Side-by-side comparison
CoBuddy (free) vs Llama 3.3 70B Instruct (free)
Meta
Llama 3.3 70B Instruct (free)
🔧 Tools
Input / 1M
$0.0000
Output / 1M
$0.0000
| CoBuddy (free) | Llama 3.3 70B Instruct (free) | |
|---|---|---|
| Provider | Baidu Qianfan | Meta |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 65,536 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools | tools |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.0000 | 0.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.0000 | 0.0000 |
Frequently asked questions
Which is cheaper, CoBuddy (free) or Llama 3.3 70B Instruct (free)?
CoBuddy (free) is cheaper than Llama 3.3 70B Instruct (free) on a 50/50 input/output blend by about $0 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, CoBuddy (free) or Llama 3.3 70B Instruct (free)?
CoBuddy (free) has the larger context window at 131k tokens versus 66k tokens for Llama 3.3 70B Instruct (free). That means CoBuddy (free) can ingest about 2.0x as much text per request.
What is the difference between CoBuddy (free) and Llama 3.3 70B Instruct (free)?
CoBuddy (free) comes from Baidu Qianfan; Llama 3.3 70B Instruct (free) comes from Meta. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.