Crusoe Cloud is live · pricing from $0.04/vcpu-hr · last verified 6 Nov 2026 · viability monitor
Crusoe Cloud
Crusoe Cloud GPU instances, serverless inference, and fine-tuning priced for AI teams that want orchestration included
Verified 8d ago · liveness 67/100 · cite: rightaichoice.com/tools/crusoe-cloud
- AI teams that want Managed Kubernetes or Managed Slurm included rather than assembled piecemeal
- Teams fine-tuning open models on proprietary data who want per-token training pricing over cluster provisioning
- Platform teams serving DeepSeek, GLM, Qwen, or Nemotron models at production traffic
- ML teams that want experiment tracking and reinforcement learning on the same cloud as their GPUs — Managed MLflow and Managed RL
- Teams that need managed databases, queues, or commodity compute on the same invoice
- Price-only buyers benchmarking raw $/GPU-hour against specialized spot GPU marketplaces
- Shops without the engineering depth to consume raw GPU instances or their own orchestration
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Skip Crusoe Cloud if you need managed databases, queues and commodity compute on one invoice alongside your GPUs, or if you want to self-serve the newest Blackwell Ultra and MI355X capacity today rather than open a sales conversation.
Spot pricing is contact-sales on every GPU model, so you cannot budget interruption discounts self-serve — the cheapest capacity tier has no published number.
On-demand GPU rates fit teams spending from a few hundred dollars a month up through sustained training budgets: L40S at $1.50/GPU-hr keeps experimentation cheap, H100 at $4.50/GPU-hr sits in the same band as specialist GPU clouds, and serverless tokens at $0.05 per 1M input undercut running your own endpoint. The economics get better only through reserved commitments and AMUs, both sales-negotiated — so compare against hyperscaler reserved terms, not list hourly rates.
In short
Crusoe Cloud — Crusoe Cloud GPU instances, serverless inference, and fine-tuning priced for AI teams that want orchestration included. Best for AI teams that want Managed Kubernetes or Managed Slurm included rather than assembled piecemeal, Teams fine-tuning open models on proprietary data who want per-token training pricing over cluster provisioning, Platform teams serving DeepSeek, GLM, Qwen, or Nemotron models at production traffic. Plans from $0.04/vcpu-hr.
No head-to-head comparison for Crusoe Cloud yet — the alternatives below are the closest matches we list.
What is Crusoe Cloud?
Crusoe Cloud — Crusoe Cloud GPU instances, serverless inference, and fine-tuning priced for AI teams that want orchestration included. Best for AI teams that want Managed Kubernetes or Managed Slurm included rather than assembled piecemeal, Teams fine-tuning open models on proprietary data who want per-token training pricing over cluster provisioning, Platform teams serving DeepSeek, GLM, Qwen, or Nemotron models at production traffic. Plans from $0.04/vcpu-hr.
Crusoe Cloud is an AI-only cloud with two surfaces: raw GPU/CPU instances (with Managed Kubernetes or Managed Slurm on top) and Crusoe Intelligence Foundry for Managed Inference, Serverless Fine-Tuning, and dedicated deployments. The GPU rate card runs from A100 80GB at $2.00/GPU-hr (PCIe) or $2.30 (SXM), L40S at $1.50, AMD MI300X at $3.45, H100 HGX at $3.90, H200 HGX at $4.29, and B200 HGX at $8.96; Vera Rubin NVL72, GB300 NVL72, B300 HGX, and MI355X route through sales. CPU starts at $0.04/vCPU-hr, object storage at $0.06/GiB-month, and Managed Kubernetes at $0.10 per cluster hour. New in October 2026: Managed RL and Managed MLflow bring reinforcement-learning and experiment tracking onto the same platform. Above the metal, Serverless Inference bills per token by model. DeepSeek V4 Pro sits at $1.74 in / $3.48 out per 1M tokens, GLM-5.3 at $1.40 / $4.40, GPT-OSS 120B at $0.05 / $0.25, and Nemotron 3.5 Super VL handles text, image, and video at $0.10 / $0.40. Serverless Fine-Tuning prices training the same way, from $0.40 per 1M tokens on Llama 3.1 8B, Nemotron 3.5 Lightning, and the small Qwen builds up to $10.00 on GLM-5.2 and GLM-5.3. Self-Serve Deployments give you a dedicated endpoint without a sales call: H100 80GB at $5.50/GPU-hr, H200 at $6.00, B200 at $9.65, and MI355X at $7.70. Who it fits: teams training or serving open models who would rather have orchestration included than bolted together. We'd point ML platform teams here when the alternative is a bare GPU marketplace plus a DIY Slurm story. The bet underneath is Crusoe's own data centers and power contracts; the September 2026 $3.9B Series F is funding that buildout.
