Mako-8B Operator is a fine-tuned language model purpose-built for autonomous on-chain inference on Base. She powers the chat experience at deepmako.com — a crypto-native AI platform where users interact with Mako using $MAKO token credits.

Mako isn't a generic assistant. She's a character with a distinct voice: sharp, unfiltered, lowercase, and real. She uses tools autonomously, chains multi-step research, and operates natively in the Base L2 ecosystem.

Model Details


Developer	DeepMako
Base Model	Qwen 2.5 7B Instruct
Parameters	8B
Format	GGUF (Q8_0)
File	`mako-7b-operator-v0.1.Q8_0.gguf`
Size	~8.1 GB
Context Window	4,096 tokens
Tool Calling	Native (Qwen chat template)
Chat Template	ChatML (`<\|im_start\|>`, `<\|im_end\|>`)

Capabilities

🦈 Distinct Personality

Mako talks lowercase, curses naturally, and doesn't do the helpful-assistant act. She matches your energy — flirts if you flirt, roasts if you're being dumb, and gives it to you straight when you're being real.

🔧 Native Tool Calling

Mako decides when to call tools without being told. Available tools include:

web_search — Real-time internet search
web_extract — Read full page content from URLs
read_tweet — Parse Twitter/X posts
get_balance — Check ETH/token balances on Base
get_gas — Live gas prices on Base L2
resolve_ens — ENS name resolution

⛓️ Tool Chaining

Mako chains tools automatically — e.g., searching → extracting the top result → summarizing. Up to 4 tool rounds per request.

🔵 Base Chain Intelligence

Deep understanding of ERC standards, smart contract patterns, bridging mechanics, account abstraction (ERC-4337), and Base-specific architecture.

Inference Parameters

yaml

temperature: 0.9
top_k: 40
top_p: 0.92
min_p: 0.05
repeat_penalty: 1.05
num_ctx: 4096
stop: ["<|im_end|>", "<|endoftext|>"]

Usage

With llama.cpp

bash

./llama-server -m mako-7b-operator-v0.1.Q8_0.gguf \
  --ctx-size 4096 \
  --port 8080

With Ollama

dockerfile

FROM mako-7b-operator-v0.1.Q8_0.gguf

PARAMETER stop <|im_end|>
PARAMETER stop <|endoftext|>
PARAMETER temperature 0.9
PARAMETER top_k 40
PARAMETER top_p 0.92
PARAMETER min_p 0.05
PARAMETER num_ctx 4096
PARAMETER repeat_penalty 1.05

bash

ollama create mako -f Modelfile
ollama run mako

API (OpenAI-compatible)

python

from openai import OpenAI

client = OpenAI(
    base_url="https://your-endpoint/v1",
    api_key="your-key"
)

response = client.chat.completions.create(
    model="mako-8b-operator",
    messages=[
        {"role": "user", "content": "what's the gas price on base right now"}
    ],
    temperature=0.9
)

Training

Fine-tuned on curated conversational data emphasizing:

Persona consistency — Maintaining Mako's character voice across all interactions
Tool-use judgment — Knowing when to call tools vs. answer directly
Domain knowledge — Base chain, DeFi, smart contracts, and crypto culture
Concise dialogue — Natural, to-the-point conversation patterns

Intended Use

Mako-8B Operator is designed to power the inference backend at deepmako.com. It is optimized for conversational AI with tool-calling capabilities in the crypto/Base ecosystem.

Limitations

Mako uses profanity and unfiltered language by design — this is not a safety-aligned assistant model
Knowledge cutoff inherited from the base model's training data
Optimized for English only
Best results with the provided system prompt and tool definitions

deepmako/Mako-8B-Operator

Mako-8B Operator

Overview