Cheapest LLM API 2026

AI API costs can scale fast. This guide identifies the cheapest frontier LLM APIs by price, ranks them for quality-per-dollar, and shows how to cut costs further with APIMaster.ai.

Cheapest LLM APIs by Price (2026)

Model	Provider	Input/M	Output/M	Context	Notes
GPT-4o mini	OpenAI	$0.15	$0.60	128K	Cheapest OpenAI
DeepSeek V4	DeepSeek	$0.27	$1.10	128K	Cheapest frontier
Gemini 2.0 Flash	Google	$0.075	$0.30	1M	Cheapest with vision
DeepSeek V3	DeepSeek	$0.27	$1.10	128K	Slightly older
Claude Haiku 4.5	Anthropic	$0.80	$4.00	200K	Cheapest Claude
Llama 3.3 70B	via providers	$0.23	$0.40	128K	Open-source

Official list prices. APIMaster offers additional discounts—see marketplace.

Best Value for Common Tasks

Simple Text Tasks (classification, extraction, summarization)

Cheapest option: Gemini 2.0 Flash at $0.075/M input

# Monthly cost for 100M calls × 200 input + 100 output tokens
# = 20B input + 10B output = 20K input M + 10K output M
# Gemini Flash: $0.075 × 20,000 + $0.30 × 10,000 = $1,500 + $3,000 = $4,500
# GPT-4o mini: $0.15 × 20,000 + $0.60 × 10,000 = $3,000 + $6,000 = $9,000

Code Generation (medium complexity)

Best price-performance: DeepSeek V4

DeepSeek V4 matches GPT-4o on most coding benchmarks at less than 6% of the price.

Long Document Analysis

Best value: Claude Haiku 4.5 (200K context at $0.80/M input)

GPT-4o mini tops out at 128K. For documents 128K–200K tokens, Haiku is the cheapest option.

Reasoning Tasks

Best value: DeepSeek R1 at $0.55/M input (vs o3 at $10.00/M)

How to Cut Your LLM API Bill

1. Right-size your model

Don't use a frontier model for simple tasks:

def classify_sentiment(text):
    # Use cheap model for simple classification
    resp = client.chat.completions.create(
        model="gpt-4o-mini",  # NOT gpt-5
        messages=[
            {"role": "system", "content": "Reply with only: positive, negative, or neutral"},
            {"role": "user", "content": text},
        ],
        max_tokens=5,  # Short output
    )
    return resp.choices[0].message.content.strip()

2. Limit max_tokens

Only generate what you need:

# Bad: allows up to 4096 tokens
response = client.chat.completions.create(model="gpt-4o", messages=messages)

# Good: cap at what you'll actually use
response = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    max_tokens=256,  # 94% cost reduction on output
)

3. Use prompt caching

Cached tokens cost 75% less on most providers:

# The long system prompt is cached after first use
SYSTEM = "You are an expert at extracting structured data from text. " + LONG_SCHEMA_DESCRIPTION
response = client.chat.completions.create(
    model="deepseek-v4",
    messages=[
        {"role": "system", "content": SYSTEM},  # cached on repeat
        {"role": "user", "content": document},
    ],
)

4. Batch non-urgent tasks

Many providers offer 50% off for async batch processing:

# Use batch API for non-real-time jobs
# DeepSeek batch: $0.135/M input (vs $0.27 standard = 50% off)

5. Use APIMaster for additional discounts

APIMaster offers 30–70% off official list prices on most models:

Model	Official	APIMaster	Savings
Claude Sonnet	$3.00/M	See marketplace	Up to 60%
GPT-4o	$5.00/M	See marketplace	Up to 50%
DeepSeek V4	$0.27/M	See marketplace	Additional

Monthly Budget Scenarios

Startup ($100/month budget)

At $100/month with DeepSeek V4 ($0.82/M combined avg):

• ~122M total tokens/month
• ≈ 250,000 API calls at avg 500 tokens each
• Sufficient for a small production chatbot

Scale-up ($1,000/month budget)

With mixed model strategy:

• Simple tasks → GPT-4o mini or Gemini Flash: 80% of volume
• Complex tasks → Claude Sonnet: 20% of volume
• Estimated 500K–1M calls/month

Enterprise ($10,000/month budget)

Volume discounts + APIMaster rates can stretch this to 5M+ calls/month depending on model mix.

Access the Cheapest LLM APIs via APIMaster

APIMaster aggregates all major providers in one endpoint, fingerprint-verifies each model, and offers competitive pricing:

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