Jan-v1

OverviewCopy Anchor Link

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.

PerformanceCopy Anchor Link

SimpleQA BenchmarkCopy Anchor Link

Jan-v1 demonstrates strong factual question-answering capabilities:

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 BenchmarksCopy Anchor Link

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

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

RequirementsCopy Anchor Link

• 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-v1Copy Anchor Link

Quick StartCopy Anchor Link

1. Download Jan Desktop
2. Click Open in Jan above, or open the Hub and search for Jan-v1
3. Choose a variant that fits your hardware, then click Download
4. Once downloaded, select Jan-v1 from the model selector in any chat
5. Start chatting - no additional configuration needed

DemoCopy Anchor Link

Deployment OptionsCopy Anchor Link

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 ParametersCopy Anchor Link

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

What Jan-v1 Does WellCopy Anchor Link

• 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

LimitationsCopy Anchor Link

• 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 FormatsCopy Anchor Link

GGUF QuantizationsCopy Anchor Link

• 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 AvailableCopy Anchor Link

• Jan-v1 on Hugging Face
• Jan-v1 GGUF on Hugging Face

Technical NotesCopy Anchor Link

CommunityCopy Anchor Link

• Discussions: HuggingFace Community
• Support: Available through Jan App at jan.ai