GPT-4 1106 Preview style="color:var(--t2);font-weight:400">API8K context

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

What is GPT-4 1106 Preview?

OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous models due to its broader general knowledge and advanced reasoning...

GPT-4 on the release timeline

GPT-4 pricing

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

On output price, GPT-4 is cheaper than 3% of the 309 models in the catalog. It is served by 2 providers; the best combined rate at our last snapshot was ≈ $30.00 / $60.00 per 1M via OpenAI.

What GPT-4 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.

GPT-4 vs alternatives

When not to use GPT-4

• It is premium-priced (output cheaper than only 3% of the catalog) — for routine work a cheaper model likely does the job.
• Its 8K context is small — not ideal for large documents or big codebases.

Specs

How to call GPT-4

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="openai/gpt-4",
    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":"openai/gpt-4","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: "openai/gpt-4",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes GPT-4 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for GPT-4

• Be explicit and show the shape of the answer. Spell out format, tone and constraints up front, and include one short example of the output you want — GPT-4 follows concrete instructions better than abstract ones.
• Give it real tools. Pass a tools=[...] schema instead of asking it to "pretend" — let GPT-4 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.
• It's premium — spend where it counts. Route easy calls to a cheaper model and reserve GPT-4 for the hard reasoning; trim system prompts and few-shot examples that don't move the result.
• Use the system role for rules. Put persistent instructions in the system message and keep user turns task-specific; pair with structured outputs for reliable automation.

Tips are derived from GPT-4's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for GPT-4

Popular open-source frameworks and agents to build with GPT-4 over the API — star counts pulled from GitHub (July 2026).

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

Migrating to GPT-4

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → openai/gpt-4. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.

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 GPT-4 is served by 2 providers, requests can fail over to a healthy one automatically. See the error-code guide and failover setup.

Related reading

Frequently asked questions