DeepSeek V3.2 Speciale style="color:var(--t2);font-weight:400">APIOPEN WEIGHTS131K context

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).

What is DeepSeek V3.2 Speciale?

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

DeepSeek V3.2 on the release timeline

DeepSeek V3.2 pricing

Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):

On output price, DeepSeek V3.2 is cheaper than 83% of the 309 models in the catalog. It is served by 12 providers; the best combined rate at our last snapshot was ≈ $0.23 / $0.34 per 1M via StreamLake, with upstream quantizations fp4, fp8.

What DeepSeek V3.2 costs per month

Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.

DeepSeek V3.2 vs alternatives

Specs

How to call DeepSeek V3.2

Copyfrom openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
    model="deepseek/deepseek-v3.2",
    messages=[{"role": "user", "content": "Hello"}],
    # supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)

Copycurl https://api.datallmlab.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek/deepseek-v3.2","messages":[{"role":"user","content":"Hello"}]}'

Copyimport OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
  model: "deepseek/deepseek-v3.2",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes DeepSeek V3.2 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for DeepSeek V3.2

• State the goal, not every step. DeepSeek V3.2 reasons internally — give it the objective, constraints and success criteria and let it plan the approach; over-scripting each step tends to lower quality. Turn effort up for hard problems.
• Give it real tools. Pass a tools=[...] schema instead of asking it to "pretend" — let DeepSeek V3.2 emit tool calls, execute them, and feed results back for the next turn.
• Constrain JSON with a schema. Use response_format / structured outputs rather than "reply in JSON" to get valid, parseable objects every time.
• Cheap enough to batch. Great for high-volume classification, extraction and drafting — template the prompt, batch requests, and validate outputs programmatically.

Tips are derived from DeepSeek V3.2's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for DeepSeek V3.2

Popular open-source projects for running and building with DeepSeek V3.2 — star counts pulled from GitHub (July 2026).

Listed by GitHub stars; inclusion is by ecosystem relevance (inference engines, agent frameworks and SDKs), not affiliation. Stars change — see each repo for current numbers.

Migrating to DeepSeek V3.2

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → deepseek/deepseek-v3.2. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

DeepSeek V3.2 ships open weights (deepseek-ai/DeepSeek-V3.2, ~2.2M downloads and 1.5K likes in the last 30 days), with community quantizations (fp4, fp8) for smaller GPUs, so you can run it yourself. Most teams still use the API: no GPU to provision or keep warm, no inference ops, and instant access across 12 providers with automatic failover. Self-host when data residency or fixed per-token economics matter most.

Rate limits & reliability

Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff; because DeepSeek V3.2 is served by 12 providers, requests can fail over to a healthy one automatically. See the error-code guide and failover setup.

Related reading

Frequently asked questions