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vLLM/recipes/models/IFM/Jais-3-0.9B.yaml
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2026-10-17 09:14:36 +00:00

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meta:
title: "Jais-3-0.9B"
slug: "jais-3-0.9b"
provider: "IFM"
description: "Compact dense model for mathematics, code, instruction following, and STEM tasks"
date_added: 2026-10-05
date_updated: 2026-10-05
tasks:
- text
performance_headline: "1.08B stored parameters including embeddings, with 131K context and native K2-Horizon parsing"
related_recipes:
- "IFM/Jais-3-3.7B"
hardware:
h200: verified
model:
model_id: "IFM/Jais-3-0.9B"
architecture: dense
parameter_count: "1.08B"
active_parameters: "1.08B"
context_length: 131072
base_args:
- "--trust-remote-code"
- "--chat-template-content-format"
- "string"
- "--dtype"
- "bfloat16"
- "--max-model-len"
- "131072"
- "--gpu-memory-utilization"
- "0.85"
base_env: {}
features:
reasoning:
description: "Extract Jais-3 reasoning into message.reasoning"
args: ["--reasoning-parser", "k2_horizon"]
tool_calling:
description: "Enable automatic tool choice with the K2-Horizon parser"
args: ["--enable-auto-tool-choice", "--tool-call-parser", "k2_horizon"]
variants:
default:
precision: bf16
vram_minimum_gb: 3
description: "Released BF16 checkpoint; the command starts at an 8K runtime context"
compatible_strategies:
- single_node_tp
- multi_node_tp
- multi_node_tp_pp
hardware_overrides: {}
guide: |
## Overview
Jais-3-0.9B is a compact dense model in the IFM Jais-3
family, with 1.08B stored parameters including embeddings and a 131,072-token
context window.
Jais-3 is an open-weight IFM model family built for transparent
foundation-model research, staged checkpoint analysis, and practical
deployment. The series spans compact dense models such as Jais-3-0.9B
for local experimentation, dense mid-size and large models for high-quality
research workloads, and mixture-of-expert (MoE) models for higher-capacity
serving.
## Launch Commands
Jais-3-0.9B's `config.json` already enables YaRN, so the full 131,072-token context needs no RoPE override.
```bash
vllm serve IFM/Jais-3-0.9B \
--trust-remote-code \
--chat-template-content-format string \
--dtype bfloat16 \
--max-model-len 131072 \
--gpu-memory-utilization 0.85 \
--reasoning-parser k2_horizon \
--enable-auto-tool-choice \
--tool-call-parser k2_horizon
```
Lower `--max-model-len` (e.g. 8192) to reduce KV-cache memory.
## Client usage
```python
from openai import OpenAI
client = OpenAI(
api_key="EMPTY", base_url="http://localhost:8000/v1", timeout=3600
)
resp = client.chat.completions.create(
model="IFM/Jais-3-0.9B",
messages=[{"role": "user", "content": "لدينا عددان مجموعهما 50 وحاصل ضربهما 600. ما هما العددان؟ اشرح خطوات الحل."}],
temperature=1.0, top_p=0.95, max_tokens=2048,
)
print(resp.choices[0].message.content)
```
### Thinking modes
The model supports selectable thinking through `chat_template_kwargs`, per
request or server-wide via `--default-chat-template-kwargs`:
- `{"reasoning_effort": "high"}` — full thinking (default).
- `{"reasoning_effort": "low"}` — no thinking.
## References
- [IFM/Jais-3-0.9B on Hugging Face](https://huggingface.co/IFM/Jais-3-0.9B)
- [Jais 3 Collection](https://huggingface.co/collections/IFM/jais-3)