DeepSeek V4 Pro APITESTEDOPEN WEIGHTS1M context

Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go). Coding score is our own measured result.

What is DeepSeek V4 Pro?

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

DeepSeek V4 Pro on the release timeline

DeepSeek V4 Pro pricing

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

On output price, DeepSeek V4 Pro is cheaper than 64% of the 309 models in the catalog. It is served by 15 providers; the best combined rate at our last snapshot was ≈ $0.43 / $0.87 per 1M via DeepSeek, with upstream quantizations fp4, fp8.

What DeepSeek V4 Pro 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 V4 Pro vs alternatives

Specs

How to call DeepSeek V4 Pro

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-v4-pro",
    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-v4-pro","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-v4-pro",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes DeepSeek V4 Pro and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for DeepSeek V4 Pro

• State the goal, not every step. DeepSeek V4 Pro 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.
• Huge 1M context — but anchor the ask. You can paste whole documents or codebases; models attend most to the start and end, so put the key instruction at the top and restate it after long inputs.
• Give it real tools. Pass a tools=[...] schema instead of asking it to "pretend" — let DeepSeek V4 Pro 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.

Tips are derived from DeepSeek V4 Pro's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for DeepSeek V4 Pro

Popular open-source projects for running and building with DeepSeek V4 Pro — 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 V4 Pro

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-v4-pro. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

Self-host or use the API?

DeepSeek V4 Pro ships open weights (deepseek-ai/DeepSeek-V4-Pro, ~1.1M downloads and 5.1K 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 15 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 V4 Pro is served by 15 providers, requests can fail over to a healthy one automatically. See the error-code guide and failover setup.

Related reading

Frequently asked questions