Key features
- NVIDIA B200 180GB HGX on-demand at $8.96/GPU-hr
- NVIDIA H200 141GB HGX at $4.29/GPU-hr and H100 80GB HGX at $3.90/GPU-hr
- AMD MI300X 192GB at $3.45/GPU-hr; L40S at $1.50 and A100 at $2.00–$2.30
- MI355X 288GB, Vera Rubin NVL72, GB300 NVL72, B300 HGX via sales
- Spot pricing on every GPU model via sales
- Crusoe Managed Kubernetes at $0.10 per cluster hour
- Crusoe Managed Slurm and fault-tolerant Crusoe AutoClusters
- Serverless Inference with per-token input, output, and cached-input pricing
- Serverless Fine-Tuning from $0.40 to $10.00 per 1M training tokens
- Self-Serve Deployments: dedicated H100 endpoint at $5.50/GPU-hr without a sales call
- Tailored Deployments with dedicated, benchmarked endpoints
- Provisioned Throughput sold as AI Model Units (AMUs) with commitment discounts
- Managed RL for reinforcement-learning training on open models (launched Oct 2026)
- Managed MLflow for experiment tracking on Crusoe Cloud (launched Oct 2026)
- Model hub with DeepSeek V4.x, GLM-5.3, Gemma 4, Qwen 3.x, Llama 3.x, GPT-OSS, and Nemotron 3
Behind the verdict
Pick Crusoe when the job is open models end to end: prep data, fine-tune, serve, and track experiments without stitching four vendors together. The October 2026 launch of Managed RL and Managed MLflow closes a gap that used to push teams to Databricks or a DIY stack, and the per-token fine-tuning prices stay low enough that small models (Llama 3.1 8B, Nemotron 3.5 Lightning, Qwen3.5 4B, all at $0.40/1M training tokens) are close to impulse-buy territory. Where it bites: this is an AI-only cloud. No managed Postgres, no queues, no commodity compute on the same invoice. If your product needs those next to the GPUs, you are running two vendors and reconciling two bills. Price-only buyers benchmarking raw $/GPU-hour against specialist spot marketplaces will also find cheaper headline numbers elsewhere — Crusoe sells the orchestration and the data-center story, not the lowest possible hourly rate. Frontier silicon is still a sales conversation. Vera Rubin, GB300 NVL72, B300 HGX, and MI355X sit behind Contact Sales, with spot on every model also routed through the team. Teams that want to swipe a card for the newest hardware today will be disappointed; teams planning a quarter ahead won't care. The closest alternative depends on what you're weighing. Against a hyperscaler, Crusoe wins on AI-specific orchestration and loses on breadth. Against a bare GPU marketplace, it wins on managed Kubernetes and Slurm, serverless inference, and fine-tuning — and loses on raw $/hr. In practice, we'd reach for Crusoe when a team has more model work than infrastructure work, and the ops headcount saved on Managed Kubernetes at $0.10 per cluster hour outweighs the per-hour premium. One caveat worth naming: the recent engineering posts (quantized-weight fine-tuning math, larger
Models under the hood
as of 2026-11-08
Limitations
- Crusoe Cloud is a GPU/compute-first platform: GPU instances, Managed Inference, Serverless Fine-Tuning and Managed Kubernetes are the core offerings, with spot pricing shown as a separate rate class from on-demand.
- Many headline items — including GB300 NVL72, Vera Rubin NVL72, AMD MI355X, Tailored Deployments and Provisioned Throughput — route through a sales conversation rather than self-serve checkout.
- Fine-tuning rates vary by model (from $0.40 to $10.00 per 1M training tokens), so repeated runs on larger models add up.
- Self-serve hourly GPU pricing is available, but guaranteed capacity and volume commitments require sales engagement.
as of 2026-10-19
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Is Crusoe Cloud still active?
Crusoe Cloud is live · pricing from $0.04/vcpu-hr · last verified 6 Nov 2026 · viability monitor.
Viability score
How well maintained and how widely used is Crusoe Cloud? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What's new in Crusoe Cloud
Checked 5 days agoAcross the latest 10 updates: 2 launches and 8 news mentions.
Making room for bigger fine-tuning datasets
Crusoe engineering post on supporting larger fine-tuning datasets on Crusoe Cloud.
From data center to cloud: Crusoe announces new capabilities across its vertically integrated infrastructure
Crusoe announced new capabilities spanning its data center and cloud infrastructure.
Open models, end to end: Introducing Crusoe Managed RL and Managed MLflow
Crusoe launched Managed RL and Managed MLflow on Crusoe Cloud, pitched as end-to-end support for open models.
