Mistral: Saba

Public pricingIntelligence 79/100Medium memory도구 활용

Mistral: Saba은 일반 대화, 분석, 운영 환경에 맞춘 텍스트 모델입니다. 낮은 지연과 효율적 추론, 33K tokens의 컨텍스트, 저비용 특성을 결합해 general chat, analysis, and production workloads에서 안정적인 작업을 돕습니다. 특히 지연, 비용, 처리량가 중요한 경우에 잘 맞으며, 안정적인 출력, 유연한 배포, 확장성을 중시하는 팀에 실용적입니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다.

Input

$0.20/1M

Output

$0.60/1M

Cached

$0.02/1M

Batch

$0.10/1M

Calculate your Saba bill.

Set your workload — see cost at your exact volume.

What would Saba cost you?

Adjust the workload to see your monthly bill.

Conversations per month50,000

1,00010,00050,000250,0001M10M

Input length

Output length

Repeated questions?

Replies can wait a few hours (batch discount)

Technical specifications

Saba at a glance.

Memory

32,768

tokens

Max reply

8,192

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

mistral

Released

Feb 2025

Training cutoff

Oct 2024

Availability

Public pricing

Status

active

What it can do

Capabilities & limits.

Understands images
Deep step-by-step thinking
Uses tools / calls functions
Strict JSON output
Streams replies
Fine-tunable on your data

When to pick Saba

Agentic workflows that call tools or APIs.
High-volume workloads where unit cost matters.

When to look elsewhere

Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Saba — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Saba costs roughly $39 per month. Input is $0.20 /1M tokens and output is $0.60 /1M tokens.

Saba has a 32,768-token context window (medium memory — a long report or a codebase file). That means you can fit about 6,144 words of input and history in a single call.

Beyond text generation, Saba supports calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.

Saba was released in February 2025, with training data cut off around October 2024.

Models in a similar class include Ministral 3 14B 2512, Ministral 3 8B 2512, Mistral Small 4. The "Similar models" section below this FAQ links into each.

Still unsure?

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