llmprices 1.2.0

Compare LLM API costs across providers from the command line

llmprices

Compare LLM API prices across providers from the command line.

Find the cheapest model for your prompt in seconds

$ llm-cost calc "Summarize this article for me" --output 500

╭── Cost estimate · 7 input + 500 output ──────────────────────────────────────╮
│  #  Provider      Model                Total cost    vs cheapest              │
│  1  Mistral AI    Mistral Small 3.2    $0.000090     cheapest                 │
│  2  DeepSeek      DeepSeek V4 Flash    $0.000141     1.6x                     │
│  3  Google        Gemini 2.5 Flash-L   $0.000200     2.2x                     │
│  4  xAI           Grok 4.1 Fast        $0.000251     2.8x                     │
│  5  OpenAI        GPT-5.4 Nano         $0.000626     7.0x                     │
│  6  Anthropic     Claude Haiku 4.5     $0.002507     27.9x                    │
│  7  Google        Gemini 3.1 Pro       $0.006014     66.8x                    │
│  8  OpenAI        GPT-5.5              $0.015035    167.1x                    │
╰──────────────────────────────────────────────────────────────────────────────╯

  Cheapest: Mistral Small 3.2 (Mistral AI) — $0.000090

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Install

pip install llmprices

For accurate token counting (uses tiktoken):

pip install "llmprices[tiktoken]"

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Usage

List all models

llm-cost list

Filter by provider:

llm-cost list --provider anthropic
llm-cost list --provider openai

Filter by efficiency tier:

llm-cost list --tier flagship    # Top-tier models (GPT-5.5, Claude Opus 4.7, o3)
llm-cost list --tier advanced    # Advanced models (GPT-5.4, Claude Sonnet, Gemini Pro)
llm-cost list --tier standard    # Standard models (GPT-5, Claude Haiku, Gemini Flash)
llm-cost list --tier budget      # Budget models (Nano, Small, Lite models)

Sort options (input, output, context, name, value):

llm-cost list --sort output
llm-cost list --sort value       # Sort by efficiency/cost ratio

Search by name:

llm-cost list --search gpt-5
llm-cost list --search gemini

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Calculate cost for a prompt

# Auto-estimate tokens from text
llm-cost calc "Write me a blog post about AI pricing" --output 800

# Specify tokens directly
llm-cost calc --input 4000 --output 1000

# Top 5 cheapest only
llm-cost calc --input 10000 --output 2000 --top 5

# Filter to one provider
llm-cost calc "My prompt" --output 500 --provider google

# Filter by efficiency tier
llm-cost calc "Complex reasoning task" --output 1500 --tier advanced

# Sort by value (efficiency/cost ratio) instead of just cost
llm-cost calc "My prompt" --output 1000 --sort value --top 10

# One specific model
llm-cost calc "My prompt" --output 500 --model gpt-5-5

Understanding Value Score: The value score represents the efficiency-to-cost ratio. Higher scores mean better value:

• Budget models often have high value scores for simple tasks
• Advanced/Flagship models have lower value scores but better quality
• Use --sort value to find the best balance for your use case

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Compare specific models

# Latest flagships head-to-head
llm-cost compare gpt-5-5 claude-opus-4-7 gemini-3-1-pro

# Compare different tiers to see value differences
llm-cost compare gpt-5-5 deepseek-r1 mistral-small-3-2 --input 5000 --output 2000

# Mid-tier sweet spot
llm-cost compare gpt-5-4 claude-sonnet-4-6 gemini-3-flash --input 5000 --output 1000

# Budget tier
llm-cost compare gpt-5-4-nano deepseek-v4-flash grok-4-1-fast mistral-small-3-2

# New agentic models
llm-cost compare deepseek-v4-pro glm-5-1 kimi-k2-6 minimax-m2-7 --input 5000 --output 1000

# From a real prompt
llm-cost compare gpt-5-5 claude-opus-4-7 --prompt "Explain how transformers work"

The comparison table shows:

• Tier: Efficiency tier (flagship/advanced/standard/budget)
• Value: Efficiency-to-cost ratio (higher = better value)
• Total Cost: Complete cost for the specified tokens

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List providers

llm-cost providers

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Supported models (May 2026)

Prices in USD per 1M tokens.

