Model introduction
DeepSeek V3.2 is a reasoning-first open model for agent scenarios, using sparse attention for efficient long context and supporting tools in thinking and non-thinking modes.
Model capabilities
Specifications come from the cited model material. Catalog tags help identify access features; use the source documentation for exact limits.
Verified specifications
- Official positioning
- Reasoning-first model for agents
- Context window
- 164,000 tokens
- Maximum output
- 164,000 tokens
- Verified capabilities
- DSA sparse attention, thinking mode, tool use
Sources: B.AI DeepSeek V3.2 model guide
Model pricing and access
Prices are read directly from the MoleAPI console catalog and shown by current billing group and context tier.
Your final charge follows the account group shown in the console.
Live pricing source
Pricing table
USD / 1M tokensStandardx1defaultInput $0.29 · Output $0.435
Input
$0.29 / 1M tokens
Output
$0.435 / 1M tokens
Cache read
$0.145 / 1M tokens
Discountx0.8discountInput $0.232 · Output $0.348
Input
$0.232 / 1M tokens
Output
$0.348 / 1M tokens
Cache read
$0.116 / 1M tokens
Relayx0.3relayInput $0.087 · Output $0.1305
Input
$0.087 / 1M tokens
Output
$0.1305 / 1M tokens
Cache read
$0.0435 / 1M tokens
Access protocols
Available billing groups: Standard, Discount, Relay
- openai
- POST
- /v1/chat/completions
About deepseek-v3.2
This introduction is transcreated for clarity and cross-checked against the cited model material.
DeepSeek V3.2 is a reasoning-first open model for agent scenarios, using sparse attention for efficient long context and supporting tools in thinking and non-thinking modes.
Core strengths
- DeepSeek Sparse Attention improves long-context reasoning efficiency.
- Thinking and non-thinking modes can both use tools.
- A 164K context and open-weight path support controlled deployment.
Limitations
- It is primarily text-focused; vision and audio need external models or tools.
- Thinking mode adds token use and wait time.
Selection and production evaluation
Start a deepseek-v3.2 evaluation by mapping its official positioning to real work: Agent development, code generation and review, long-text analysis, and complex problem solving with tools. The first pass should exercise both its main strength, "DeepSeek Sparse Attention improves long-context reasoning efficiency.", and its known limitation, "It is primarily text-focused; vision and audio need external models or tools.", instead of relying on a single subjective general-chat comparison.
For access, MoleAPI currently lists openai protocols and the Standard, Discount, Relay billing groups for this DeepSeek model; the default price summary is Input $0.29 / 1M tokens · Output $0.435 / 1M tokens. Pricing, protocols, and groups come from the live catalog, so production planning should still price representative requests using real context length, output size, and cache-hit assumptions.
No independent ranking is shown unless it matches this exact model ID and reasoning profile, so nearby variants are not used as a proxy. Before launch, pin the model ID, prompt, and sample set, then compare task accuracy, structured-output validity, tool-call success, and timeout rates under the same conditions.
The model material on this page was last checked on 2026-07-24. When upstream model cards, context limits, or tool support change, update the cited bilingual facts before changing the recommendation; live MoleAPI price changes remain separate and update from the catalog automatically.
Code examples
These examples use MoleAPI's OpenAI-compatible endpoint and run after you replace the API key.
curl https://api.moleapi.com/v1/chat/completions \
-H "Authorization: Bearer $MOLEAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v3.2",
"messages": [{"role": "user", "content": "Hello"}]
}'Frequently asked questions
How is deepseek-v3.2 priced?
This page reads prices from the MoleAPI console API and updates with model prices, context tiers, and account groups.
How can I access deepseek-v3.2?
Protocols and endpoints come from the supported_endpoint_types field in the MoleAPI model catalog.
How do I switch an existing project to deepseek-v3.2?
Keep the MoleAPI API address and key, replace the model parameter with the model ID on this page, then check protocol-specific parameter differences.
Where do the deepseek-v3.2 model details come from?
Capabilities and limitations are checked against B.AI and the other cited pages. Pricing and available protocols come only from the MoleAPI console.