Initial: 20 LLM model pricing rows

README.md

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+---
+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.

data.jsonl

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+{"model": "gpt-5", "provider": "openai", "input_per_1k_tokens_usd": 0.005, "output_per_1k_tokens_usd": 0.015, "context_window": 200000, "modality": "text"}
+{"model": "gpt-5-mini", "provider": "openai", "input_per_1k_tokens_usd": 0.00015, "output_per_1k_tokens_usd": 0.0006, "context_window": 128000, "modality": "text"}
+{"model": "gpt-4o", "provider": "openai", "input_per_1k_tokens_usd": 0.0025, "output_per_1k_tokens_usd": 0.01, "context_window": 128000, "modality": "multimodal"}
+{"model": "gpt-4o-mini", "provider": "openai", "input_per_1k_tokens_usd": 0.00015, "output_per_1k_tokens_usd": 0.0006, "context_window": 128000, "modality": "multimodal"}
+{"model": "o1", "provider": "openai", "input_per_1k_tokens_usd": 0.015, "output_per_1k_tokens_usd": 0.06, "context_window": 200000, "modality": "text"}
+{"model": "o3-mini", "provider": "openai", "input_per_1k_tokens_usd": 0.0011, "output_per_1k_tokens_usd": 0.0044, "context_window": 200000, "modality": "text"}
+{"model": "claude-opus-4-1", "provider": "anthropic", "input_per_1k_tokens_usd": 0.015, "output_per_1k_tokens_usd": 0.075, "context_window": 200000, "modality": "multimodal"}
+{"model": "claude-sonnet-4-6", "provider": "anthropic", "input_per_1k_tokens_usd": 0.003, "output_per_1k_tokens_usd": 0.015, "context_window": 200000, "modality": "multimodal"}
+{"model": "claude-haiku-4-5", "provider": "anthropic", "input_per_1k_tokens_usd": 0.0008, "output_per_1k_tokens_usd": 0.004, "context_window": 200000, "modality": "multimodal"}
+{"model": "claude-3-5-sonnet", "provider": "anthropic", "input_per_1k_tokens_usd": 0.003, "output_per_1k_tokens_usd": 0.015, "context_window": 200000, "modality": "multimodal"}
+{"model": "claude-3-5-haiku", "provider": "anthropic", "input_per_1k_tokens_usd": 0.0008, "output_per_1k_tokens_usd": 0.004, "context_window": 200000, "modality": "multimodal"}
+{"model": "gemini-2-5-pro", "provider": "google", "input_per_1k_tokens_usd": 0.00125, "output_per_1k_tokens_usd": 0.01, "context_window": 1000000, "modality": "multimodal"}
+{"model": "gemini-2-5-flash", "provider": "google", "input_per_1k_tokens_usd": 0.000075, "output_per_1k_tokens_usd": 0.0003, "context_window": 1000000, "modality": "multimodal"}
+{"model": "gemini-1-5-pro", "provider": "google", "input_per_1k_tokens_usd": 0.00125, "output_per_1k_tokens_usd": 0.005, "context_window": 2000000, "modality": "multimodal"}
+{"model": "gemini-1-5-flash", "provider": "google", "input_per_1k_tokens_usd": 0.000075, "output_per_1k_tokens_usd": 0.0003, "context_window": 1000000, "modality": "multimodal"}
+{"model": "llama-3.1-405b", "provider": "meta", "input_per_1k_tokens_usd": 0.005, "output_per_1k_tokens_usd": 0.005, "context_window": 128000, "modality": "text"}
+{"model": "llama-3.1-70b", "provider": "meta", "input_per_1k_tokens_usd": 0.0009, "output_per_1k_tokens_usd": 0.0009, "context_window": 128000, "modality": "text"}
+{"model": "llama-3.1-8b", "provider": "meta", "input_per_1k_tokens_usd": 0.0002, "output_per_1k_tokens_usd": 0.0002, "context_window": 128000, "modality": "text"}
+{"model": "mistral-large", "provider": "mistral", "input_per_1k_tokens_usd": 0.002, "output_per_1k_tokens_usd": 0.006, "context_window": 128000, "modality": "text"}
+{"model": "deepseek-r1", "provider": "deepseek", "input_per_1k_tokens_usd": 0.00055, "output_per_1k_tokens_usd": 0.00219, "context_window": 64000, "modality": "text"}