Efficiency Tiers

Models are categorized by their capabilities and efficiency:

• 🏆 Flagship: Top-tier models with maximum efficiency for complex tasks (GPT-5.5, Claude Opus 4.7, o3)
• ⚡ Advanced: Excellent balance of quality and cost (GPT-5.4, Claude Sonnet, DeepSeek R1, Gemini Pro)
• ✓ Standard: Solid performance for most tasks (GPT-5, Claude Haiku, Gemini Flash)
• 💰 Budget: Cost-effective for simple tasks (Nano, Small, Lite models)

Provider	Model	Tier	Input	Output	Context
OpenAI	GPT-5.5	Flagship	$5.00	$30.00	1M
OpenAI	GPT-5.5 Pro	Flagship	$30.00	$180.00	1M
OpenAI	GPT-5.4 Pro	Flagship	$30.00	$180.00	400K
OpenAI	o3	Flagship	$10.00	$40.00	200K
Anthropic	Claude Opus 4.7	Flagship	$5.00	$25.00	1M
Anthropic	Claude Opus 4.6	Flagship	$5.00	$25.00	1M
OpenAI	GPT-5.4	Advanced	$2.50	$15.00	1.05M
OpenAI	o4 Mini	Advanced	$1.10	$4.40	200K
Anthropic	Claude Sonnet 4.6	Advanced	$3.00	$15.00	1M
Google	Gemini 3.1 Pro	Advanced	$2.00	$12.00	1M
Google	Gemini 2.5 Pro	Advanced	$1.25	$10.00	1M
xAI	Grok 4	Advanced	$3.00	$15.00	2M
DeepSeek	DeepSeek R1	Advanced	$0.55	$2.19	1M
OpenAI	GPT-5	Standard	$1.25	$10.00	400K
OpenAI	GPT-5.4 Mini	Standard	$0.75	$4.50	400K
Anthropic	Claude Haiku 4.5	Standard	$1.00	$5.00	200K
Google	Gemini 3 Flash	Standard	$0.50	$3.00	1M
Google	Gemini 2.5 Flash	Standard	$0.30	$2.50	1M
DeepSeek	DeepSeek V4 Pro	Standard	$1.74	$3.48	1M
Mistral AI	Mistral Large 3	Standard	$0.50	$1.50	256K
Mistral AI	Mistral Medium 3.5	Standard	$1.00	$3.00	256K
Z.AI	GLM-5.1	Standard	$1.40	$4.40	200K
Kimi	Kimi K2.6	Standard	$0.95	$4.00	256K
Cohere	Command R+	Standard	$3.00	$15.00	128K
OpenAI	GPT-5.4 Nano	Budget	$0.20	$1.25	200K
Google	Gemini 2.5 Flash-Lite	Budget	$0.10	$0.40	1M
xAI	Grok 4.1 Fast	Budget	$0.20	$0.50	2M
DeepSeek	DeepSeek V4 Flash	Budget	$0.14	$0.28	1M
MiniMax	MiniMax M2.7	Budget	$0.30	$1.20	197K
Mistral AI	Mistral Small 3.2	Budget	$0.06	$0.18	131K
Meta	Llama 4 Maverick	Budget	$0.27	$0.85	1M
Meta	Llama 3.3 70B	Budget	$0.59	$0.79	128K
Cohere	Command R7B	Budget	$0.04	$0.15	128K

Notes:

• DeepSeek V4 has two API variants: deepseek-v4-flash and deepseek-v4-pro.
• Cached-input, batch, promotional, long-context, and subscription-plan discounts are not included in the main table.

Price sources:

• DeepSeek: Models & Pricing
• Z.AI: Pricing
• Kimi: Kimi K2.6 Pricing
• MiniMax: Pay as You Go

33 models across 11 providers. Prices stored in llm_cost/data/prices.yaml — PRs to update them are always welcome!

📦 PyPI: pypi.org/project/llmprices

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Token counting

Default: word-based heuristic — zero extra dependencies. For accurate counts:

pip install "llmprices[tiktoken]"

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Contributing

The easiest contribution is updating llm_cost/data/prices.yaml when a provider changes their pricing. Each entry is just 4 fields:

my-new-model:
  name: My New Model
  input: 1.50      # $ per 1M input tokens
  output: 6.00     # $ per 1M output tokens
  context: 200000  # context window in tokens

git clone https://github.com/madeburo/llmcost
cd llmprices
pip install -e ".[dev]"
pytest