uplinkswitch/llm-api-pricing

LLM API Pricing

Per-token API prices for 84 chat models and per-image, per-second and per-generation prices for 87 image, video, audio and 3D models. Each row puts the model developer's own list price next to the price on UplinkSwitch, an OpenAI- and Anthropic-compatible API gateway.

Every value comes from the public catalog API at https://api.uplinkswitch.com/v1/catalog and /v1/catalog/media. It's the same feed the gateway bills from, and it needs no key. The snapshot_at column shows when each row was read. Every row links to the model's price page on uplinkswitch.com (model_url), and open-weight models also link to their official weights on the Hub (weights_repo).

• Live, sortable version with a monthly cost calculator: LLM API Price Comparison Space
• Official weights for every open model here: LLM API pricing: open-weight models
• Same prices on the web: uplinkswitch.com/models · price index (CSV/JSON) · side-by-side comparisons

Configs

Config	Rows	What one row is
chat_models (default)	84	One chat model: list and UplinkSwitch prices per 1M input, cached-input and output tokens
media_models	245	One price variant of an image, video, audio or 3D model (for example resolution=2K)
chat_price_history	167	One chat model on one snapshot date (2026-10-16 onward)

The raw catalog responses are in raw/catalog.json and raw/catalog_media.json.

Load it

from datasets import load_dataset

chat = load_dataset("uplinkswitch/llm-api-pricing", "chat_models", split="train").to_pandas()
media = load_dataset("uplinkswitch/llm-api-pricing", "media_models", split="train").to_pandas()
history = load_dataset("uplinkswitch/llm-api-pricing", "chat_price_history", split="train").to_pandas()

# Monthly cost of 50M input + 10M output tokens, list vs UplinkSwitch
chat["list_monthly"] = 50 * chat.list_input_usd_per_1m + 10 * chat.list_output_usd_per_1m
chat["uplink_monthly"] = 50 * chat.price_input_usd_per_1m + 10 * chat.price_output_usd_per_1m
print(chat.sort_values("uplink_monthly")[["display_name", "list_monthly", "uplink_monthly"]].head(20))

With pandas only:

import pandas as pd
chat = pd.read_csv("hf://datasets/uplinkswitch/llm-api-pricing/data/chat_models.csv")

Columns

chat_models

Column	Type	Meaning
model_id	string	The model value to send to the API
display_name	string	Model name as the developer writes it
developer	string	Anthropic, OpenAI, Google, xAI, DeepSeek, Qwen, Moonshot AI, Z.ai, MiniMax, Xiaomi, Tencent, NVIDIA, Meta, …
wire_formats	string	API formats the model accepts, pipe-separated (openai, anthropic)
list_input_usd_per_1m	float	Developer list price, USD per 1M input tokens. Empty when the developer publishes no price
list_cache_read_usd_per_1m	float	Developer list price for cached input tokens
list_output_usd_per_1m	float	Developer list price, USD per 1M output tokens
price_input_usd_per_1m	float	UplinkSwitch price, USD per 1M input tokens
price_cache_read_usd_per_1m	float	UplinkSwitch price for cached input tokens
price_output_usd_per_1m	float	UplinkSwitch price, USD per 1M output tokens
pct_under_list_input	float	100 × (1 − price / list) on input, rounded to 0.1
pct_under_list_output	float	Same, on output
model_url	string	The model's page on uplinkswitch.com, e.g. https://uplinkswitch.com/models/claude-opus-5-5
weights_repo	string	Official open weights on the Hugging Face Hub; empty for closed models
snapshot_at	string	ISO 8601 time the catalog was read

media_models

Column	Type	Meaning
model_id, display_name, developer	string	As above (OpenAI, Alibaba, ByteDance, Google, Kling, Tripo, Black Forest Labs, ElevenLabs, MiniMax, xAI)
kind	string	image, video, audio or 3d
unit	string	What one price buys: image, second, minute, generation or 1k_characters
variant	string	The parameter values this price applies to, e.g. resolution=4K or duration=8, audio=True; default when there is one price
price_usd	float	UplinkSwitch price per unit
list_usd	float	Developer list price per unit, empty when none is published
pct_under_list	float	100 × (1 − price / list)
endpoints	string	API paths that serve the model, pipe-separated
model_url	string	The model's page on uplinkswitch.com, e.g. https://uplinkswitch.com/models/media/nano-banana-2
snapshot_at	string	ISO 8601 time the catalog was read

chat_price_history

snapshot_date, model_id, display_name, list_input_usd_per_1m, list_output_usd_per_1m, price_input_usd_per_1m, price_output_usd_per_1m. Use it to track list-price and gateway-price changes over time.

Example rows (2026-10-18)

Model	List in / out ($/1M)	UplinkSwitch in / out ($/1M)	Family pricing
Claude Opus 5.5	4 / 20	2.10 / 6.00	All Claude models
GPT-6.1 Sol	2 / 10	0.60 / 3.00	All GPT models
Gemini 3.1 Pro Preview	2 / 12	1.20 / 7.20	All Gemini models
DeepSeek V4 Pro	1.32 / 3.96	0.792 / 1.92	All DeepSeek models
Kimi K3	3 / 15	0.90 / 4.50	All Kimi models
Qwen3.7 Max	1.475 / 4.425	0.885 / 2.655	All Qwen models
GLM-5.3	1.092 / 3.432	0.3276 / 1.0296	All GLM models
Grok 4.7	2 / 6	0.60 / 1.80	All Grok models

In this snapshot, 73 of the 84 chat models have a published list price. The median UplinkSwitch output price is 40% under list. Cached input costs more than list on five models (deepseek-v4-flash-0731, deepseek-v4-pro-0813, deepseek-v4.1-flash, gpt-6-luna, mimo-v2.6-pro), so check the cache column if your workload is cache-heavy.

