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Jan-v1

Jan-v1

Overview

Jan-v1 is a 4B parameter model based on Qwen3-4B-thinking, designed for reasoning and problem-solving tasks. The model achieves 91.1% accuracy on SimpleQA through model scaling and fine-tuning approaches.

Performance

SimpleQA Benchmark

Jan-v1 demonstrates strong factual question-answering capabilities:

Jan-v1 SimpleQA Performance

At 91.1% accuracy, Jan-v1 outperforms several larger models on SimpleQA, including Perplexity's 70B model. This performance represents effective scaling and fine-tuning for a 4B parameter model.

Chat and Creativity Benchmarks

Jan-v1 has been evaluated on conversational and creative tasks:

Jan-v1 Creativity Benchmarks

These benchmarks (EQBench, CreativeWriting, and IFBench) measure the model's ability to handle conversational nuance, creative expression, and instruction following.

Requirements

  • Memory:
    • Minimum: 8GB RAM (with Q4 quantization)
    • Recommended: 16GB RAM (with Q8 quantization)
  • Hardware: CPU or GPU
  • API Support: OpenAI-compatible at localhost:1337

Using Jan-v1

Quick Start

  1. Download Jan Desktop
  2. Select Jan-v1 from the model list
  3. Start chatting - no additional configuration needed

Demo

Jan-v1 Demo

Deployment Options

Using vLLM:


vllm serve janhq/Jan-v1-4B \
--host 0.0.0.0 \
--port 1234 \
--enable-auto-tool-choice \
--tool-call-parser hermes

Using llama.cpp:


llama-server --model jan-v1.gguf \
--host 0.0.0.0 \
--port 1234 \
--jinja \
--no-context-shift

Recommended Parameters


temperature: 0.6
top_p: 0.95
top_k: 20
min_p: 0.0
max_tokens: 2048

What Jan-v1 Does Well

  • Question Answering: 91.1% accuracy on SimpleQA
  • Reasoning Tasks: Built on thinking-optimized base model
  • Tool Calling: Supports function calling through hermes parser
  • Instruction Following: Reliable response to user instructions

Limitations

  • Model Size: 4B parameters limits complex reasoning compared to larger models
  • Specialized Tasks: Optimized for Q&A and reasoning, not specialized domains
  • Context Window: Standard context limitations apply

Available Formats

GGUF Quantizations

  • Q4_K_M: 2.5 GB - Good balance of size and quality
  • Q5_K_M: 2.89 GB - Better quality, slightly larger
  • Q6_K: 3.31 GB - Near-full quality
  • Q8_0: 4.28 GB - Highest quality quantization

Models Available

Technical Notes

The model includes a system prompt in the chat template by default to match benchmark performance. A vanilla template without system prompt is available in chat_template_raw.jinja.

Community

Jan Nano 128kLucy