Side-by-side comparison
ERNIE 4.5 21B A3B Thinking vs LFM2-24B-A2B
Baidu Qianfan
ERNIE 4.5 21B A3B Thinking
Input / 1M
$0.0700
Output / 1M
$0.2800
| ERNIE 4.5 21B A3B Thinking | LFM2-24B-A2B | |
|---|---|---|
| Provider | Baidu Qianfan | LiquidAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 32,768 |
| 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 | 0.0300 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.2800 | 0.1200 |
Frequently asked questions
Which is cheaper, ERNIE 4.5 21B A3B Thinking or LFM2-24B-A2B?
LFM2-24B-A2B is cheaper than ERNIE 4.5 21B A3B Thinking on a 50/50 input/output blend by about $0.1 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 LFM2-24B-A2B?
ERNIE 4.5 21B A3B Thinking has the larger context window at 131k tokens versus 33k tokens for LFM2-24B-A2B. That means ERNIE 4.5 21B A3B Thinking can ingest about 4.0x as much text per request.
What is the difference between ERNIE 4.5 21B A3B Thinking and LFM2-24B-A2B?
ERNIE 4.5 21B A3B Thinking comes from Baidu Qianfan; LFM2-24B-A2B comes from LiquidAI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.