Crusoe has staked out a unique position in GPU cloud: AI-only data centers drawing from a mix of renewable sources and natural gas capture, combined with an AI-only focus and long-term capacity contracts. Their 2026 deals linked to Stargate have put them in front of every enterprise AI procurement conversation. That differentiation is real, not marketing spin.
Crusoe publishes on-demand pricing: H100 at $3.90/hr and H200 at $4.29/hr. Spheron's H100 SXM5 starts at $3.10/hr on-demand. At the same SKU, Spheron is about 20% cheaper, and the comparison is verifiable without a sales call. Beyond price, the differences that matter are scale, sustainability sourcing, and which billing model fits your workload.
Crusoe Cloud Overview: Sustainable Energy Focus, AI-Only Infrastructure, and 2026 Scale
Crusoe's origin story starts at natural gas wellheads. Oil and gas operations often flare methane that cannot be economically piped to market. Crusoe's early mobile data centers captured that waste gas, burned it in generators on-site, and converted the output into GPU compute. The emissions argument is that burning methane for useful compute is cleaner than atmospheric release or open-air flaring.
That stranded-gas model was the foundation, but Crusoe's energy mix has since expanded significantly. Their current infrastructure draws from wind, solar, hydropower, geothermal, and natural gas across multiple facilities, with carbon capture and storage in development. Stranded gas was the origin story and remains part of the mix, but it is no longer the whole picture. As they raised more capital and chased larger contracts, they expanded into purpose-built AI data centers in fixed locations. The Stargate-linked capacity deals, announced in 2025 and 2026, include grid-connected facilities where the energy sourcing is broader.
Their AI-only positioning is consistent: Crusoe does not chase general cloud workloads, storage, or networking services. Every GPU rack is tuned for ML training. That focus means the infrastructure is well-optimized for large training clusters. For smaller or shorter workloads, they do offer on-demand access to H100 and H200, but their reserved-contract model is where they focus for enterprise scale.
Spheron Overview: On-Demand GPU Access Without Commitment
Spheron aggregates bare-metal GPU capacity from vetted data center partners globally and presents it through a single pricing interface. The model is fundamentally different from Crusoe's: no reserved contracts, no multi-month commitments, per-minute billing, and instant provisioning.
You pick a GPU model, choose on-demand or spot pricing, and have a live instance in minutes. Full root access. No negotiation with a sales team. The catalog covers H100, H200, B200, A100, L40S, RTX 4090, RTX 5090, and other SKUs. Check live GPU pricing for current availability and rates.
Spot pricing is available for interruptible workloads where you can checkpoint and resume. Spot instances are cheaper than on-demand and appropriate for training jobs that tolerate occasional preemption.
GPU SKU Availability: Who Actually Has B200 Today
| GPU Model | Spheron Availability | Crusoe Availability |
|---|---|---|
| H100 SXM5 80GB | On-demand, instant | On-demand ($3.90/hr) |
| H100 PCIe 80GB | On-demand | Limited |
| H200 SXM 141GB | On-demand, spot | On-demand ($4.29/hr) |
| B200 SXM | Check live pricing | Announced, contact sales |
| A100 80GB | On-demand | Limited |
| L40S 48GB | On-demand | Not standard catalog |
Crusoe offers on-demand access to H100 and H200. For B200, GB200, and MI355x, availability is limited and requires a sales conversation. Spheron's full catalog is accessible on-demand with no prior contract or commitment. For a detailed performance and specs comparison between the H100 SXM5 and H200, see our NVIDIA H100 vs H200 guide.
Pricing Comparison: On-Demand and Reserved
Crusoe publishes on-demand pricing for H100 and H200. B200 and newer generations require a sales conversation. The table below reflects both platforms' published rates as of 06 May 2026. For a side-by-side GPU cloud pricing comparison across 15+ providers, including on-demand, spot, and reserved tiers, see the full breakdown.
| GPU Model | Spheron On-Demand | Spheron Spot | Crusoe On-Demand | Crusoe Reserved |
|---|---|---|---|---|
| H100 SXM5 | $3.10/hr | N/A | $3.90/hr | Contact sales |
| H200 SXM on Spheron | $2.51/hr | $1.19/hr | $4.29/hr | Contact sales |
| B200 SXM | Spot only | $2.06/hr | Contact sales | Contact sales |
| A100 80GB | $1.04/hr | N/A | Not listed | Contact sales |
Pricing fluctuates based on GPU availability. The prices above are based on 06 May 2026 and may have changed. Check current GPU pricing → for live rates.
Real-World Cost Scenario
Running 8x H100 SXM5 for 200 hours per month at published on-demand rates:
- Spheron on-demand: 8 x $3.10 x 200 = $4,960/month
- Crusoe on-demand: 8 x $3.90 x 200 = $6,240/month
That is a $1,280/month saving (~20%) using Spheron at the same H100 SKU, both at published rates with no contract required. No opaque quotes or sales conversations needed to verify the math.
