AIモデルインテリジェンス

Mistral Saba 24B

groq/saba-24b

提供： groq · ファミリー: mistral · リリース 2025-02-06 · 知識カットオフ: 2024-08

⚠ これはコミュニティのファインチューン / 派生モデルで、ベンダーの公式リリースではありません。

$0.790
入力 / 100万トークン
$0.790
出力 / 100万トークン
33K
コンテキスト長
33K
最大出力

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

機能一覧

✓ ツール呼び出し✗ 推論? 構造化出力✗ 添付✗ オープンウェイト✓ 温度制御
モダリティ: 入力 text · 出力 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding41
  • Tool calling40/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)0/20
  • Provider availability1/10
Agents51
  • Tool calling35/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output47
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume17/20
Cost efficiency57
  • Headline price (log-scaled)57/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)0/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$4.34
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$8.69
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$1.98
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$7.11
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$9.95
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

料金詳細

推奨料金 (提供元): groq · mistral-saba-24b

$0.790
入力
$0.790
出力

1 か所で利用可能

プロバイダープロバイダーモデルID入力 / 1M出力 / 1Mコンテキストリリース日
Groq
groq
mistral-saba-24b$0.790$0.79033K2025-02-06

Frequently asked questions

How much does Mistral Saba 24B cost?

Mistral Saba 24B costs $0.790 per 1M input tokens and $0.790 per 1M output tokens, sourced from groq. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Mistral Saba 24B?

Mistral Saba 24B has a context window of 33K tokens, with a max output of 33K tokens per reply. This is the total combined size of prompt + completion.

Does Mistral Saba 24B support tool calling?

Yes. Mistral Saba 24B supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Mistral Saba 24B support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for Mistral Saba 24B in our data source. Verify with groq's official documentation before relying on it in production.

Can Mistral Saba 24B accept image input?

No. Mistral Saba 24B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Mistral Saba 24B open-weight?

No. Mistral Saba 24B is a proprietary model — only groq (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to Mistral Saba 24B?

If Mistral Saba 24B doesn't fit, consider ALLaM-2-7b, Whisper Large V3, Whisper Large v3 Turbo. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

More groq models

Capability lists this model is in

See also

最終更新：

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.