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Fireworks AI vs Crusoe
Fireworks sells measured speed and deep post-training on 400+ open models. Crusoe sells owned capacity, a cluster-wide KV cache and a smaller serverless list.
By The Subconscious Team · Updated
Fireworks AI vs Crusoe: key differences
Both serve DeepSeek V4 Pro and other open models through OpenAI-compatible APIs, but they prove speed differently. Fireworks has posted 167 to 174 tokens per second on DeepSeek V4 Pro in third-party measurements and serves its full 1M context. Crusoe's figure is a vendor claim: up to 9.9x faster time to first token and 5x throughput versus vLLM on prefix-heavy work, thanks to MemoryAlloy, a KV cache shared across the cluster. Catalog size is lopsided. Fireworks lists 400+ models across text, vision, audio and embeddings. Crusoe's serverless catalog covers DeepSeek, GLM, Kimi, Gemma, gpt-oss and Nemotron, priced from $0.05 in and $0.20 out per million, with cached input well below list.
Fireworks wins on post-training. It runs SFT, DPO and reinforcement fine-tuning in LoRA or full-parameter form, serves fine-tunes at base-model prices, and its Training API went GA on August 31, 2026. Crusoe has offered serverless LoRA fine-tuning since July 2026. On dedicated hardware Crusoe is cheaper: self-serve H100 deployments run $5.50 per GPU-hour and raw H100s $3.90, while Fireworks raised dedicated H100s to $8 an hour on September 1. Crusoe also rents raw GB200, B200 and MI355X clusters with Kubernetes or Slurm. Fireworks holds SOC 2, HIPAA and ISO certifications. Choose Fireworks for proven throughput and RL on open models. Choose Crusoe for cheaper dedicated capacity and agents that resend the same long prefixes.
What Fireworks AI and Crusoe do
Fireworks AI
Fireworks AI was founded in 2022 by former Meta PyTorch engineers led by CEO Lin Qiao, and it sells speed on open models. Its custom serving stack has posted 167 to 174 tokens per second on DeepSeek V4 Pro in third-party measurements, several times what most GPU peers hit on the same model. The catalog holds 400+ models across text, vision, audio and embeddings, served through an OpenAI-compatible API. In July 2026 it raised a $1.505B Series D at a $17.5B valuation, with a reported $1B+ run rate and 40T+ tokens a day.
Example models: DeepSeek V4 Pro, Kimi K3
Full Fireworks AI profileCrusoe
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 profileShould you choose Fireworks AI or Crusoe?
Fireworks AI
Choose Fireworks AI for
- Third-party measured speed on DeepSeek V4 Pro
- Reinforcement fine-tuning with the Training API
- Full 1M context on DeepSeek V4 Pro
Crusoe
Choose Crusoe for
- Cheaper dedicated H100 endpoints per GPU-hour
- Prefix-heavy chat and agent traffic
- Raw GPU clusters on Kubernetes or Slurm
Fireworks AI vs Crusoe at a glance
| Attribute | Fireworks AI | Crusoe |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | DeepSeek V4 Pro, Kimi K3 | DeepSeek V4, GLM 5.3, Kimi K2.6, Nemotron 3 |
| Speed | 167–174 tok/s on DeepSeek V4 Pro | Up to 9.9x faster TTFT vs vLLM (vendor claim) |
| Price | Fine-tunes served at base price | $0.05–$1.74 in, $0.20–$4.40 out per 1M |
| Customization | SFT, DPO, RFT; Training API | Serverless LoRA fine-tuning |
| Deployment | Serverless, dedicated GPUs | Serverless, self-serve and tailored dedicated, raw GPUs |
| Long context | Full 1M on DeepSeek V4 Pro | Varies by model; cluster-wide KV cache |
Frequently asked questions
What is the difference between Fireworks AI and Crusoe?
Fireworks sells measured speed and deep post-training on 400+ open models. Crusoe sells owned capacity, a cluster-wide KV cache and a smaller serverless list.
When should I choose Fireworks AI over Crusoe?
Third-party measured speed on DeepSeek V4 Pro; Reinforcement fine-tuning with the Training API; Full 1M context on DeepSeek V4 Pro.
When should I choose Crusoe over Fireworks AI?
Cheaper dedicated H100 endpoints per GPU-hour; Prefix-heavy chat and agent traffic; Raw GPU clusters on Kubernetes or Slurm.
Is Fireworks AI or Crusoe cheaper?
Fireworks AI: Fine-tunes served at base price. Crusoe: $0.05–$1.74 in, $0.20–$4.40 out per 1M. The cheaper choice depends on the model and workload.
Which has more context, Fireworks AI or Crusoe?
Fireworks AI: Full 1M on DeepSeek V4 Pro. Crusoe: Varies by model; cluster-wide KV cache.
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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.