AXE-BLADE-4B

Precision code specialist. Runs on your hardware. No cloud required.

AXE-BLADE is a distilled reasoning model purpose-built for fast, accurate code generation, refactoring, and tool-calling. It delivers production-quality code output in a 2.3GB package that runs at full speed on consumer hardware.

Part of the AXE Fleet — sovereign AI designed to run entirely on local hardware with zero cloud dependency.

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Model Details

Property	Value
Base Architecture	Qwen3-4B
Training Method	Multi-stage distillation from frontier reasoning models
Parameters	4 billion
Format	GGUF (Q4_K_M)
Download Size	2.3 GB
Context Window	32,768 tokens
Specialization	Code generation, refactoring, tool-calling
Target Hardware	Apple Silicon (M1/M2/M3/M4), CUDA GPUs, CPU

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What Makes BLADE Different

Most small models sacrifice quality for size. BLADE doesn't.

• Thinks before it codes. Step-by-step reasoning produces correct solutions, not plausible-looking ones.
• Native tool-calling. First-class <tool_call> support for agentic workflows, IDE integrations, and autonomous coding pipelines.
• Clean output by default. No filler, no preamble. Just the solution.
• Type-safe and idiomatic. Type annotations, proper naming conventions, and production patterns out of the box.
• Multi-language. Python, TypeScript, Rust, Go, C++, Bash, SQL, and more.

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Benchmarks

Evaluated across our internal fleet of 21 models with 8 sampling profiles:

Metric	Score
Overall Grade	A
Fleet Score	97.5 / 100
Ranking	Top 3 out of 21 models
Code Accuracy	Consistently correct across function-level and module-level tasks
Tool-Call Compliance	Structured output follows schema reliably

BLADE outperforms several 7B and 8B models on code tasks while using less than half the memory.

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Quick Start

Ollama (Recommended)

ollama run axe-blade-4b

llama.cpp

./llama-cli -m axe-blade-4b.gguf \
  -p "Write a Python async web scraper with proper error handling" \
  -n 1024 --temp 0.7

Python (llama-cpp-python)

from llama_cpp import Llama

llm = Llama(model_path="axe-blade-4b.gguf", n_ctx=8192, n_gpu_layers=-1)

response = llm.create_chat_completion(
    messages=[
        {"role": "system", "content": "You are a precise code assistant."},
        {"role": "user", "content": "Write a Redis-backed rate limiter in Python"}
    ],
    temperature=0.7,
    max_tokens=1024
)
print(response["choices"][0]["message"]["content"])

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Sample Output

Prompt: "Write a function to validate email addresses with proper regex"

BLADE Response:

import re
from typing import Optional

def validate_email(email: str) -> Optional[str]:
    """Validate an email address. Returns normalized email or None."""
    pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
    email = email.strip().lower()
    if re.match(pattern, email):
        return email
    return None

No boilerplate. No explanation you didn't ask for. Just working code.

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Hardware Requirements

Setup	RAM Required	Speed
Apple Silicon (M1+)	3 GB	~40 tok/s
NVIDIA GPU (8GB+)	3 GB VRAM	~50 tok/s
CPU-only	4 GB RAM	~8 tok/s

BLADE fits comfortably alongside your other applications. Run AI-assisted coding without sending your code to any cloud.

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Use Cases

• Local coding assistant — IDE integration without API keys or subscriptions
• Agentic pipelines — Tool-calling support for autonomous code review, refactoring, and generation
• Air-gapped environments — Full capability with zero network access
• Edge deployment — Small enough for embedded systems and field devices
• CI/CD integration — Automated code review and generation in your pipeline

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The AXE Fleet

AXE Technology builds sovereign AI systems. Local models that run on your hardware, no cloud required.

The fleet includes specialized models for code, research, strategy, security, and general intelligence. Each model is distilled and optimized for its domain, then benchmarked against the full fleet to ensure quality.

• Website: axe.onl
• Mission: Free intelligence. No gatekeepers. No subscriptions.

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License

Apache 2.0 — use it however you want, commercially or otherwise.

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Citation

@misc{axe-blade-4b,
  title={AXE-BLADE-4B: Distilled Code Specialist},
  author={AXE Technology},
  year={2026},
  url={https://huggingface.co/axyn/axe-blade-4b}
}