AI infrastructure spend: a framework for evaluating cost, risk, and vendor choice
Crusoe published a framework for evaluating AI infrastructure cost, risk and vendor choice.
Quantized weights, full precision: The math behind 75% cheaper fine-tuning
Crusoe engineering post explaining a method it says cuts fine-tuning cost by 75%.
Crusoe Spark AI factories achieve NVIDIA Exemplar-level performance
Crusoe said its Spark AI factories reached NVIDIA Exemplar-level performance.
Crusoe expands NVIDIA DSX collaboration with open-source NVIDIA Run:ai
Crusoe expanded its NVIDIA DSX collaboration and added open-source NVIDIA Run:ai support.
How green is Crusoe's inference engine?
Crusoe engineering post on the environmental profile of its inference engine.
GPU programming with Triton, part 1
First part of a Crusoe engineering series on GPU programming with Triton.
White glove tokenization for frontier models
Crusoe engineering post on tokenization support for frontier models.
What do users say about Crusoe Cloud?
What people actually say about Crusoe Cloud — is it worth it?
We scanned public community sources for Crusoe Cloud on Oct 11, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 0 of the posts we fetched could be positively tied to Crusoe Cloud. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
How we verified this
Every listed fact about Crusoe Cloud — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 6 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Crusoe Cloud 23 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed models, pricing page, limitations
- — changed link health, our verdict, integrations, who should skip it, pricing tiers, description, who it suits, summary, features
- — changed pricing page
- — changed integrations, description, pricing tiers, features, who should skip it, who it suits, summary, our verdict, models, platforms, limitations, pricing page
- — changed limitations, switching out, switching in, use cases, summary, description, who should skip it, setup time, pricing fit, our verdict, who it suits, pricing tiers, features, hidden costs, models
- — changed summary, features, who should skip it, description, who it suits, pricing tiers, our verdict
Showing the 6 most recent of 23 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Crusoe Cloud cost in 2026?
Crusoe Cloud: Plans from $0.04/vcpu-hr. Pricing last verified 6 Nov 2026.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Crusoe Cloud's pricing actually pencils out — and where peers do it cheaper.
On-demand GPU rates fit teams spending from a few hundred dollars a month up through sustained training budgets: L40S at $1.50/GPU-hr keeps experimentation cheap, H100 at $4.50/GPU-hr sits in the same band as specialist GPU clouds, and serverless tokens at $0.05 per 1M input undercut running your own endpoint. The economics get better only through reserved commitments and AMUs, both sales-negotiated — so compare against hyperscaler reserved terms, not list hourly rates.
Has Crusoe Cloud's pricing changed?
No plan price for Crusoe Cloud has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Crusoe Cloud?
Pick Crusoe Cloud if you are AI teams that want Managed Kubernetes or Managed Slurm included rather than assembled piecemeal, Teams fine-tuning open models on proprietary data who want per-token training pricing over cluster provisioning, Platform teams serving DeepSeek, GLM, Qwen, or Nemotron models at production traffic, ML teams that want experiment tracking and reinforcement learning on the same cloud as their GPUs — Managed MLflow and Managed RL.
Look elsewhere if you are Teams that need managed databases, queues, or commodity compute on the same invoice, Price-only buyers benchmarking raw $/GPU-hour against specialized spot GPU marketplaces, Shops without the engineering depth to consume raw GPU instances or their own orchestration, Anyone who needs frontier silicon (Vera Rubin, GB300, B300, MI355X) self-serve today — those route through sales.
Skip it if Skip Crusoe Cloud if you need managed databases, queues and commodity compute on one invoice alongside your GPUs, or if you want to self-serve the newest Blackwell Ultra and MI355X capacity today rather than open a sales conversation.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Crusoe Cloud actually fits — and what changes day-one when you adopt it.
You upload proprietary data to Serverless Fine-Tuning, pick Qwen3.5 9B at $0.40 per 1M training tokens, and get back an improved model without provisioning a cluster.
Outcome: A fine-tuned model in hours instead of a multi-day cluster setup, billed per training token rather than per GPU-hour.
You serve GPT-OSS 120B through Serverless Inference at $0.05 input / $0.25 output per 1M tokens, then move the hottest route to a Self-Serve Deployment on H100 at $6.30/GPU-hr as traffic grows.
Outcome: Cost-per-token stays low at burst traffic and latency becomes predictable on dedicated capacity, with no sales call in either step.
You book an HGX B200 or GB200 NVL72 cluster through sales, run distributed training on Crusoe Managed Slurm, and rely on AutoClusters to survive node failure mid-run.
Outcome: A long training job that does not restart from scratch on a single node fault, with RDMA networking and accelerated storage underneath.
