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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); or removed (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)

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.

More: https://thelanternworks.com/install/?ref=hf

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