L LLM Cloud Hub
Side-by-side comparison

Qwen Plus 0728 (thinking) vs Codestral 2508

Qwen

Qwen Plus 0728 (thinking)

πŸ”§ Tools {} JSON
Input / 1M
$0.2600
Output / 1M
$0.7800
View Qwen Plus 0728 (thinking) β†’
Mistral

Codestral 2508

πŸ”§ Tools {} JSON
Input / 1M
$0.3000
Output / 1M
$0.9000
View Codestral 2508 β†’
Qwen Plus 0728 (thinking)Codestral 2508
Provider Qwen Mistral
Context window Maximum tokens (input + output) the model can process in a single request. Glossary β†’ 1,000,000 256,000
Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). tools, json_mode tools, json_mode
Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary β†’ 0.2600 0.3000
Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5Γ— pricier than input. Glossary β†’ 0.7800 0.9000

Frequently asked questions

Which is cheaper, Qwen Plus 0728 (thinking) or Codestral 2508?

Qwen Plus 0728 (thinking) is cheaper than Codestral 2508 on a 50/50 input/output blend by about $0.08 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, Qwen Plus 0728 (thinking) or Codestral 2508?

Qwen Plus 0728 (thinking) has the larger context window at 1M tokens versus 256k tokens for Codestral 2508. That means Qwen Plus 0728 (thinking) can ingest about 3.9x as much text per request.

What is the difference between Qwen Plus 0728 (thinking) and Codestral 2508?

Qwen Plus 0728 (thinking) comes from Qwen; Codestral 2508 comes from Mistral. 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.

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