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Crusoe vs Inference.net
Inference.net resells spare GPU time for cheap batch and distills traces into custom models. Crusoe serves real-time traffic on capacity it builds itself.
By The Subconscious Team · Updated
Crusoe vs Inference.net: key differences
Inference.net grew from buying idle GPU time across data centers, and its Batch API still reflects that: up to 1M requests per file, completion windows from 24 hours to 7 days, and pricing that passes on the discounts it gets. Fragmented capacity suits offline work more than strict real-time SLAs. Crusoe is the opposite model. It builds campuses like the Abilene site behind Stargate and serves open models such as DeepSeek, GLM, Kimi and Nemotron on its own engine, from $0.05 in and $0.20 out per million. Its MemoryAlloy cache shares KV state across the cluster, which Crusoe says makes repeated prefixes much faster than on vLLM, a claim measured on prefix-heavy workloads.
Both sell a route to custom models, with different starting points. Inference.net's Gateway routes traffic to open, closed or custom models under one key, captures every request, and turns it into eval and training data. It then fine-tunes a task-specific model and deploys it on a dedicated GPU with a 99.99% uptime target, and its Halo optimizer suggests fixes from agent traces. Crusoe offers serverless LoRA fine-tuning, self-serve deployments per GPU-hour and tailored SLAs, but no built-in trace capture. Inference.net publishes few independent benchmarks, so buyers lean on its numbers. Crusoe's speed figures are also its own.
What Crusoe and Inference.net do
Crusoe
Crusoe started in 2018 turning wasted natural gas into power for computing and has since become a vertically integrated AI infrastructure company: it sources energy, builds data centers and rents GPUs through Crusoe Cloud. It designed and built the Abilene, Texas campus behind the OpenAI and Oracle Stargate project, planned at 1.2 GW, and in March 2026 announced an adjacent 900 MW campus for Microsoft. On September 17, 2026 it closed the first part of a $3.9B Series F at a $30.9B post-money valuation, and it reports over 6 GW of contracted capacity. Crusoe Cloud lists GB200 NVL72, B200 and AMD MI355X by quote, with H100 at $3.90 and H200 at $4.29 per GPU-hour on demand.
Example models: DeepSeek V4 Pro, GLM 5.3, Kimi K2.6
Full Crusoe profileInference.net
Inference.net started as a buyer of last resort for idle GPU time. Its scheduler aggregates small unused chunks of capacity across data centers and runs models on them, and it passes the steep discounts it gets from those data centers on to customers. That origin still shows in its OpenAI-compatible Batch API, which takes up to 1M requests per file with completion windows from 24 hours to 7 days and far higher headroom than synchronous limits.
Example models: open catalog models plus customer fine-tunes served on dedicated GPUs
Full Inference.net profileShould you choose Crusoe or Inference.net?
Crusoe
Choose Crusoe for
- Real-time chat and agents at production scale
- LoRA fine-tuning next to serving
- Raw GPU clusters with Kubernetes or Slurm
Inference.net
Choose Inference.net for
- Million-request offline batch jobs
- Distilling a closed-API workload into a small model
- Capturing production traces for evals
Crusoe vs Inference.net at a glance
| Attribute | Crusoe | Inference.net |
|---|---|---|
| Model access | Open weights | Open, closed and custom |
| Flagship models | DeepSeek V4, GLM 5.3, Kimi K2.6, Nemotron 3 | Customer fine-tunes |
| Speed | Up to 9.9x faster TTFT vs vLLM (vendor claim) | Batch windows of 24h to 7 days |
| Price | $0.05–$1.74 in, $0.20–$4.40 out per 1M | Discounted spare GPU capacity |
| Customization | Serverless LoRA fine-tuning | Distill traces into custom models |
| Deployment | Serverless, self-serve and tailored dedicated, raw GPUs | Batch API, gateway, dedicated GPUs |
| Long context | Varies by model; cluster-wide KV cache | Varies by model |
Frequently asked questions
What is the difference between Crusoe and Inference.net?
Inference.net resells spare GPU time for cheap batch and distills traces into custom models. Crusoe serves real-time traffic on capacity it builds itself.
When should I choose Crusoe over Inference.net?
Real-time chat and agents at production scale; LoRA fine-tuning next to serving; Raw GPU clusters with Kubernetes or Slurm.
When should I choose Inference.net over Crusoe?
Million-request offline batch jobs; Distilling a closed-API workload into a small model; Capturing production traces for evals.
Is Crusoe or Inference.net cheaper?
Crusoe: $0.05–$1.74 in, $0.20–$4.40 out per 1M. Inference.net: Discounted spare GPU capacity. The cheaper choice depends on the model and workload.
Which has more context, Crusoe or Inference.net?
Crusoe: Varies by model; cluster-wide KV cache. Inference.net: Varies by model.
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.