SambaNova vs Particle.AI

SambaNova

SambaNova designs its own inference chip, the Reconfigurable Dataflow Unit, and sells fast tokens on large open models through SambaCloud. The RDU maps the model graph onto the chip to cut trips to off-chip memory. A three-tier memory design of SRAM, HBM and bulk DRAM lets one system host very large models and hot swap between several of them in milliseconds. SambaCloud serves models like MiniMax M3 (in preview with a 1M context), DeepSeek V3.1, Llama 3.3 70B, Gemma 4 31B and GPT-OSS 120B, with speeds reported by Artificial Analysis.

Example models: MiniMax M3, GPT-OSS 120B, DeepSeek V3.1

Particle.AI

Particle AI is an early San Francisco infrastructure startup with a mission to make intelligence as cheap and abundant as electricity. The team works on post-training, inference optimization and distributed systems, all aimed at pushing down cost per unit of intelligence. It is still hiring its founding team and works fully in person. Mixpanel founder Suhail Doshi started it, with backing from Y Combinator, 8VC, Caffeinated Capital and angels including Patrick Collison, Adam D'Angelo and Aaron Levie.

Example models: Particle-1, DeepSeek V4.1 Flash, GLM 5.3 Flash

SambaNova

Choose SambaNova for

• Interactive agents on large open models.
• Fast decode where generation is the wait.
• Hot swapping between models in one agent.

Particle.AI

Choose Particle.AI for

• Cheap high-volume Flash-model calls.
• 1M context on small DeepSeek and GLM models.
• A fallback route in Vercel AI Gateway.