|---|---|
| Provider | Perplexity | Sao10K |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 128,000 | 16,000 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | text-only | text-only |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 2.0000 | 3.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 8.0000 | 3.0000 |
Frequently asked questions
Which is cheaper, Sonar Deep Research or Llama 3.1 70B Hanami x1?
Llama 3.1 70B Hanami x1 is cheaper than Sonar Deep Research on a 50/50 input/output blend by about $2 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, Sonar Deep Research or Llama 3.1 70B Hanami x1?
Sonar Deep Research has the larger context window at 128k tokens versus 16k tokens for Llama 3.1 70B Hanami x1. That means Sonar Deep Research can ingest about 8.0x as much text per request.
What is the difference between Sonar Deep Research and Llama 3.1 70B Hanami x1?
Sonar Deep Research comes from Perplexity; Llama 3.1 70B Hanami x1 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.