Crypto Basics

Types of Stablecoins: A Complete Guide for 2025

Discover the types of stablecoins—fiat-backed, crypto-backed, algorithmic, and commodity-based. Learn how they work, their pros and cons, and which is best for your crypto strategy in 2025.
Token Metrics Team
8 min
MIN

The cryptocurrency market is famous for volatility—Bitcoin can swing by thousands of dollars in a day, and altcoins can rise or crash in hours. But what if you need price stability? That’s where stablecoins come in.

Stablecoins are digital currencies pegged to stable assets like the US dollar, gold, or even algorithmically maintained price levels. They bridge the gap between the speed and efficiency of blockchain technology and the reliability of traditional money.

As of 2025, stablecoins account for over $140 billion in circulating supply, making them essential for traders, investors, and decentralized finance (DeFi) users. But not all stablecoins are the same—different types use different mechanisms to maintain their stability, each with unique pros and cons.

In this guide, we’ll break down the types of stablecoins, how they work, their risks, and which might be best for your needs.

What Are Stablecoins?

A stablecoin is a cryptocurrency designed to maintain a stable value by pegging its price to a reference asset. Most stablecoins are pegged to fiat currencies like the U.S. dollar (e.g., 1 USDT ≈ $1), but some track commodities (like gold) or are algorithmically balanced to hold value.

They are widely used for:

  • Trading: Moving quickly in and out of volatile assets.
  • DeFi: Providing liquidity, borrowing, and earning yields.
  • Remittances: Sending low-cost, fast cross-border payments.
  • Hedging: Protecting against crypto market volatility.

Types of Stablecoins

There are four main types of stablecoins:

  1. Fiat‑Collateralized Stablecoins
  2. Crypto‑Collateralized Stablecoins
  3. Algorithmic (Non‑Collateralized) Stablecoins
  4. Commodity‑Backed Stablecoins

Each has a different method of maintaining its peg. Let’s break them down.

1. Fiat‑Collateralized Stablecoins

Definition:
These are backed 1:1 by traditional currencies like the U.S. dollar, euro, or yen. For every stablecoin issued, an equivalent amount of fiat is held in reserve by a trusted custodian.

How They Work:
If you buy 1 USDC, Circle (its issuer) holds $1 in a regulated bank account or short-term U.S. Treasury securities. When you redeem that stablecoin, the issuer sends you the equivalent amount in fiat and burns the coin.

Examples:

  • Tether (USDT) – Largest stablecoin by market cap; widely used on exchanges.
  • USD Coin (USDC) – Issued by Circle, fully regulated and audited.
  • TrueUSD (TUSD) – Offers real-time attestation of reserves.
  • PayPal USD (PYUSD) – Launched by PayPal for payments and DeFi.

Pros:

  • High stability – Pegged directly to fiat.
  • Transparent – Many provide audits and attestations.
  • Easy adoption – Ideal for traders, merchants, and payment platforms.

Cons:

  • Centralization – Custodians control reserves and can freeze accounts.
  • Regulatory risks – Subject to government oversight.
  • Less transparency for some issuers – (e.g., Tether faced scrutiny over its reserves).

2. Crypto‑Collateralized Stablecoins

Definition:
These are backed by cryptocurrencies like Ethereum or Bitcoin instead of fiat. Because crypto is volatile, these stablecoins are overcollateralized (e.g., $150 in ETH backs $100 in stablecoins).

How They Work:
When you mint a crypto-backed stablecoin like DAI, you deposit collateral (e.g., ETH) into a smart contract. If the collateral value drops too much, the contract automatically liquidates some assets to maintain the peg.

Examples:

  • DAI – Issued by MakerDAO, backed by ETH, USDC, and other assets.


  • sUSD – A synthetic USD issued by Synthetix.
  • MIM (Magic Internet Money) – Collateralized by multiple crypto assets.

Pros:

  • Decentralized – No single company controls reserves.
  • Transparent – All collateral balances are viewable on-chain.
  • Resistant to censorship – Issuers can’t freeze accounts.

Cons:

  • Volatility risk – Collateral can lose value quickly, requiring liquidations.
  • Overcollateralization – Ties up more capital than fiat-backed options.
  • Complexity – Requires understanding of DeFi mechanics.

3. Algorithmic (Non‑Collateralized) Stablecoins

Definition:
These don’t use physical reserves. Instead, they maintain their peg via algorithmic supply adjustments—minting or burning tokens to balance price around $1.

