# DeepSeek V3.2 Thinking

DeepSeek V3.2 Thinking operates in thinking mode with an extended output budget. It suits complex problems where thorough chain-of-thought exploration improves answer quality.

- **Model ID:** `deepseek/deepseek-v3.2-thinking`
- **Type:** chat
- **Providers:** bedrock, deepinfra
- **Context window:** 163,842
- **Maximum output tokens:** 8,000
- **Pricing:** $0.26/1M input tokens, $0.38/1M output tokens
- **Canonical page:** https://vercel.com/ai-gateway/models/deepseek-v3.2-thinking

## Supported parameters

Detailed capability metadata has not been reported for this model.

## Example

```ts
import { streamText } from 'ai'

const result = streamText({
  model: 'deepseek/deepseek-v3.2-thinking',
  prompt: 'Why is the sky blue?'
})
```

## About

DeepSeek V3.2 Thinking became available on AI Gateway on December 1, 2025 as the reasoning-optimized variant of the V3.2 release. It operates exclusively in thinking mode, generating extended chain-of-thought reasoning traces before producing a final answer. The output token budget extends to 8K tokens, compared to 8K for the standard V3.2 chat variant. That headroom accommodates complex multi-step reasoning chains.

The trade-off is explicit: DeepSeek V3.2 Thinking does not support tool use. This makes it a pure reasoning engine rather than a tool-augmented agent. Where the standard DeepSeek-V3.2 supports tool calls across both reasoning and non-reasoning modes, the Thinking variant trades tool integration for a deeper reasoning budget. Use it when the reasoning process itself is the primary value, such as complex scientific analysis, multi-step mathematical derivation, or structured argument construction.

The Thinking variant and standard V3.2 are accessible through AI Gateway under the `deepseek` provider without separate account setup.

## What to consider

DeepSeek V3.2 Thinking does not support tool use. If your pipeline needs both extended reasoning and tool calls, use the standard DeepSeek-V3.2 model, which supports tool calls in both reasoning and non-reasoning modes.

## When to use

### Best For

- Complex scientific, mathematical, or logical problems where a reasoning budget of 8K tokens allows thorough exploration of solution paths before reaching an answer
- Document analysis requiring structured multi-step inference (legal reasoning, regulatory interpretation, academic literature synthesis) where reasoning depth affects output quality
- Research contexts where seeing the full chain of thought is part of the desired output, not just the final answer
- Evaluating reasoning model behavior where the extended output budget lets you observe how the model approaches ambiguous or difficult prompts

### Consider Alternatives When

- Tool calls are required alongside reasoning. Use standard DeepSeek-V3.2, which supports tool use in both modes
- Your task is general chat, summarization, or instruction-following without complex reasoning needs. Standard DeepSeek-V3.2 costs less per output token
- Response latency is critical. Extended reasoning traces produce longer responses with higher time-to-complete

## Best for

- **Complex scientific problems:** A reasoning budget of 8K tokens allows thorough exploration of solution paths for mathematical and logical tasks
- **Structured document analysis:** Multi-step inference for legal reasoning, regulatory interpretation, and academic literature synthesis
- **Chain-of-thought output:** Research contexts where seeing the full reasoning trace is part of the desired output
- **Reasoning model evaluation:** The extended output budget lets you observe how the model approaches ambiguous or difficult prompts

## Consider alternatives

- **Tool calls required:** Use standard DeepSeek-V3.2, which supports tool use alongside reasoning in both modes
- **General chat or summarization:** Standard DeepSeek-V3.2 costs less per output token for instruction-following without complex reasoning
- **Latency-critical responses:** Extended reasoning traces produce longer responses with higher time-to-complete

## Frequently asked questions

### Does DeepSeek V3.2 Thinking support tool calling?

No. The Thinking variant is a pure reasoning engine without tool-use support. For tool calls alongside reasoning, use the standard DeepSeek-V3.2 model.

### What is the maximum output token budget for DeepSeek V3.2 Thinking?

Up to 8K tokens per response, compared to 8K for the standard V3.2 chat variant.

### When would I use DeepSeek V3.2 Thinking over DeepSeek-R1?

Choose DeepSeek V3.2 Thinking for the V3.2 stack and reasoning output up to 8K tokens. DeepSeek-R1 is MIT-licensed. If license terms matter for your deployment, confirm the license for the model you pick.

### Why does the output token budget matter for reasoning models?

Reasoning models generate a chain-of-thought trace before the final answer. Complex problems can require thousands of reasoning tokens. A budget of 8K tokens provides headroom for multi-step derivations that would exceed an 8K limit.

### How do I access DeepSeek V3.2 Thinking through AI Gateway?

Use the model ID `deepseek/deepseek-v3.2-thinking` with an AI Gateway API key or OIDC token. No separate DeepSeek platform account is required.

## Links

- [Model page](https://vercel.com/ai-gateway/models/deepseek-v3.2-thinking)
- [AI Gateway documentation](https://vercel.com/docs/ai-gateway)
- [Provider model documentation](https://aws.amazon.com/about-aws/whats-new/2026/02/amazon-bedrock-adds-support-six-open-weights-models/)