Saba API33K context

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

What is Saba?

Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional...

Saba on the release timeline

Saba pricing

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

On output price, Saba is cheaper than 72% of the 309 models in the catalog.

What Saba 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.

Saba vs alternatives

When not to use Saba

• It is served by a single provider, so there is less failover headroom during an outage.

Specs

How to call Saba

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

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

Prompting tips for Saba

• 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 — Saba follows concrete instructions better than abstract ones.
• Give it real tools. Pass a tools=[...] schema instead of asking it to "pretend" — let Saba 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 Saba's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.

Open-source tools for Saba

Popular open-source frameworks and agents to build with Saba 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 Saba

Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → mistralai/mistral-saba. 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