Side-by-side comparison
Llama 3 70B Instruct vs ERNIE 4.5 300B A47B
| Llama 3 70B Instruct | ERNIE 4.5 300B A47B | |
|---|---|---|
| Provider | Meta | Baidu Qianfan |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 8,192 | 123,000 |
| 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 → | 0.5100 | 0.2800 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.7400 | 1.1000 |
Frequently asked questions
Which is cheaper, Llama 3 70B Instruct or ERNIE 4.5 300B A47B ?
Llama 3 70B Instruct is cheaper than ERNIE 4.5 300B A47B on a 50/50 input/output blend by about $0.065 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 70B Instruct or ERNIE 4.5 300B A47B ?
ERNIE 4.5 300B A47B has the larger context window at 123k tokens versus 8k tokens for Llama 3 70B Instruct. That means ERNIE 4.5 300B A47B can ingest about 15.0x as much text per request.
What is the difference between Llama 3 70B Instruct and ERNIE 4.5 300B A47B ?
Llama 3 70B Instruct comes from Meta; ERNIE 4.5 300B A47B comes from Baidu Qianfan. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.