L LLM Cloud Hub
Side-by-side comparison

Mistral Small 3.1 24B vs ERNIE 4.5 VL 424B A47B

Mistral

Mistral Small 3.1 24B

πŸ‘ Vision
Input / 1M
$0.3500
Output / 1M
$0.5600
View Mistral Small 3.1 24B β†’
Baidu Qianfan

ERNIE 4.5 VL 424B A47B

πŸ‘ Vision
Input / 1M
$0.4200
Output / 1M
$1.2500
View ERNIE 4.5 VL 424B A47B β†’
Mistral Small 3.1 24BERNIE 4.5 VL 424B A47B
Provider Mistral Baidu Qianfan
Context window Maximum tokens (input + output) the model can process in a single request. Glossary β†’ 128,000 123,000
Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). vision vision
Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary β†’ 0.3500 0.4200
Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5Γ— pricier than input. Glossary β†’ 0.5600 1.2500

Frequently asked questions

Which is cheaper, Mistral Small 3.1 24B or ERNIE 4.5 VL 424B A47B ?

Mistral Small 3.1 24B is cheaper than ERNIE 4.5 VL 424B A47B on a 50/50 input/output blend by about $0.38 per 1M tokens. Exact savings depend on your input-vs-output ratio β€” use the cost calculator on this page for a workload-specific estimate.

Which has a larger context window, Mistral Small 3.1 24B or ERNIE 4.5 VL 424B A47B ?

Mistral Small 3.1 24B has the larger context window at 128k tokens versus 123k tokens for ERNIE 4.5 VL 424B A47B . That means Mistral Small 3.1 24B can ingest about 1.0x as much text per request.

What is the difference between Mistral Small 3.1 24B and ERNIE 4.5 VL 424B A47B ?

Mistral Small 3.1 24B comes from Mistral; ERNIE 4.5 VL 424B A47B comes from Baidu Qianfan. They differ in pricing, context window, and supported capabilities β€” see the side-by-side table on this page for the exact figures, refreshed nightly.

Keyboard shortcuts

?
Show this overlay
/
Focus the first form field
g h
Go to / (home)
g b
Go to /best-llm-for
g c
Go to /cost
g s
Go to /self-hosted
g x
Go to /compliance
Esc
Close any overlay

Inspired by Linear and GitHub conventions. The two-key sequences (g then h) work within ~1 second.