How They Work:
If demand increases and the price rises above $1, the protocol mints more coins. If it falls below $1, the protocol burns coins or incentivizes users to buy them back.

Examples:

  • Ampleforth (AMPL) – Elastic supply adjusts daily.
  • UST (TerraUSD) – Infamously collapsed in 2022 after its peg broke.
  • Frax (FRAX) – Uses a hybrid model: partly collateralized, partly algorithmic.

Pros:

  • Highly capital-efficient – Doesn’t require large reserves.
  • Decentralized – Often governed by smart contracts and DAOs.

Cons:

  • Peg instability – Prone to “death spirals” when market confidence drops.
  • Complex mechanisms – Harder for average users to understand.
  • History of failures – UST/LUNA crash eroded trust in algorithmic coins.

4. Commodity‑Backed Stablecoins

Definition:
These stablecoins are pegged to commodities like gold, silver, or oil, giving them intrinsic value beyond fiat.

How They Work:
For every coin issued, an equivalent amount of the commodity is held in a secure vault. For example, owning 1 PAX Gold (PAXG) means you own 1 troy ounce of physical gold stored by the issuer.

Examples:

  • PAX Gold (PAXG) – Backed by physical gold.


  • Tether Gold (XAUT) – Gold-backed token from Tether.
  • Digix Gold (DGX) – Pegged to gold bars in Singapore vaults.

Pros:

  • Hedge against inflation – Commodities like gold retain value during economic uncertainty.
  • Diversification – Offers exposure to both crypto and commodities.

Cons:

  • Low liquidity – Less widely used than fiat-backed stablecoins.
  • Storage & audit challenges – Requires trust in the issuer to maintain reserves.

Why Do Stablecoins Matter?

Stablecoins are the backbone of DeFi and crypto trading.

  • Trading & arbitrage: They provide a quick way to exit volatile positions without converting back to fiat.
  • Cross-border payments: Cheaper and faster than SWIFT or remittance services.
  • DeFi participation: Essential for lending, borrowing, yield farming, and liquidity pools.
  • On-ramp/off-ramp: They simplify converting between traditional finance and blockchain.

Which Type of Stablecoin Should You Use?

If you want simplicity & security: Go with fiat-backed coins like USDC or PYUSD.

If you value decentralization: Choose crypto-collateralized options like DAI.

If you’re comfortable with high risk: Explore algorithmic models like FRAX (but beware of peg risks).

If you want inflation protection: Consider commodity-backed coins like PAXG.

Key Risks of Stablecoins

  • Regulation: Governments are increasing oversight of fiat-backed coins.
  • Centralization: Some issuers can freeze funds or blacklist wallets.
  • Smart contract risks: DeFi-based stablecoins can suffer from bugs or exploits.
  • Peg breaks: Algorithmic models are especially vulnerable to confidence loss.

The Future of Stablecoins

In 2025, stablecoins are evolving to meet regulatory and market demands:

  • Central Bank Digital Currencies (CBDCs): Governments are issuing digital dollars and euros, potentially competing with stablecoins.
  • Regulated issuers: Projects like USDC are working closely with regulators to ensure compliance.
  • Hybrid models: Combining fiat and algorithmic elements (e.g., Frax) to enhance stability.

As DeFi expands and global adoption grows, stablecoins will remain at the heart of crypto finance.

Final Thoughts

Stablecoins are more than just “digital dollars.” They’re a critical bridge between traditional finance and blockchain innovation.

  • Fiat-backed stablecoins bring stability and ease of use.
  • Crypto-collateralized ones offer transparency and decentralization.
  • Algorithmic models push innovation but carry higher risks.
  • Commodity-backed coins provide a hedge against inflation and diversify exposure.

Choosing the right type depends on your risk tolerance, use case, and trust level. Whether for trading, saving, or participating in DeFi, understanding the types of stablecoins can help you navigate the crypto ecosystem with confidence.

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Token Metrics Team

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Fartcoin:

The green and red dots on the following Fartcoin price chart represent the bullish and bearish market signals, respectively. Since Nov 26, 2024, Token Metrics AI has given 4 trading signals for Fartcoin. Let’s analyze each signal separately.

The Fartcoin chart above displays green and red dots that mark bullish and bearish signals from the Token Metrics AI, respectively. Over the last six months — starting November 26, 2024 — our system produced four significant trade signals for Fartcoin. Let’s evaluate them one by one.

