Side-by-side comparison
DeepSeek V3.2 Speciale vs Olmo 3 32B Think
DeepSeek
DeepSeek V3.2 Speciale
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Input / 1M
$0.2870
Output / 1M
$0.4310
| DeepSeek V3.2 Speciale | Olmo 3 32B Think | |
|---|---|---|
| Provider | DeepSeek | AllenAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 163,840 | 65,536 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | json_mode | json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.2870 | 0.1500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.4310 | 0.5000 |
Frequently asked questions
Which is cheaper, DeepSeek V3.2 Speciale or Olmo 3 32B Think?
Olmo 3 32B Think is cheaper than DeepSeek V3.2 Speciale on a 50/50 input/output blend by about $0.034 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, DeepSeek V3.2 Speciale or Olmo 3 32B Think?
DeepSeek V3.2 Speciale has the larger context window at 164k tokens versus 66k tokens for Olmo 3 32B Think. That means DeepSeek V3.2 Speciale can ingest about 2.5x as much text per request.
What is the difference between DeepSeek V3.2 Speciale and Olmo 3 32B Think?
DeepSeek V3.2 Speciale comes from DeepSeek; Olmo 3 32B Think comes from AllenAI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.