change_pct float64 -15 49.8 | date stringdate 2026-10-28 00:00:00 2026-10-29 00:00:00 | from_hourly_usd float64 0.41 6.13 | gpu stringclasses 6
values | key stringlengths 60 70 | source_url stringclasses 3
values | status stringclasses 1
value | tier stringclasses 3
values | to_hourly_usd float64 0.41 6.19 | vendor stringclasses 2
values | vram_gb int64 24 141 |
|---|---|---|---|---|---|---|---|---|---|---|
1 | 2026-10-29 | 0.9315 | L40S | Verda (formerly DataCrunch)|L40S|Spot instance (1x GPU)|48|1 | https://verda.com/pricing | ranked | Spot instance (1x GPU) | 0.941 | Verda (formerly DataCrunch) | 48 |
49.8 | 2026-10-29 | 1.1378 | A100 SXM | Vast.ai|A100 SXM|Marketplace on-demand (verified; median per GPU)|80|1 | https://console.vast.ai/api/v0/bundles/?q=%7B%22gpu_name%22%3A%7B%22eq%22%3A%22A100%20SXM4%22%7D%2C%22rentable%22%3A%7B%22eq%22%3Atrue%7D%2C%22rented%22%3A%7B%22eq%22%3Afalse%7D%2C%22verified%22%3A%7B%22eq%22%3Atrue%7D%2C%22type%22%3A%22on-demand%22%2C%22limit%22%3A1000%7D | ranked | Marketplace on-demand (verified; median per GPU) | 1.7043 | Vast.ai | 80 |
1 | 2026-10-29 | 0.406 | RTX A6000 | Verda (formerly DataCrunch)|RTX A6000|Spot instance (1x GPU)|48|1 | https://verda.com/pricing | ranked | Spot instance (1x GPU) | 0.41 | Verda (formerly DataCrunch) | 48 |
1 | 2026-10-29 | 0.812 | RTX A6000 | Verda (formerly DataCrunch)|RTX A6000|On-demand instance (1x GPU)|48|1 | https://verda.com/pricing | ranked | On-demand instance (1x GPU) | 0.82 | Verda (formerly DataCrunch) | 48 |
1 | 2026-10-29 | 6.127 | H200 SXM | Verda (formerly DataCrunch)|H200 SXM|On-demand instance (1x GPU)|141|1 | https://verda.com/pricing | ranked | On-demand instance (1x GPU) | 6.188 | Verda (formerly DataCrunch) | 141 |
1 | 2026-10-29 | 3.064 | H200 SXM | Verda (formerly DataCrunch)|H200 SXM|Spot instance (1x GPU)|141|1 | https://verda.com/pricing | ranked | Spot instance (1x GPU) | 3.094 | Verda (formerly DataCrunch) | 141 |
1 | 2026-10-29 | 2.204 | A100 SXM | Verda (formerly DataCrunch)|A100 SXM|On-demand instance (1x GPU)|80|1 | https://verda.com/pricing | ranked | On-demand instance (1x GPU) | 2.226 | Verda (formerly DataCrunch) | 80 |
-6.8 | 2026-10-29 | 0.5175 | RTX 4090 | Vast.ai|RTX 4090|Marketplace on-demand (verified; median per GPU)|24|1 | https://console.vast.ai/api/v0/bundles/?q=%7B%22gpu_name%22%3A%7B%22eq%22%3A%22RTX%204090%22%7D%2C%22rentable%22%3A%7B%22eq%22%3Atrue%7D%2C%22rented%22%3A%7B%22eq%22%3Afalse%7D%2C%22verified%22%3A%7B%22eq%22%3Atrue%7D%2C%22type%22%3A%22on-demand%22%2C%22limit%22%3A1000%7D | ranked | Marketplace on-demand (verified; median per GPU) | 0.4822 | Vast.ai | 24 |
1 | 2026-10-29 | 1.102 | A100 SXM | Verda (formerly DataCrunch)|A100 SXM|Spot instance (1x GPU)|80|1 | https://verda.com/pricing | ranked | Spot instance (1x GPU) | 1.113 | Verda (formerly DataCrunch) | 80 |
1 | 2026-10-29 | 2.35 | H100 SXM | Verda (formerly DataCrunch)|H100 SXM|Spot instance (1x GPU)|80|1 | https://verda.com/pricing | ranked | Spot instance (1x GPU) | 2.373 | Verda (formerly DataCrunch) | 80 |
1 | 2026-10-29 | 4.699 | H100 SXM | Verda (formerly DataCrunch)|H100 SXM|On-demand instance (1x GPU)|80|1 | https://verda.com/pricing | ranked | On-demand instance (1x GPU) | 4.746 | Verda (formerly DataCrunch) | 80 |
1 | 2026-10-29 | 1.863 | L40S | Verda (formerly DataCrunch)|L40S|On-demand instance (1x GPU)|48|1 | https://verda.com/pricing | ranked | On-demand instance (1x GPU) | 1.882 | Verda (formerly DataCrunch) | 48 |
-15 | 2026-10-28 | 1.3389 | A100 SXM | Vast.ai|A100 SXM|Marketplace on-demand (verified; median per GPU)|80|1 | https://console.vast.ai/api/v0/bundles/?q=%7B%22gpu_name%22%3A%7B%22eq%22%3A%22A100%20SXM4%22%7D%2C%22rentable%22%3A%7B%22eq%22%3Atrue%7D%2C%22rented%22%3A%7B%22eq%22%3Afalse%7D%2C%22verified%22%3A%7B%22eq%22%3Atrue%7D%2C%22type%22%3A%22on-demand%22%2C%22limit%22%3A1000%7D | ranked | Marketplace on-demand (verified; median per GPU) | 1.1378 | Vast.ai | 80 |