The first major signal was bullish on November 26, 2024, when Fartcoin was trading at $0.29. This signal preceded a massive run-up, with the price topping out at $2.49. That’s an astounding 758% gain — all captured within just under two months. It’s one of the most powerful validations of the AI model’s ability to anticipate momentum early.

Following that rally, a bearish signal was triggered on January 26, 2025, just before the market corrected. Fartcoin retraced sharply, plunging 74.76% from the highs. Traders who acted on this bearish alert could have avoided substantial drawdowns — or even profited through short-side exposure.

On March 25, 2025, the AI turned bullish again, as Fartcoin traded near $0.53. Over the next several weeks, the token surged to $1.58, a 198% rally. Again, the AI proved its ability to detect upward momentum early.

Most recently, on June 1, 2025, Token Metrics AI flipped bearish once again. The current Trader Grade of 24.34 reinforces this view. For now, the system warns of weakness in the memecoin market — a trend that appears to be playing out in real-time.

Across all four trades, the AI captured both the explosive upside and protected traders from steep corrections — a rare feat in the volatile world of meme tokens.

Bittensor

Next, we examine Bittensor, the native asset of the decentralized AI Layer 1 network. Over the last six months, Token Metrics AI produced five key signals — and the results were a mixed bag but still largely insightful.

In December 2024, the AI turned bearish around $510, which preceded a sharp decline to $314 by February — a 38.4% drawdown. This alert helped traders sidestep a brutal correction during a high-volatility period.

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The third signal marked a solid win: Bittensor dropped from $327 to $182.9 following the bearish call — another 44% drop captured in advance.

In April 2025, momentum returned. The AI issued a bullish alert on April 19, with TAO at $281. By the end of May, the token had rallied to over $474, resulting in a 68.6% gain — one of the best performing bullish signals in the dataset.

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Finally, we analyze the AI’s predictive power for Ethereum, the second-largest crypto by market cap. Over the six-month window, Token Metrics AI made three major calls — and each one captured critical pivots in ETH’s price.

On November 7, 2024, a green dot (bullish) appeared when ETH was priced at $2,880. The price then surged to $4,030 in less than 40 days, marking a 40% gain. For ETH, such a move is substantial and was well-timed.

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Whether you’re a trader looking to time the next big altcoin rally or an investor managing downside in turbulent markets, Token Metrics AI signals — available via the fastest crypto API — offer a powerful edge.

Backtesting Token Metrics AI across memecoins, AI narratives, and Ethereum shows consistent results: early identification of breakouts, timely exit signals, and minimized risk exposure. While no model is perfect, the six-month history reveals a tool capable of delivering real value — especially when used alongside sound risk management.

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As the crypto ecosystem rapidly matures, developers, quant traders, and crypto-native startups are relying more than ever on high-quality APIs to build data-powered applications. Whether you're crafting a trading bot, developing a crypto research platform, or launching a GPT agent for market analysis, choosing the right API is critical.

Two names dominate the space in 2025: CoinGecko and Token Metrics. But while both offer access to market data, they serve fundamentally different purposes. CoinGecko is a trusted source for market-wide token listings and exchange metadata. Token Metrics, on the other hand, delivers AI-powered intelligence for predictive analytics and decision-making.

Let’s break down how they compare—and why the Token Metrics API is the superior choice for advanced, insight-driven builders.

🧠 AI Intelligence: Token Metrics Leads the Pack

At the core of Token Metrics is machine learning and natural language processing. It’s not just a data feed. It’s an AI that interprets the market.

Features exclusive to Token Metrics API:

  • Trader Grade (0–100) – Short-term momentum score based on volume, volatility, and technicals
  • Investor Grade (0–100) – Long-term asset quality score using fundamentals, community metrics, liquidity, and funding
  • Bullish/Bearish AI Signals – Real-time alerts based on over 80 weighted indicators
  • Sector-Based Smart Indices – Curated index sets grouped by theme (AI, DeFi, Gaming, RWA, etc.)
  • Sentiment Scores – Derived from social and news data using NLP
  • LLM-Friendly AI Reports – Structured, API-returned GPT summaries per token
  • Conversational Agent Access – GPT-based assistant that queries the API using natural language

In contrast, CoinGecko is primarily a token and exchange aggregator. It offers static data: price, volume, market cap, supply, etc. It’s incredibly useful for basic info—but it lacks context or predictive modeling.

