Side-by-side comparison
gpt-oss-120b vs Ling-2.6-flash
inclusionAI
Ling-2.6-flash
🔧 Tools
{} JSON
Input / 1M
$0.0800
Output / 1M
$0.2400
| gpt-oss-120b | Ling-2.6-flash | |
|---|---|---|
| Provider | OpenAI | inclusionAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 131,072 | 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 → | 0.0390 | 0.0800 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.1800 | 0.2400 |
Frequently asked questions
Which is cheaper, gpt-oss-120b or Ling-2.6-flash?
gpt-oss-120b is cheaper than Ling-2.6-flash on a 50/50 input/output blend by about $0.0505 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, gpt-oss-120b or Ling-2.6-flash?
Ling-2.6-flash has the larger context window at 262k tokens versus 131k tokens for gpt-oss-120b. That means Ling-2.6-flash can ingest about 2.0x as much text per request.
What is the difference between gpt-oss-120b and Ling-2.6-flash?
gpt-oss-120b comes from OpenAI; Ling-2.6-flash comes from inclusionAI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.