Networking Architecture: InfiniBand vs RoCE
Crusoe's Stargate-scale clusters use InfiniBand (HDR or NDR) for maximum all-reduce bandwidth during distributed training. InfiniBand HDR delivers approximately 200 Gb/s per port with microsecond-level latency, which matters when you are running all-reduce across hundreds of GPUs during large model training.
Spheron uses RoCE (RDMA over Converged Ethernet) for multi-GPU configurations. RoCE v2 delivers 100-200 Gb/s and is the standard interconnect for multi-GPU configurations up to 8 GPUs. For NVLink-connected 8x GPU nodes, intra-node bandwidth is the same regardless of the external interconnect.
Practical framing:
- For 100+ GPU frontier training with tight all-reduce performance requirements, InfiniBand matters and Crusoe's infrastructure is purpose-built for it.
- For 1-8 GPU inference, fine-tuning, or training up to 70B parameters, RoCE is effectively equivalent. The bottleneck is not the interconnect.
For more context on how topology choices affect workload selection, see our guide on serverless GPU vs on-demand vs reserved which covers multi-node considerations in depth. If you are still deciding on the right GPU cloud approach for your use case, the GPU cloud AI buyer's guide covers the key decision criteria.
Sustainability Claims: What Each Company Actually Verifies
| Claim | Crusoe | Spheron |
|---|---|---|
| Primary energy source | Wind, solar, hydropower, geothermal, natural gas (stranded gas origin); carbon capture and storage in development | Grid-connected data centers, region-dependent |
| PUE claim | Not prominently published | Depends on partner facility |
| Third-party verification | Partial (lifecycle emissions reports) | Standard Tier 2/3 compliance per facility |
| Net emissions argument | Methane-capture logic: burning waste gas beats atmospheric release | N/A, no green energy claim made |
| Grid-connected proportion | Growing as they expand | Majority |
The nuance in Crusoe's sustainability story matters here. Their methane capture argument is strongest for mobile data centers deployed directly to active flare sites. In that original model, the alternative is not clean energy, it is methane vented or flared into the atmosphere. Using it for GPU compute does reduce net emissions.
Crusoe's current energy mix has expanded well beyond stranded gas. Their infrastructure now draws from wind, solar, hydropower, geothermal, and natural gas, with carbon capture and storage in development. Stranded gas was the origin story and remains part of the mix, but it is no longer the dominant narrative. As they scale into large fixed facilities tied to Stargate and similar programs, grid-connected power makes up a growing share. Crusoe continues to publish lifecycle emissions reports, but third-party verification is partial and varies by facility.
Spheron does not make sustainability claims. If green energy sourcing matters for your compliance reporting, verify directly with the underlying facility operators. No misleading green marketing, but also no certified renewable energy claim.
Contract Terms and Billing Granularity
| Term | Spheron | Crusoe |
|---|---|---|
| Minimum commitment | None | Multi-month reserved blocks (varies) |
| Billing unit | Per minute | Per minute (on-demand) / Per hour or per day (reserved) |
| On-demand availability | Yes, full catalog | Yes (H100, H200); B200+ requires sales |
| Reserved discounts | Spot pricing for interruptible workloads | Significant discounts for committed capacity |
| Contract structure | No contracts | Enterprise agreements required for scale |
| Cancellation | Stop any time | Contract terms apply |
For on-demand workloads, billing granularity is comparable: Spheron bills per-minute and Crusoe bills per-minute, so short-job overhead is minimal on both. The gap opens when comparing Spheron on-demand against Crusoe's reserved blocks, which commit capacity per-day or per-block regardless of actual job duration. A 47-minute fine-tuning run under a Crusoe reserved allocation still charges for the full reserved unit. On Spheron's per-minute on-demand pricing, that same run costs exactly 47 minutes at $3.10/hr.
