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Groq vs Boundless
Groq runs a small open-model catalog on its own LPU chip. Boundless serves open models with 1M context on most and resells GPT and Claude on the same API.
By The Subconscious Team · Updated
Groq vs Boundless: key differences
Groq publishes 500 tokens per second on GPT-OSS 120B and 1,000 on GPT-OSS 20B, with tight tail latency, Whisper for speech and the Groq Compound agent system. Its self-serve catalog is small, capped around 131K context, and does not host fine-tuned models. Boundless serves open models such as GLM-5.3, DeepSeek V4.1 Flash and Kimi K3, most with 1M context, plus GPT and Claude. Vercel's AI Gateway measured Boundless at 342 tokens per second on DeepSeek V4.1 Flash 1017 and 276 on GLM-5.3 Flash.
Groq is the pick for voice agents and SLAs judged on tail latency, and its small models sit near the price floor. Boundless fits long-context agent work on models like GLM-5.3 and Kimi K3, or teams that want engineers to tune a reserved deployment against contracted latency targets. Boundless offers no fine-tuning and publishes no benchmarks of its own.
What Groq and Boundless do
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.
Example models: GPT-OSS 120B, Qwen 3.8 27B
Full Groq profileBoundless
Boundless launched in September 2026 as an inference partner for AI-native startups. It sells two things. The Model API serves pre-tuned models on shared capacity, billed per token from prepaid credits with a budget per API key. Tailored inference reserves capacity for one customer, and Boundless engineers pick the model on the customer’s own evals, tune precision, batching, caching, speculative decoding and parallelism, then run the deployment against uptime, throughput and latency targets written into the contract. A free two-week evaluation tests those targets on real traffic against the customer’s current provider first.
Example models: GLM-5.3, DeepSeek V4.1 Flash, Kimi K3
Full Boundless profileShould you choose Groq or Boundless?
Groq vs Boundless at a glance
| Attribute | Groq | Boundless |
|---|---|---|
| Model access | Open weights | Open weights, plus closed GPT and Claude |
| Flagship models | GPT-OSS 120B, Qwen 3.8 27B | GLM-5.3, DeepSeek V4.1 Flash, Kimi K3 |
| Speed | 500–1,000 tok/s | 342 tok/s on DeepSeek V4.1 Flash 1017 (Vercel) |
| Price | Near the floor on small models | $0.04–$2.30 in, $0.21–$11.40 out per 1M (open) |
| Customization | No fine-tuned model hosting | Serving-stack tuning, no fine-tuning |
| Deployment | GroqCloud API | Serverless API, reserved tailored capacity |
| Long context | Around 131K max | 1M context on most models |
Frequently asked questions
What is the difference between Groq and Boundless?
Groq runs a small open-model catalog on its own LPU chip. Boundless serves open models with 1M context on most and resells GPT and Claude on the same API.
When should I choose Groq over Boundless?
Voice apps pairing Whisper with fast replies; Tight tail latency under strict SLAs; Low-cost small-model calls.
When should I choose Boundless over Groq?
1M-context open models; GPT and Claude on one API; Reserved capacity tuned by its engineers.
Is Groq or Boundless cheaper?
Groq: Near the floor on small models. Boundless: $0.04–$2.30 in, $0.21–$11.40 out per 1M (open). The cheaper choice depends on the model and workload.
Which has more context, Groq or Boundless?
Groq: Around 131K max. Boundless: 1M context on most models.
Related comparisons
Running long-horizon agents?
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.