Side-by-side comparison
Codestral 2508 vs Trinity Large Thinking
Arcee AI
Trinity Large Thinking
🔧 Tools
{} JSON
Input / 1M
$0.2200
Output / 1M
$0.8500
| Codestral 2508 | Trinity Large Thinking | |
|---|---|---|
| Provider | Mistral | Arcee AI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 256,000 | 262,144 |
| 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 → | 0.3000 | 0.2200 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.9000 | 0.8500 |
Frequently asked questions
Which is cheaper, Codestral 2508 or Trinity Large Thinking?
Trinity Large Thinking is cheaper than Codestral 2508 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, Codestral 2508 or Trinity Large Thinking?
Trinity Large Thinking has the larger context window at 262k tokens versus 256k tokens for Codestral 2508. That means Trinity Large Thinking can ingest about 1.0x as much text per request.
What is the difference between Codestral 2508 and Trinity Large Thinking?
Codestral 2508 comes from Mistral; Trinity Large Thinking comes from Arcee AI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.