Groq vs Recurse
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Groq compared with Recurse
| Detail | Groq | Recurse |
| What it does | Premier neocloud for fast inference
| Build and deploy Agent MCP Apps
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| Stage | Established
| Growing
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| Founded | Not given
| Not given
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| Based in | US
| Not given
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| Pricing model | Not given
| usage-based
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| Pricing | Not given
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| Key features | - GroqMetal: dedicated bare-metal infrastructure tuned for speed and reliability
- GroqCore: production-ready inference stack with no infrastructure expertise required
- GroqAssured: enterprise-grade governance, auditability, and control
- 256 LPUs per rack with 40 PB/s SRAM bandwidth
- 1,000 tokens per second per user throughput
- 128 GB on-chip SRAM per rack
- 315 PFLOPS of FP8 inference compute
- 13 globally distributed data centers across four continents
| - Run agents with Python tools
- Deploy agents as MCP servers
- Validate structured inputs and outputs
- Inspect run results and artifacts
- Secrets management
- 24-hour result retention
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| What makes it different | - Fast inference at scale without sacrificing affordability
- LPU pioneered technology integrated with NVIDIA GPUs
- Fully integrated platform combining infrastructure, inference, and control
| - No subscription or idle charges for usage-based pricing
- Zero markup on model tokens
- Hosting included with deployment
- Available through MCP clients like Claude and Codex
- Full visibility into agent execution and results
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
| Not given
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | 85 ● no change since last check | 35 ● no change since last check |
| Trust Flow (Majestic) | 37 | 11 |
| Citation Flow (Majestic) | 56 | 20 |
| Referring domains (Majestic) | 12552 | 39 |
4 details filled in for both companies.
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