Platform Feature Comparison
| Feature | Spheron | Crusoe | Winner |
|---|---|---|---|
| On-demand access | Yes, full catalog | Yes (H100, H200) | Comparable |
| H100 pricing | $3.10/hr | $3.90/hr | Spheron (~20% cheaper) |
| Minimum commitment | None | Multi-month reserved | Spheron |
| Contract required | No | Yes for scale | Spheron |
| GPU catalog breadth | H100, H200, B200, A100, L40S, RTX series | H100, H200, B200 (AI-focused) | Comparable |
| B200 availability | Check live | Announced/reserved | Comparable |
| Multi-GPU (8x) | NVLink + RoCE | NVLink + InfiniBand | Tie |
| 100+ GPU clusters | Up to 8x per job | Hundreds (reserved) | Crusoe |
| Sustainability claim | No claim | Stranded gas / methane | Crusoe (if verified matters) |
| Billing granularity | Per minute | Per minute (on-demand) / block (reserved) | Spheron (vs reserved) |
| Setup time | Minutes | Days to weeks (reserved onboarding) | Spheron |
| Vendor lock-in | Minimal (multi-provider) | Moderate (contract terms) | Spheron |
Use-Case Decision Guide
Choose Spheron if you need:
- On-demand H100 on-demand rental with no reserved block commitment
- Per-minute billing for workloads under 200 hours/month where reserved contracts do not break even
- Fast provisioning: training runs, fine-tuning, inference serving that needs to start today
- Budget predictability without negotiating enterprise contracts
- Spot pricing for checkpointable training workloads
- Access to GPU models beyond the AI-data-center tier (RTX 4090, RTX 5090, A100 PCIe)
- A transparent cost comparison before committing. See also our Spheron vs CoreWeave comparison for a similar breakdown against another enterprise-focused provider
Choose Crusoe if you need:
- Reserved multi-GPU cluster capacity across 100+ GPUs for frontier model training
- Sustainability reporting that specifically cites stranded gas and methane capture in your supply chain
- Long-term capacity guarantees tied to large AI infrastructure programs
- Stargate-affiliated access with dedicated cluster allocations
Choose both:
Use Spheron for inference, fine-tuning, experimentation, and burst capacity. Use Crusoe for long-running frontier training under a reserved contract if your scale justifies the commitment. The workloads are different enough that many teams can use both without overlap.
Conclusion
- Crusoe's sustainability story started with stranded gas, which remains part of their energy mix. Their current infrastructure spans wind, solar, hydropower, geothermal, and natural gas, with carbon capture and storage in development. The methane-capture argument holds up for original mobile data centers; the story is more complex for their grid-connected fixed facilities.
- Crusoe publishes on-demand H100 at $3.90/hr and H200 at $4.29/hr. Spheron's H100 SXM5 is $3.10/hr on-demand, roughly 20% cheaper at the same SKU. For B200 and newer hardware, Crusoe requires a sales conversation; Spheron lists spot pricing directly.
- Spheron's per-minute billing and no-contract model make it the practical choice for most AI teams. Running 8x H100 for 200 hours saves $1,280/month on Spheron vs Crusoe at published on-demand rates.
- B200 availability at Spheron is live on spot pricing; H200 is available both on-demand and spot. At Crusoe, B200 is gated behind reserved allocation processes.
- If sustainability compliance specifically requires stranded-gas provenance in your supply chain, Crusoe has a documented argument. If you just want clean, honest GPU pricing with no commitments, Spheron covers that.
For teams ready to start today, check current GPU pricing at Spheron and deploy from app.spheron.ai.
Crusoe's reserved contracts make sense when you are training frontier models for months at a time. For inference, fine-tuning, and on-demand GPU access without a commitment, Spheron covers the same hardware at published, per-minute rates.
H100 GPU on Spheron → | H200 GPU pricing → | View all GPU pricing →
Frequently Asked Questions
Crusoe publishes on-demand H100 pricing at $3.90/hr with per-minute billing. Spheron's H100 SXM5 is $3.10/hr with per-minute billing and no minimum commitment. At the same SKU, Spheron is about 20% cheaper. Both platforms publish their rates, so the comparison is verifiable without a sales call.
Yes. Crusoe offers three pricing modes: on-demand, spot, and reserved. On-demand H100 is $3.90/hr and H200 is $4.29/hr, both with per-minute billing. B200 and newer models require a sales conversation. Most of Spheron's catalog is on-demand with no contracts. H100, H200, and A100 are available on-demand with per-minute billing; B200 is currently spot-only. Spot pricing is available for interruptible workloads.
Crusoe publishes lifecycle emissions data and has disclosed methane capture metrics, but third-party verification varies by facility. Their core claim - that using otherwise-flared gas for compute reduces net emissions - has been validated in principle by academic and industry analyses. The key caveat: as Crusoe scales into grid-connected data centers (including Stargate-tied facilities), the proportion of stranded-gas power vs grid power changes. Spheron does not make a stranded-gas claim, but also does not make misleading green claims.
Spheron supports multi-GPU configurations with NVLink interconnects, covering most fine-tuning and training workloads up to 70B+ parameters. Crusoe's Stargate-scale infrastructure is built for frontier model training across hundreds of GPUs on InfiniBand fabrics. For teams that genuinely need that scale, Crusoe's reserved cluster model is purpose-built. For the other 90%+ of AI teams, Spheron's on-demand access at lower cost covers the use case.
Crusoe has announced B200 deployments as part of their Stargate-affiliated capacity expansion, but availability through standard channels is limited and typically reserved for committed customers. Spheron's B200 availability can be checked live at spheron.network/pricing/.
For inference, Spheron's on-demand model is typically more cost-effective. Inference workloads are bursty and difficult to forecast - paying only for what you use matters more than reserved discounts. Crusoe's reserved model benefits training workloads where you can predict utilization weeks in advance. For high-throughput inference serving, Spheron's per-minute billing and instant provisioning are structural advantages.