3 | 2026-10-28 | 0.5022 | RTX 4090 | Vast.ai|RTX 4090|Marketplace on-demand (verified; median per GPU)|24|1 | https://console.vast.ai/api/v0/bundles/?q=%7B%22gpu_name%22%3A%7B%22eq%22%3A%22RTX%204090%22%7D%2C%22rentable%22%3A%7B%22eq%22%3Atrue%7D%2C%22rented%22%3A%7B%22eq%22%3Afalse%7D%2C%22verified%22%3A%7B%22eq%22%3Atrue%7D%2C%22type%22%3A%22on-demand%22%2C%22limit%22%3A1000%7D | ranked | Marketplace on-demand (verified; median per GPU) | 0.5175 | Vast.ai | 24 |
Lantern Works GPU Rental Price History
A daily history of per-GPU-hour rental prices from tracked cloud GPU providers (H100, H200, A100, L40S, RTX 4090/5090, RTX A6000, B200 and others). This covers tracked providers only, not the whole market.
Snapshot range: 2026-10-27 to 2026-10-29 (3 daily snapshots). The files hold 114 price series, 133 change points and 14 price changes.
Query the live data with an MCP agent
Lantern Works runs a free, read-only MCP server (no API key) over the same live feed this dataset is built from.
Hosted endpoint (nothing to install, 13 tools):
claude mcp add --transport http lantern-works-deals "https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=hf"
For Claude Desktop, Cursor or VS Code, add https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=hf as an HTTP MCP server. The hosted endpoint adds four opt-in price-watch tools (create_watch_key, watch_price, list_watches, delete_watch) to the 9 package tools.
Stdio (local, 9 tools):
claude mcp add lantern-works-deals -- uvx lantern-works-deals-mcp
or in an MCP client config:
{"mcpServers": {"lantern-works-deals": {"command": "uvx", "args": ["lantern-works-deals-mcp"]}}}
Main GPU tools: compare_gpu_prices, get_price_changes, estimate_job_cost, rebuild_quote.
Example prompt:
Find the cheapest tracked H100 rental, estimate a 100-hour run on it, and tell me whether that rate changed since yesterday. Show the vendor source and check time for each price.
Files
gpu_price_points.csv: one row per change point. Each row is the first snapshot date at that price or status for a series (vendor | gpu | tier | vram_gb | gpu_count). Columns: key, vendor, gpu, tier, vram_gb, gpu_count, billing_unit, first_seen, date, hourly_usd, price_usd, status, verified_at.status:ranked;held(published but not ranked, either stale or too thin a marketplace); orremoved(no longer tracked).
gpu_price_changes.csv: day-over-day price changes (from_hourly_usd, to_hourly_usd, change_pct, source_url).history.json: the raw upstream file.
Live feeds (always current)
- Current prices: https://thelanternworks.com/api/v1/gpu-prices.json?ref=hf
- Changes since yesterday: https://thelanternworks.com/api/v1/gpu-price-changes.json?ref=hf
- Upstream history: https://thelanternworks.com/api/v1/gpu-prices/history.json?ref=hf
In a notebook:
import json, urllib.request
feed = json.load(urllib.request.urlopen("https://thelanternworks.com/api/v1/gpu-prices.json?ref=hf"))
h100 = sorted((r for r in feed["rates"] if r["canonical_model"] == "H100"), key=lambda r: r["hourly_equiv_usd"])
Sources and method
- Each rate comes from the vendor's own pricing page or API (
source_url). A daily job re-reads every source (robots.txt respected) and updates a price only where it parsed one. A rate not re-verified for 7 days is held and not ranked. - Prices are list prices before tax, storage and egress. Check the vendor page before you pay.
Update cadence
Upstream refreshes daily at about 10:23 UTC. This dataset copy is a snapshot and can lag the live feed until it is re-published.
License
The price data is licensed CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Credit: Lantern Works (https://thelanternworks.com/?ref=hf). Prices are factual quotes from the vendors' public pages. The MCP server code is MIT.
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