meta:
  title: "Jais-3-MoVA-36B-A4B"
  slug: "jais-3-mova-36b-a4b"
  provider: "IFM"
  description: "Sparse MoVA and MoE long-context model for research and production-style serving experiments"
  date_added: 2026-10-05
  date_updated: 2026-10-05
  tasks: [text]
  performance_headline: "37.44B stored parameters including embeddings / 5.95B active parameters per token"
  related_recipes: ["IFM/Jais-3-32B", "IFM/Jais-3-375B-A23B"]
  hardware:
    h200: verified
model:
  model_id: "IFM/Jais-3-MoVA-36B-A4B"
  architecture: moe
  parameter_count: "37.44B"
  active_parameters: "5.95B"
  context_length: 524288
  base_args: ["--trust-remote-code", "--chat-template-content-format", "string", "--dtype", "bfloat16", "--enable-expert-parallel"]
  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: 90
    description: "BF16 serving runtime with native vLLM execution"
compatible_strategies: [single_node_tep, multi_node_tep, multi_node_tp_pp]
default_strategy: single_node_tep
hardware_overrides: {}
strategy_overrides:
  single_node_tep:
    tp: 2
guide: |
  ## Overview

  Jais-3-MoVA-36B-A4B is a mixture-of-expert (MoE) model in the IFM Jais-3
  family. It combines MoVA attention and MoE layers, with 37.44B stored parameters
  including embeddings, 5.95B active parameters per token, 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 for high-quality research workloads, and
  mixture-of-expert (MoE) models such as Jais-3-MoVA-36B-A4B for higher-capacity
  serving.

  ## Launch Commands

  ```bash
  vllm serve IFM/Jais-3-MoVA-36B-A4B \
    --tensor-parallel-size 2 \
    --trust-remote-code \
    --chat-template-content-format string \
    --dtype bfloat16 \
    --enable-expert-parallel \
    --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-MoVA-36B-A4B",
      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-MoVA-36B-A4B on Hugging Face](https://huggingface.co/IFM/Jais-3-MoVA-36B-A4B)
  - [Jais 3 Collection](https://huggingface.co/collections/IFM/jais-3)