# Mistral AI vs Crusoe

> Mistral is a model lab with its own API. Crusoe is an energy-first cloud serving DeepSeek, GLM and Kimi on a shared KV cache, with LoRA tuning and raw GPUs.

Canonical: https://www.subconscious.dev/compare/mistral-ai-vs-crusoe · By The Subconscious Team · Updated September 30, 2026

## How they compare

Mistral sells its own weights. Medium 3.5 costs $1.50 in and $7.50 out per million tokens and scores 77.6% on SWE-Bench Verified by Mistral's count, Small 4 costs $0.15 in and $0.60 out, and Large 3 costs $0.50 in and $1.50 out, with context topping out at 256K. Crusoe does not train models. Its Intelligence Foundry serves DeepSeek, GLM, Kimi, Gemma, gpt-oss and Nemotron from $0.05 in and $0.20 out, on an engine with MemoryAlloy, a KV cache shared across the cluster. Crusoe claims up to 9.9x faster time to first token and 5x throughput versus vLLM on prefix-heavy work, though those are its own benchmarks. For agents that resend long shared context, that cache reuse can matter more than list price.

Customization favors Crusoe for self-serve teams. It launched LoRA fine-tuning in July 2026 and deploys the result on serverless, per-GPU-hour or tailored endpoints, and it rents raw clusters with H100 on demand at $3.90 an hour. Mistral's fine-tuning API is deprecated, and custom training goes through Forge, its enterprise pre-training, post-training and RL system. Mistral wins on distribution: the same models run on Azure, Bedrock, Vertex AI, Snowflake and watsonx, self-host on as few as four GPUs, and serve from EU or US regions with a Priority Tier SLA. Crusoe's serverless catalog is small, and its GB200, B200 and MI355X capacity needs a sales conversation.

## What each one does

### Mistral AI

Mistral AI is a Paris lab that sells its models through La Plateforme, its own API, and releases most of them as open weights. It consolidated the lineup in 2026. Mistral Medium 3.5, released April 28, is a dense 128B model that merges instruction following, reasoning and coding into one set of weights, and it replaced both Devstral 2 and the Magistral reasoning models. It costs $1.50 in and $7.50 out per million tokens and scores 77.6% on SWE-Bench Verified by Mistral's count. Mistral Small 4, a 119B mixture-of-experts model with 6.5B active, costs $0.15 in and $0.60 out. Mistral Large 3, a 675B MoE under Apache 2.0, runs $0.50 in and $1.50 out. All three carry a 256K context window.

### 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.

## Which is best, and when

### Choose Mistral AI for

- EU data residency on first-party models
- Cost-sensitive volume on Small 4
- Moving the same weights across clouds

### Choose Crusoe for

- Agents resending long shared prefixes
- Self-serve LoRA tuning and deployment
- Large GB200 or B200 clusters

## At a glance

| Attribute | Mistral AI | Crusoe |
|---|---|---|
| Model access | Open weights, plus closed Codestral | Open weights |
| Flagship models | Mistral Medium 3.5, Small 4, Large 3 | DeepSeek V4, GLM 5.3, Kimi K2.6, Nemotron 3 |
| Speed | - | Up to 9.9x faster TTFT vs vLLM (vendor claim) |
| Price | $0.15–$1.50 in, $0.60–$7.50 out per 1M | $0.05–$1.74 in, $0.20–$4.40 out per 1M |
| Customization | Forge (enterprise); fine-tuning API deprecated | Serverless LoRA fine-tuning |
| Deployment | API, Azure, Bedrock, Vertex, self-host | Serverless, self-serve and tailored dedicated, raw GPUs |
| Long context | 256K | Varies by model; cluster-wide KV cache |

## FAQ

### What is the difference between Mistral AI and Crusoe?

Mistral is a model lab with its own API. Crusoe is an energy-first cloud serving DeepSeek, GLM and Kimi on a shared KV cache, with LoRA tuning and raw GPUs.

### When should I choose Mistral AI over Crusoe?

EU data residency on first-party models; Cost-sensitive volume on Small 4; Moving the same weights across clouds.

### When should I choose Crusoe over Mistral AI?

Agents resending long shared prefixes; Self-serve LoRA tuning and deployment; Large GB200 or B200 clusters.

### Is Mistral AI or Crusoe cheaper?

Mistral AI: $0.15–$1.50 in, $0.60–$7.50 out per 1M. 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, Mistral AI or Crusoe?

Mistral AI: 256K. Crusoe: Varies by model; cluster-wide KV cache.

## Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs Mistral AI](https://www.subconscious.dev/compare/subconscious-vs-mistral-ai.md), [Subconscious vs Crusoe](https://www.subconscious.dev/compare/subconscious-vs-crusoe.md).

Full profiles: [Mistral AI](https://www.subconscious.dev/providers/mistral-ai.md), [Crusoe](https://www.subconscious.dev/providers/crusoe.md).