Use cases
- Fine-tune GLM 5.2 or DeepSeek V4 Flash on proprietary data at $5.00-$10.00 per 1M training tokens with no cluster provisioning.
- Serve GPT-OSS 120B at $0.05 per 1M input tokens for high-volume, cost-sensitive workloads.
- Run DeepSeek V4 Pro inference at $1.74 input / $3.48 output per 1M tokens for reasoning-heavy applications.
- Spin up a dedicated H100 endpoint at $6.30/GPU-hr self-serve when serverless latency is not enough.
- Train large models on GB200 NVL72 or HGX B200 clusters with RDMA networking and AutoCluster fault tolerance.
- Replace hand-rolled Kubernetes with Crusoe Managed Kubernetes at $0.10 per cluster hour.
- Run long distributed training jobs that survive node failure using Crusoe AutoClusters.
- Wire Crusoe-hosted models into an agent built with Pydantic AI.
Setup time & first value
How long it actually takes to get something useful out of Crusoe Cloud — broken out by persona, not the marketing-page minute.
Serverless Inference and Serverless Fine-Tuning are the fast paths — a token-priced endpoint or a fine-tuning job can be running the same day. Self-Serve Deployments on H100 or H200 take minutes to spin up once you have an account. Raw GPU instances with Managed Kubernetes at $0.10 per cluster hour take an afternoon for a platform engineer. GB200 NVL72, MI355X and Provisioned Throughput start
Switching to or from Crusoe Cloud
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a hyperscaler GPU bill: move inference traffic to Serverless Inference at $0.05-$1.74 per 1M input tokens, then shift training to on-demand H100 or H200 instances.
- →From a raw GPU marketplace: keep your containers and layer Crusoe Managed Kubernetes at $0.10 per cluster hour or Managed Slurm over the same images.
- →From self-managed Slurm on bare metal: move the scheduler to Crusoe Managed Slurm and add AutoClusters for fault tolerance on long jobs.
- →From a vLLM deployment you operate: move open-model serving to Self-Serve Deployments from $6.30/GPU-hr and drop the ops burden.
- ↗To a hyperscaler: re-point inference traffic and drain Self-Serve Deployments, since Crusoe holds no managed database or queue state to export.
- ↗To another GPU cloud: export model weights and container images from Crusoe's registry ($0.10 per GiB/month) and rebuild the cluster on the target.
- ↗To a model API provider: swap the base URL for any model served through Crusoe Serverless Inference, since billing is per token and stateless.
Integrations
Resources & guides
- Resourcecrusoe.ai
Serving Llms On Crusoe With Kserve From Zero To 6000 Tokens Second
Helpful link from crusoe.ai
- Resourcecrusoe.ai
How to run an AI coding agent on Crusoe with OpenCode
Helpful link from crusoe.ai
- Resourcecrusoe.ai
Slurm on Crusoe Managed Kubernetes: How we built managed GPU training infrastructure
Helpful link from crusoe.ai
- Resourcecrusoe.ai
Self-healing distributed Pytorch training with Slurm on Crusoe Managed Kubernetes
Helpful link from crusoe.ai
Tutorials & Learning
YouTube returned 6 videos for “Crusoe Cloud”, and we withheld 6: 6 could not be judged, because “Crusoe Cloud” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Crusoe Cloud.
Official links
What are the best Crusoe Cloud alternatives?
The closest alternatives to Crusoe Cloud we list are Modal, RunPod and Fireworks AI. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Modal | Freemium | Pricing not published | — |
| RunPod | Paid | Pricing not published | — |
| Fireworks AI | Freemium | Pricing not published | — |
Alternatives to Crusoe Cloud
View allModal
Modal's serverless GPU cloud runs Python functions and sandboxes with per-second billing, spinning up GPU inference and agent compute from
RunPod
Rent GPU pods, Serverless inference endpoints and multi-node GPU clusters by the second on Runpod's AI developer cloud.
Fireworks AI
Fireworks AI runs open-model inference, ensembling and fine-tuning on one platform at per-token prices.
Tools that pair well with Crusoe Cloud
Common stack mates teams adopt alongside Crusoe Cloud, with the specific reason each pairing earns its keep.
Modal
Modal's serverless GPU cloud runs Python functions and sandboxes with per-second billing, spinning up GPU inference and agent compute from
RunPod
Rent GPU pods, Serverless inference endpoints and multi-node GPU clusters by the second on Runpod's AI developer cloud.
Fireworks AI
Fireworks AI runs open-model inference, ensembling and fine-tuning on one platform at per-token prices.
Frequently asked questions
Our FAQ answer written Oct 19, 2026 quotes $3.45, which no longer matches the verified price table, so it is being re-reviewed and is not shown.
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