Open-weight models: weights and API price

Model	Weights on the Hub	API price page
DeepSeek V4 Pro	deepseek-ai/DeepSeek-V4-Pro	deepseek-v4-pro
DeepSeek V4 Flash	deepseek-ai/DeepSeek-V4-Flash	deepseek-v4-flash
DeepSeek V4 Flash 0731	deepseek-ai/DeepSeek-V4-Flash-0731	deepseek-v4-flash-0731
DeepSeek V4 Flash Vision (exp)	deepseek-ai/DeepSeek-V4-Flash-Vision-Exp	deepseek-v4-flash-vision-exp
DeepSeek V4.1 Flash	deepseek-ai/DeepSeek-V4.1-Flash	deepseek-v4.1-flash
DeepSeek V4.1 Flash 1017	deepseek-ai/DeepSeek-V4.1-Flash-1017	deepseek-v4.1-flash-1017
GLM-5.3	zai-org/GLM-5.3	glm-5.3
GLM-5.3 Flash	zai-org/GLM-5.3-Flash	glm-5.3-flash
GLM-5.2	zai-org/GLM-5.2	glm-5.2
GLM-5.1	zai-org/GLM-5.1	glm-5.1
Kimi K3	moonshotai/Kimi-K3	kimi-k3
Kimi K2.6	moonshotai/Kimi-K2.6	kimi-k2.6
Kimi K2.5	moonshotai/Kimi-K2.5	kimi-k2.5
Qwen3.6 27B	Qwen/Qwen3.6-27B	qwen3.6-27b
MiniMax M2.7	MiniMaxAI/MiniMax-M2.7	minimax-m2.7
MiniMax M2.5	MiniMaxAI/MiniMax-M2.5	minimax-m2.5
MiMo V2.5	XiaomiMiMo/MiMo-V2.5	mimo-v2.5
DiffusionGemma 26B A4B	google/diffusiongemma-26B-A4B-it	diffusiongemma-26b-a4b-it
Llama 3.2 11B Vision	meta-llama/Llama-3.2-11B-Vision-Instruct	llama-3.2-11b-vision-instruct

Read more

Pricing write-ups that use this data, one per model family:

• LLM API pricing comparison, October 2026
• Claude API pricing · GPT API pricing · Gemini API pricing · Grok API pricing
• DeepSeek API pricing · Kimi API pricing · GLM API pricing · Qwen API pricing
• What Claude Code costs on API billing · Using Cursor with your own API key: what it costs · Kimi, GLM and Qwen coding plans vs pay-per-token API
• The hidden prompt tokens in cheap LLM APIs · A free AI API: $1 of credit for Claude, GPT, Gemini and more
• Image and video prices: media models · Veo 3.1 guide · Nano Banana Pro guide

How it's built

scripts/build.py reads the two catalog endpoints and writes every file in data/ and raw/. It has no dependencies beyond the Python standard library. Run python scripts/build.py <out_dir> to rebuild it yourself. List prices are the model developers' own published per-token prices; the catalog stores them next to the gateway price so the two can be compared row by row.

Limitations

• Prices change. Trust snapshot_at, and for a live figure read the catalog API or uplinkswitch.com/models.
• List prices are standard-tier, non-batch prices. Batch, priority, long-context and regional tiers aren't included.
• Open-weight fine-tunes and community models often have no developer list price, so their list columns are empty.
• Volume discounts (3% from 100M tokens, 6% from 1B, 10% from 10B per month) aren't applied in the price columns.

Use the prices

The same key and base URL work with the OpenAI and Anthropic SDKs:

from openai import OpenAI

client = OpenAI(base_url="https://api.uplinkswitch.com/v1", api_key="sk-uplink-live-...")
reply = client.chat.completions.create(model="claude-opus-5-5", messages=[{"role": "user", "content": "hi"}])

• Python package: pip install uplinkswitch
• SDK setup (OpenAI, Anthropic, Gemini): uplinkswitch.com/guides/sdks
• Coding tools: Claude Code · Cursor · Cline · Roo Code · Kilo Code · OpenCode
• Daily token-count check of every model: uplinkswitch.com/proof
• Verify a signed usage statement: uplinkswitch.com/statements/verify
• Savings calculator: uplinkswitch.com/savings
• Get a key (prepaid from $10, no subscription): uplinkswitch.com/console
• Source and issues: github.com/uplinkswitch

License and citation

CC BY 4.0. Please credit "UplinkSwitch LLM API Pricing dataset" with a link to this page.

@misc{uplinkswitch_llm_api_pricing,
  title  = {LLM API Pricing},
  author = {{Uplink Switch LLC}},
  year   = {2026},
  url    = {https://huggingface.co/datasets/uplinkswitch/llm-api-pricing}
}