Winner: Token Metrics — The only crypto API built for AI-native applications and intelligent automation.

🔍 Data Depth & Coverage

While CoinGecko covers more tokens and more exchanges, Token Metrics focuses on providing actionable insights rather than exhaustively listing everything.

Feature                                                   Token Metrics API                                    CoinGecko API

Real-time + historical OHLCV              ✅                                                          ✅

Trader/Investor Grades                        ✅ AI-powered                                     ❌

Exchange Aggregation                         ✅ (Used in indices, not exposed)     ✅

Sentiment & Social Scoring                  ✅ NLP-driven                                     ❌

AI Signals                                               ✅                                                         ❌

Token Fundamentals                            ✅ Summary via deepdive         ⚠️ Limited

                                                                        endpoint

NFT Market Data                                  ❌                                                          ✅

On-Chain Behavior                               ✅ Signals + Indices                   ⚠️ Pro-only (limited)

If you're building something analytics-heavy—especially trading or AI-driven—Token Metrics gives you depth, not just breadth.

Verdict: CoinGecko wins on broad metadata coverage. Token Metrics wins on intelligence and strategic utility.

🛠 Developer Experience

One of the biggest barriers in Web3 is getting devs from “idea” to “prototype” without friction. Token Metrics makes that easy.

Token Metrics API Includes:

  • SDKs for Python, Node.js, and Postman
  • Quick-start guides and GitHub sample projects
  • Integrated usage dashboard to track limits and history
  • Conversational agent to explore data interactively
  • Clear, logical endpoint structure across 21 data types

CoinGecko:

  • Simple REST API
  • JSON responses
  • Minimal docs
  • No SDKs
  • No built-in tooling (must build from scratch)

Winner: Token Metrics — Serious devs save hours with ready-to-go SDKs and utilities.

📊 Monitoring, Quotas & Support

CoinGecko Free Tier:

  • 10–30 requests/min
  • No API key needed
  • Public endpoints
  • No email support
  • Rate limiting enforced via IP

Token Metrics Free Tier:

  • 5,000 requests/month
  • 1 request/min
  • Full access to AI signals, grades, rankings
  • Telegram & email support
  • Upgrade paths to 20K–500K requests/month

While CoinGecko’s no-login access is beginner-friendly, Token Metrics offers far more power per call. With just a few queries, your app can determine which tokens are gaining momentum, which are losing steam, and how portfolios should be adjusted.

Winner: Token Metrics — Better for sustained usage, scaling, and production reliability.

💸 Pricing & Value

Plan Feature                CoinGecko Pro            Token Metrics API

Entry Price                  ~$150/month                $99/month

AI Grades & Signals            ❌                               ✅ 

Sentiment Analytics            ❌                               ✅

Sector Index Insights          ❌                               ✅

NLP Token Summaries       ❌                                ✅

Developer SDKs                  ❌                                ✅

Token-Based Discounts     ❌                                ✅ (up to 35% with $TMAI)

For what you pay, Token Metrics delivers quant models and intelligent signal streams — not just raw price.

Winner: Token Metrics — Cheaper entry, deeper value.

🧠 Use Cases Where Token Metrics API Shines

  • Trading Bots
    Use Trader Grade and Signal endpoints to enter/exit based on AI triggers.
  • GPT Agents
    Generate conversational answers for “What’s the best AI token this week?” using structured summaries.
  • Crypto Dashboards
    Power sortable, filtered token tables by grade, signal, or narrative.
  • Portfolio Rebalancers
    Track real-time signals for tokens held, flag risk zones, and show sector exposure.
  • LLM Plugins
    Build chat-based investment tools with explainability and score-based logic.

🧠 Final Verdict: CoinGecko for Info, Token Metrics for Intelligence

If you're building a crypto price tracker, NFT aggregator, or exchange overview site, CoinGecko is a solid foundation. It’s reliable, broad, and easy to get started.

But if your product needs to think, adapt, or help users make better decisions, then Token Metrics API is in another class entirely.

You're not just accessing data — you're integrating AI, machine learning, and predictive analytics into your app. That’s the difference between showing the market and understanding it.

🔗 Ready to Build Smarter?

