Side-by-side comparison
Llama 3.1 70B Hanami x1 vs Palmyra X5
Sao10K
Llama 3.1 70B Hanami x1
Input / 1M
$3.0000
Output / 1M
$3.0000
| Llama 3.1 70B Hanami x1 | Palmyra X5 | |
|---|---|---|
| Provider | Sao10K | Writer |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 16,000 | 1,040,000 |
| 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 → | 3.0000 | 0.6000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 3.0000 | 6.0000 |
Frequently asked questions
Which is cheaper, Llama 3.1 70B Hanami x1 or Palmyra X5?
Llama 3.1 70B Hanami x1 is cheaper than Palmyra X5 on a 50/50 input/output blend by about $0.3 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, Llama 3.1 70B Hanami x1 or Palmyra X5?
Palmyra X5 has the larger context window at 1M tokens versus 16k tokens for Llama 3.1 70B Hanami x1. That means Palmyra X5 can ingest about 65.0x as much text per request.
What is the difference between Llama 3.1 70B Hanami x1 and Palmyra X5?
Llama 3.1 70B Hanami x1 comes from Sao10K; Palmyra X5 comes from Writer. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.