Side-by-side comparison
Llama 3.1 Euryale 70B v2.2 vs Qwen3 235B A22B
Sao10K
Llama 3.1 Euryale 70B v2.2
🔧 Tools
{} JSON
Input / 1M
$0.8500
Output / 1M
$0.8500
| Llama 3.1 Euryale 70B v2.2 | Qwen3 235B A22B | |
|---|---|---|
| Provider | Sao10K | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 131,072 |
| 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 → | 0.8500 | 0.4550 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.8500 | 1.8200 |
Frequently asked questions
Which is cheaper, Llama 3.1 Euryale 70B v2.2 or Qwen3 235B A22B?
Llama 3.1 Euryale 70B v2.2 is cheaper than Qwen3 235B A22B on a 50/50 input/output blend by about $0.2875 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
What is the difference between Llama 3.1 Euryale 70B v2.2 and Qwen3 235B A22B?
Llama 3.1 Euryale 70B v2.2 comes from Sao10K; Qwen3 235B A22B comes from Qwen. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.