| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - llm |
| - pricing |
| - cost |
| - openai |
| - anthropic |
| - google |
| - meta |
| - reference |
| size_categories: |
| - n<1K |
| pretty_name: LLM Pricing Table |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data.jsonl |
| --- |
| |
| # LLM Pricing Table |
|
|
| Per-1k-token input/output costs for the major LLM models, in a single loadable JSONL. Useful for cost-estimator dashboards, budget enforcement, and ROI analysis. |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("mukunda1729/model-pricing-table", split="train") |
| prices = {row["model"]: row for row in ds} |
| print(prices["claude-sonnet-4-6"]["input_per_1k_tokens_usd"]) # 0.003 |
| ``` |
|
|
| ## Schema |
|
|
| | Field | Type | Notes | |
| |---|---|---| |
| | `model` | `str` | Canonical model identifier | |
| | `provider` | `str` | `openai` / `anthropic` / `google` / `meta` / `mistral` / `deepseek` | |
| | `input_per_1k_tokens_usd` | `float` | USD per 1,000 input tokens | |
| | `output_per_1k_tokens_usd` | `float` | USD per 1,000 output tokens | |
| | `context_window` | `int` | Max tokens (input + output) | |
| | `modality` | `str` | `text` / `multimodal` | |
|
|
| ## Data freshness |
|
|
| Snapshot as of 2026-04-27. Provider prices change — always cross-reference the official pricing page before relying on these in production billing. |
|
|
| Sister tooling: [`llm-cost-guard-py`](https://pypi.org/project/llm-cost-guard-py/) and [`@mukundakatta/llm-cost-guard`](https://www.npmjs.com/package/@mukundakatta/llm-cost-guard) consume this table directly. |
|
|
| Part of [The Agent Reliability Stack](https://mukundakatta.github.io/agent-stack/). |
|
|
| ## License |
|
|
| MIT. |
|
|
