Side-by-side comparison
Ling-2.6-1T vs Devstral Medium
Mistral
Devstral Medium
🔧 Tools
{} JSON
Input / 1M
$0.4000
Output / 1M
$2.0000
| Ling-2.6-1T | Devstral Medium | |
|---|---|---|
| Provider | inclusionAI | Mistral |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 262,144 | 131,072 |
| 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 | 0.4000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 2.5000 | 2.0000 |
Frequently asked questions
Which is cheaper, Ling-2.6-1T or Devstral Medium?
Devstral Medium is cheaper than Ling-2.6-1T on a 50/50 input/output blend by about $0.2 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, Ling-2.6-1T or Devstral Medium?
Ling-2.6-1T has the larger context window at 262k tokens versus 131k tokens for Devstral Medium. That means Ling-2.6-1T can ingest about 2.0x as much text per request.
What is the difference between Ling-2.6-1T and Devstral Medium?
Ling-2.6-1T comes from inclusionAI; Devstral Medium 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.