ERNIE 4.5 21B A3B Thinking vs Mistral 7B Instruct v0.1
ERNIE 4.5 21B A3B Thinking
Mistral 7B Instruct v0.1
| ERNIE 4.5 21B A3B Thinking | Mistral 7B Instruct v0.1 | |
|---|---|---|
| Provider | Baidu Qianfan | Mistral |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 2,824 |
| 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 → | 0.0700 | 0.1100 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.2800 | 0.1900 |
Frequently asked questions
Which is cheaper, ERNIE 4.5 21B A3B Thinking or Mistral 7B Instruct v0.1?
Mistral 7B Instruct v0.1 is cheaper than ERNIE 4.5 21B A3B Thinking on a 50/50 input/output blend by about $0.025 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, ERNIE 4.5 21B A3B Thinking or Mistral 7B Instruct v0.1?
ERNIE 4.5 21B A3B Thinking has the larger context window at 131k tokens versus 3k tokens for Mistral 7B Instruct v0.1. That means ERNIE 4.5 21B A3B Thinking can ingest about 46.4x as much text per request.
What is the difference between ERNIE 4.5 21B A3B Thinking and Mistral 7B Instruct v0.1?
ERNIE 4.5 21B A3B Thinking comes from Baidu Qianfan; Mistral 7B Instruct v0.1 comes from Mistral. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.