Nova Premier 1.0 API1M context

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

What is Nova Premier 1.0?

Amazon Nova Premier is the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models.

Nova Premier 1.0 on the release timeline

Nova Premier 1.0 pricing

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

On output price, Nova Premier 1.0 is cheaper than 13% of the 309 models in the catalog.

What Nova Premier 1.0 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.

Nova Premier 1.0 vs alternatives

When not to use Nova Premier 1.0

• It is premium-priced (output cheaper than only 13% of the catalog) — for routine work a cheaper model likely does the job.
• It is served by a single provider, so there is less failover headroom during an outage.

Specs

How to call Nova Premier 1.0

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="amazon/nova-premier-v1",
    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":"amazon/nova-premier-v1","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: "amazon/nova-premier-v1",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);

The same key routes Nova Premier 1.0 and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.

Prompting tips for Nova Premier 1.0

• 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 — Nova Premier 1.0 follows concrete instructions better than abstract ones.
• 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.
• It reads images. Send image parts alongside your text and ask for specific outputs (named JSON fields, a table, "what changed") rather than "describe this".
• Give it real tools. Pass a tools=[...] schema instead of asking it to "pretend" — let Nova Premier 1.0 emit tool calls, execute them, and feed results back for the next turn.
• It's premium — spend where it counts. Route easy calls to a cheaper model and reserve Nova Premier 1.0 for the hard reasoning; trim system prompts and few-shot examples that don't move the result.

Tips are derived from Nova Premier 1.0's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Nova Premier 1.0

Popular open-source frameworks and agents to build with Nova Premier 1.0 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 Nova Premier 1.0

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → amazon/nova-premier-v1. 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. See the error-code guide and failover setup.

Related reading

Frequently asked questions