Saba
Open weightToolsMistral · Released February 2025 · Knowledge cutoff September 2024
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.
It belongs to Mistral's catalog, which spans Medium and Large (capability), Small and Ministral (efficiency) and dedicated code and audio models, all with European data-residency roots.
Facts and pricing
- Provider
- Mistral
- Context window
- 33K tokens
- Input price
- 2.4 credits / 1M tokens ($0.20 raw)
- Output price
- 7.2 credits / 1M tokens ($0.60 raw)
- Vision (image input)
- No
- Tool calling
- Yes
- Extended reasoning
- No
Credits are what Zeplik bills: 1 credit = $0.10, computed from the raw provider rate with a 1.20x margin. Raw prices shown per 1M tokens.
Try Saba now
What Saba is best for
- Everyday chat and drafting on an open-weight model with transparent lineage
- Tool use and agents: reliably calls functions, so it can search, run skills and drive workflows
Example prompts
Prompts that suit a open weight model like Saba:
- Draft a project update from these rough notes
- Explain how HTTPS works to a curious teenager
- Turn this list of features into a changelog entry
- Brainstorm objections to this proposal and how to answer them
Mistral family
| Model | Context | Input cr/M | Output cr/M | Released |
|---|---|---|---|---|
| Mistral Large 4 | 1.0M | 8.4 | 25.2 | October 2026 |
| Mistral Medium 3.5 | 262K | 18.0 | 90.0 | April 2026 |
| Mistral Medium 3.5 (batch) | 262K | 9.0 | 45.0 | April 2026 |
| Mistral Small 4 | 262K | 1.8 | 7.2 | March 2026 |
| Devstral 2 2512 | 262K | 4.8 | 24.0 | December 2025 |
| Ministral 3 14B 2512 | 262K | 2.4 | 2.4 | December 2025 |
| Ministral 3 8B 2512 | 262K | 1.8 | 1.8 | December 2025 |
| Ministral 3 3B 2512 | 131K | 1.2 | 1.2 | December 2025 |
| Mistral Large 3 2512 | 262K | 6.0 | 18.0 | December 2025 |
| Voxtral Small 24B 2507 | 33K | 1.2 | 3.6 | October 2025 |
Model comparisons
- Llama 4 Maverick vs Mistral Medium 3.5
- GPT-5.6 Luna vs Mistral Small 4
- Gemini 3.5 Flash vs Mistral Small 4
- Kimi K2.7 Code vs Codestral 2508
Frequently asked questions
- What is Saba?
- Saba is an AI model by Mistral. 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.
- How much does Saba cost on Zeplik?
- Input tokens cost 2.4 credits per million and output tokens 7.2 credits per million (1 credit = $0.10; the raw provider rates are $0.20 and $0.60 per million). New accounts start with free credits.
- How long can a conversation with Saba be?
- Saba has a 33K-token context window (32,768 tokens), which covers the conversation plus any documents you attach.
- Does Saba support images and tools?
- Saba is text-only and supports tool calling.
Related models
Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads.
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI.
Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI.
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system.
Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window.
The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart.
More you can do with Saba
- 468 AI skillsReady-to-run expert methods for writing, data, code and more, each running on Saba or any model you pick.
- 997 integrationsConnect Gmail, Slack, GitHub, Notion and hundreds more so the assistant can work in your apps.
- Simple pricingPlus, Pro and Max plans with a monthly credit allowance that works across every model.