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Amazon Bedrock vs Groq
Bedrock trades raw speed for breadth and AWS governance. Groq trades breadth for speed, serving a small catalog at 500 to 1,000 tokens per second on its own LPU chip.
By The Subconscious Team · Updated
Amazon Bedrock vs Groq: key differences
Groq is a speed specialist. Its LPU keeps weights in on-chip SRAM, and Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B, with tight tail latency that suits strict SLAs. The catalog is small and shrinking, with Llama 3.3 70B and Llama 3.1 8B shut down in August 2026, and context tops out around 131K. Bedrock is the opposite design: 100+ models, closed and open, with AWS security on every call and fine-tuning, Knowledge Bases, Guardrails and AgentCore around them.
Pick Groq for the latency-bound steps: voice agents where any pause reads as awkward, and multi-call loops where each step must return fast. Pick Bedrock for everything that needs Claude or GPT, long contexts, governance or managed agent tooling. Many teams could route a fast inner step to Groq and keep the rest on Bedrock. Groq also carries a strategic question: NVIDIA licensed the LPU and hired most of its staff in December 2025, so long-term investment in GroqCloud is uncertain.
What Amazon Bedrock and Groq do
Amazon Bedrock
Amazon Bedrock is AWS's managed model service and has become the default AI control plane for many enterprises. One API reaches 100+ models from 18+ providers, including Anthropic's Claude family, Meta, Mistral, DeepSeek, Amazon's own Nova models, and, since an April 2026 partnership expansion, OpenAI models up to GPT-6 Astra. Switching models is usually just a new model ID. Every call inherits IAM, PrivateLink, KMS encryption and CloudTrail logging, and provider models never train on customer data.
Example models: Claude Opus, GPT-6 Astra
Full Amazon Bedrock profileGroq
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.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq profileShould you choose Amazon Bedrock or Groq?
Amazon Bedrock
Choose Amazon Bedrock for
- Frontier closed models with enterprise controls.
- Long-context work beyond Groq's roughly 131K cap.
- Fine-tuning and custom model import.
Groq
Choose Groq for
- Voice agents that need minimal pauses.
- Fast inner steps in multi-call agent loops.
- Predictable tail latency under strict SLAs.
Amazon Bedrock vs Groq at a glance
| Attribute | Amazon Bedrock | Groq |
|---|---|---|
| Model access | Closed and open, 100+ models | Open weights |
| Flagship models | Claude, GPT-6 Astra, Nova, DeepSeek | GPT-OSS 120B, Qwen 3.6 27B |
| Speed | Latency-optimized option on some models | 500–1,000 tok/s |
| Price | ~20–35% above direct; Claude at parity | Near the floor on small models |
| Customization | Fine-tuning, Custom Model Import | No fine-tuned model hosting |
| Deployment | Managed on AWS, AgentCore | GroqCloud API |
| Long context | Varies by model | Around 131K max |
Frequently asked questions
What is the difference between Amazon Bedrock and Groq?
Bedrock trades raw speed for breadth and AWS governance. Groq trades breadth for speed, serving a small catalog at 500 to 1,000 tokens per second on its own LPU chip.
When should I choose Amazon Bedrock over Groq?
Frontier closed models with enterprise controls; Long-context work beyond Groq's roughly 131K cap; Fine-tuning and custom model import.
When should I choose Groq over Amazon Bedrock?
Voice agents that need minimal pauses; Fast inner steps in multi-call agent loops; Predictable tail latency under strict SLAs.
Is Amazon Bedrock or Groq cheaper?
Amazon Bedrock: ~20–35% above direct; Claude at parity. Groq: Near the floor on small models. The cheaper choice depends on the model and workload.
Which has more context, Amazon Bedrock or Groq?
Amazon Bedrock: Varies by model. Groq: Around 131K max.
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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.