  • ✅ 5,000 free API calls/month
  • 🤖 Trader & Investor Grades
  • 📊 Live Bull/Bear signals
  • 🧠 AI-powered summaries and GPT compatibility
  • ⚡ 21 endpoints + Python/JS SDKs

👉 Start with Token Metrics API

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Python Quick-Start with Token Metrics: The Ultimate Crypto Price API

Token Metrics Team
10 min
MIN

If you’re a Python developer looking to build smarter crypto apps, bots, or dashboards, you need two things: reliable data and AI-powered insights. The Token Metrics API gives you both. In this tutorial, we’ll show you how to quickly get started using Token Metrics as your Python crypto price API, including how to authenticate, install the SDK, and run your first request in minutes.

Whether you’re pulling live market data, integrating Trader Grades into your trading strategy, or backtesting with OHLCV data, this guide has you covered.

🚀 Quick Setup for Developers in a Hurry

Install the official Token Metrics Python SDK:

pip install tokenmetrics

Or if you prefer working with requests directly, no problem. We’ll show both methods below.

🔑 Step 1: Generate Your API Key

Before anything else, you’ll need a Token Metrics account.

  1. Go to app.tokenmetrics.com/en/api
  2. Log in and navigate to the API Keys Dashboard
  3. Click Generate API Key
  4. Name your key (e.g., “Development”, “Production”)
  5. Copy it immediately — keep it secret.

You can monitor usage, rate limits, and quotas right from the dashboard. Track each key’s status, last used date, and revoke access at any time.

📈 Step 2: Retrieve Crypto Prices in Python

Here’s a simple example to fetch the latest price data for Ethereum (ETH):

import requests

API_KEY = "YOUR_API_KEY"

headers = {"x-api-key": API_KEY}

url = "https://api.tokenmetrics.com/v2/daily-ohlcv?symbol=ETH&startDate=<YYYY-MM-DD>&endDate=<YYYY-MM-DD>"

response = requests.get(url, headers=headers)

data = response.json()

for candle in data['data']:

    print(f"Date: {candle['DATE']} | Close: ${candle['CLOSE']}")

You now have a working python crypto price API pipeline. Customize startDate or endDate to get specific range of historical data.

📊 Add AI-Powered Trader Grades

Token Metrics’ secret sauce is its AI-driven token ratings. Here’s how to access Trader Grades for ETH:

grade_url = "https://api.tokenmetrics.com/v2/trader-grades?symbol=ETH&limit=30d"

grades = requests.get(grade_url, headers=headers).json()['data']

for day in grades:

    print(f"{day['DATE']} — Trader Grade: {day['TA_GRADE']}")

Use this data to automate trading logic (e.g., enter trades when Grade > 85) or overlay on charts.

🔁 Combine Data for Backtesting

Want to test a strategy? Merge OHLCV and Trader Grades for any token:

import pandas as pd

ohlcv_df = pd.DataFrame(data['data'])

grades_df = pd.DataFrame(grades)

combined_df = pd.merge(ohlcv_df, grades_df, on="DATE")

print(combined_df.head())

Now you can run simulations, build analytics dashboards, or train your own models.

⚙️ Endpoint Coverage for Python Devs

  • /daily-ohlcv: Historical price data
  • /trader-grades: AI signal grades (0–100)
  • /trading-signals: Bullish/Bearish signals for short and long positions.
  • /sentiment: AI-modeled sentiment scores
  • /tmai: Ask questions in plain English

All endpoints return structured JSON and can be queried via requests, axios, or any modern client.

🧠 Developer Tips

  • Each request = 1 credit (tracked in real time)
  • Rate limits depend on your plan (Free = 1 req/min)
  • Use the API Usage Dashboard to monitor and optimize
  • Free plan = 5,000 calls/month — perfect for testing and building MVPs

💸 Bonus: Save 35% with $TMAI

You can reduce your API bill by up to 35% by staking and paying with Token Metrics’ native token, $TMAI. Available via the settings → payments page.

🌐 Final Thoughts

If you're searching for the best python crypto price API with more than just price data, Token Metrics is the ultimate choice. It combines market data with proprietary AI intelligence, trader/investor grades, sentiment scores, and backtest-ready endpoints—all in one platform.

✅ Real-time & historical data
✅ RESTful endpoints
✅ Python-ready SDKs and docs
✅ Free plan to start building today

Start building today → tokenmetrics.com/api

Looking for SDK docs? Explore the full Python Quick Start Guide

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