DeepSeek V3.2 Speciale
DeepSeek-V3.2-Speciale is a high-compute variant of DeepSeek-V3.2 optimized for maximum reasoning and agentic performance. It builds on DeepSeek Sparse Attention (DSA) for efficient long-context processing, then scales post-training reinforcement lea
About
DeepSeek-V3.2-Speciale is a high-compute variant of DeepSeek-V3.2 optimized for maximum reasoning and agentic performance. It builds on DeepSeek Sparse Attention (DSA) for efficient long-context processing, then scales post-training reinforcement learning...
Modalities
Code Examples
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v3.2-speciale",
"messages": [
{ "role": "user", "content": "Explain quantum entanglement in one sentence." }
]
}' API Parameters
| Name | Type | Description |
|---|---|---|
frequency_penalty | number | Penalize tokens by their frequency so far. Positive values reduce repetition. |
include_reasoning | boolean | Include the model's internal reasoning trace in the response. |
logit_bias | object | Map of token-id to bias (-100…100) added to the logit before sampling. |
max_tokens deprecated | integer | Deprecated. Use max_completion_tokens. |
min_p | unknown | — |
presence_penalty | number | Penalize tokens that have appeared at all so far. Positive values encourage new topics. |
reasoning | object | Configuration for extended-thinking / reasoning mode. |
repetition_penalty | number | Penalize repeated tokens (>1.0 reduces repetition, <1.0 encourages it). |
response_format | one of | Constrain output to a JSON schema or an enum (structured outputs). |
seed | integer | Deterministic seed for sampling. Same seed + same prompt produces identical output. |
stop | array | Up to 4 sequences where the API will stop generating tokens. |
structured_outputs | boolean | Enable JSON-schema-constrained output. |
temperature | number | Sampling temperature; higher values produce more random output. 0 is deterministic. |
top_k | integer | Limit sampling to the top-k most likely tokens at each step. |
top_p | number | Nucleus sampling: consider only tokens whose cumulative probability ≥ top_p. |
Standard OpenAI-compatible parameters. Consult the provider docs for model-specific behaviour.