$ llm-prices top 10 --in 10000 --out 2000
Top 10 cheapest: 10,000 input / 2,000 output tokens

#    Model                  Provider            Input       Output        Total
-------------------------------------------------------------------------------
1    llama-3.1-8b-nb        Nebius          $0.000200    $0.000120    $0.000320
2    nova-micro-br          Bedrock         $0.000350    $0.000280    $0.000630
3    llama-3.1-8b           Groq            $0.000500    $0.000160    $0.000660
4    gemini-1.5-flash-8b    Google          $0.000375    $0.000300    $0.000675
5    command-r7b            Cohere          $0.000375    $0.000300    $0.000675
...

$ llm-prices compare gpt-4o claude-sonnet-4-6 gemini-2.5-flash gpt-5-nano --in 10000 --out 2000
Comparison: 10,000 input tokens, 2,000 output tokens

Model                Provider            Input       Output        Total
------------------------------------------------------------------------
gpt-5-nano           OpenAI          $0.000500    $0.000800    $0.001300
gemini-2.5-flash     Google          $0.003000    $0.005000    $0.008000 (6.2x)
gpt-4o               OpenAI            $0.0250      $0.0200    $0.0450 (34.6x)
claude-sonnet-4-6    Anthropic         $0.0300      $0.0300    $0.0600 (46.2x)

Cheapest: gpt-5-nano at $0.001300

pip install "git+https://github.com/benbencodes/llm-prices[mcp]"

{
  "mcpServers": {
    "llm-prices": {
      "command": "llm-prices-mcp"
    }
  }
}

{
  "mcpServers": {
    "llm-prices": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/benbencodes/llm-prices[mcp]", "llm-prices-mcp"]
    }
  }
}

pipx install git+https://github.com/benbencodes/llm-prices

brew tap benbencodes/tap
brew install llm-prices

pip install llm-prices

git clone https://github.com/benbencodes/llm-prices
cd llm-prices
pip install -e .

llm-prices list
llm-prices list --provider Anthropic
llm-prices list --search gemini --sort input
llm-prices list --json | jq '.[].model'

llm-prices list --provider OpenAI --sort input --markdown

| Model        | Provider | Input/Mtok | Output/Mtok | Context  | Notes                     |
|--------------|----------|------------|-------------|----------|---------------------------|
| gpt-4.1-nano | OpenAI   | $0.1000    | $0.4000     | 1023k    | Fastest, cheapest GPT-4.1 |
| gpt-4o-mini  | OpenAI   | $0.1500    | $0.6000     | 128k     | Small, fast, cheap        |
| gpt-4.1-mini | OpenAI   | $0.4000    | $1.6000     | 1023k    | 1M context, cost-efficient|
| gpt-4o       | OpenAI   | $2.5000    | $10.0000    | 128k     | Latest multimodal flagship|
...

llm-prices list --csv > llm_prices.csv

# 10,000 input tokens, 2,000 output tokens on GPT-4o
llm-prices calc gpt-4o --in 10000 --out 2000

# Model  : gpt-4o (OpenAI)
# Tokens : 10,000 in / 2,000 out
# Rate   : $2.5/Mtok in, $10.0/Mtok out
# Cost   : $0.0250 in + $0.0200 out = $0.0450 total

llm-prices calc claude-sonnet-4-6 --in 5000 --out 1000 --json

llm-prices compare gpt-4o claude-sonnet-4-6 gemini-2.5-pro qwen3-235b \
  --in 5000 --out 1000 --markdown

<!-- 5,000 input / 1,000 output tokens. Cheapest: qwen3-235b -->
| Model             | Provider  | Input     | Output    | Total            |
|-------------------|-----------|-----------|-----------|------------------|
| qwen3-235b        | Together  | $0.001000 | $0.000600 | $0.001600        |
| gemini-2.5-pro    | Google    | $0.006250 | $0.0100   | $0.0163 (10.2x)  |
| gpt-4o            | OpenAI    | $0.0125   | $0.0100   | $0.0225 (14.1x)  |
| claude-sonnet-4-6 | Anthropic | $0.0150   | $0.0150   | $0.0300 (18.8x)  |

# Top 5 cheapest for 5k input / 1k output tokens
llm-prices top 5 --in 5000 --out 1000

Top 5 cheapest: 5,000 input / 1,000 output tokens

#    Model                Provider      Input       Output       Total
----------------------------------------------------------------------
1    llama-3.1-8b         Groq       $0.000250   $0.000080   $0.000330
2    gemini-1.5-flash-8b  Google     $0.000188   $0.000150   $0.000338
3    command-r7b          Cohere     $0.000188   $0.000150   $0.000338
4    qwen3.5-9b           Together   $0.000500   $0.000150   $0.000650
5    gemini-1.5-flash     Google     $0.000375   $0.000300   $0.000675

llm-prices top 3 --provider Anthropic --in 2000 --out 800
llm-prices top 10 --in 5000 --out 1000 --markdown

# How many calls at 1k in / 500 out tokens fit in $1.00?
llm-prices budget 1.00 --in 1000 --out 500

# Filter to just Anthropic models
llm-prices budget 0.10 --provider Anthropic --in 5000 --out 2000

# Show models added in recent releases
llm-prices new

# Filter to a specific version
llm-prices new --version v0.1.42

# Output as JSON
llm-prices new --json

Recently added models (v0.1.42, data: 2026-05-20)

v0.1.42 — 10 models
  qwen3.6-flash        Qwen        $0.1875/$1.1250         1M  Qwen3.6 Flash; 1M ctx; fast multimodal...
  deepseek-v4-pro      DeepSeek    $0.4350/$0.8700         1M  DeepSeek V4 Pro; 1.6T-param MoE flagship...
  mistral-medium-3-5   Mistral     $1.5000/$7.5000       262k  Mistral Medium 3.5; dense 128B...
  perceptron-mk1       Perceptron  $0.1500/$1.5000        32k  Perceptron Mk1; video+embodied AI VLM...
  ...

from llm_prices import calculate_cost, MODELS

result = calculate_cost("gpt-4o", input_tokens=10_000, output_tokens=2_000)
print(f"Total: ${result['total_cost_usd']:.4f}")

for name, info in MODELS.items():
    if info["provider"] == "Anthropic":
        print(name, info["input_per_mtok"], info["output_per_mtok"])