# Groq vs SambaNova

> Both build their own inference chips. Groq serves small open models with steady latency; SambaNova targets fast decode on much larger open models.

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

## How they compare

Groq and SambaNova both skipped GPUs. Groq's LPU holds weights in on-chip SRAM and runs a deterministic schedule, publishing 500 tokens per second on GPT-OSS 120B. SambaNova's Reconfigurable Dataflow Unit uses SRAM, HBM and bulk DRAM tiers so one system can host very large models and hot swap between them in milliseconds. That difference shows in the catalogs. Groq's is small and narrowing toward GPT-OSS and Qwen 3.6. SambaCloud serves MiniMax M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, and SambaNova claims its SN50 runs MiniMax M2.7 near 820 tokens per second.

Treat both sets of numbers with care. SambaNova's headline figures are mostly vendor benchmarks on hardware still ramping, and much of its business runs through rack sales to neoclouds. Groq's self-serve API is simpler to adopt, with per-token prices near the floor on small models, Whisper and Groq Compound. Groq caps around 131K context and hosts no fine-tunes. Choose Groq for small models where latency must be steady. Choose SambaNova when the agent needs a big open model fast.

## What each one does

### Groq

Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.

### 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 M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, with speeds reported by Artificial Analysis.

## Which is best, and when

### Choose Groq for

- Small open models with predictable tail latency
- Self-serve API access with per-token pricing
- Voice pipelines using hosted Whisper

### Choose SambaNova for

- Fast decode on large models like MiniMax M2.7
- Agents that swap between several big models
- Neoclouds buying a premium speed tier

## At a glance

| Attribute | Groq | SambaNova |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | MiniMax M2.7, GPT-OSS 120B, DeepSeek |
| Speed | 500–1,000 tok/s | ~820 tok/s on MiniMax M2.7 (SN50) |
| Price | Near the floor on small models | $0.22 in, $0.59 out (GPT-OSS 120B) |
| Customization | No fine-tuned model hosting | - |
| Deployment | GroqCloud API | SambaCloud, racks for neoclouds |
| Long context | Around 131K max | Up to 192K (MiniMax M2.7) |

## FAQ

### What is the difference between Groq and SambaNova?

Both build their own inference chips. Groq serves small open models with steady latency; SambaNova targets fast decode on much larger open models.

### When should I choose Groq over SambaNova?

Small open models with predictable tail latency; Self-serve API access with per-token pricing; Voice pipelines using hosted Whisper.

### When should I choose SambaNova over Groq?

Fast decode on large models like MiniMax M2.7; Agents that swap between several big models; Neoclouds buying a premium speed tier.

### Is Groq or SambaNova cheaper?

Groq: Near the floor on small models. SambaNova: $0.22 in, $0.59 out (GPT-OSS 120B). The cheaper choice depends on the model and workload.

### Which has more context, Groq or SambaNova?

Groq: Around 131K max. SambaNova: Up to 192K (MiniMax M2.7).

## Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs Groq](https://www.subconscious.dev/compare/subconscious-vs-groq.md), [Subconscious vs SambaNova](https://www.subconscious.dev/compare/subconscious-vs-sambanova.md).

Full profiles: [Groq](https://www.subconscious.dev/providers/groq.md), [SambaNova](https://www.subconscious.dev/providers/sambanova.md).