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vLLM/recipes/models/IFM/Jais-3-32B.yaml
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meta:
title: "Jais-3-32B"
slug: "jais-3-32b"
provider: "IFM"
description: "Dense long-context model for reasoning research and high-capacity serving"
date_added: 2026-10-05
date_updated: 2026-10-05
tasks: [text]
performance_headline: "34.78B stored parameters including embeddings, with native vLLM execution and up to 512K context"
related_recipes: ["IFM/Jais-3-7B", "IFM/Jais-3-MoVA-36B-A4B"]
hardware:
h200: verified
model:
model_id: "IFM/Jais-3-32B"
architecture: dense
parameter_count: "34.78B"
active_parameters: "34.78B"
context_length: 524288
base_args: ["--trust-remote-code", "--chat-template-content-format", "string", "--dtype", "bfloat16"]
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: 84
description: "BF16 serving runtime with native vLLM execution"
compatible_strategies: [single_node_tp, multi_node_tp, multi_node_tp_pp]
hardware_overrides: {}
strategy_overrides:
single_node_tp:
tp: 2
guide: |
## Overview
Jais-3-32B is a large dense model in the IFM Jais-3 family,
with 34.78B stored parameters including embeddings and support for up to
524,288 tokens of context.
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 for local experimentation,
dense mid-size and large models such as Jais-3-32B for high-quality
research workloads, and mixture-of-expert (MoE) models for higher-capacity
serving.
## Launch Commands
```bash
vllm serve IFM/Jais-3-32B \
--tensor-parallel-size 2 \
--trust-remote-code \
--chat-template-content-format string \
--dtype bfloat16 \
--reasoning-parser k2_horizon \
--enable-auto-tool-choice \
--tool-call-parser k2_horizon
```
## 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-3-32B",
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-3-32B on Hugging Face](https://huggingface.co/IFM/Jais-3-32B)
- [Jais 3 Collection](https://huggingface.co/collections/IFM/jais-3)