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Groq vs Particle.AI
Particle.AI sells cheap Flash-class models with 1M context through Vercel AI Gateway. Groq sells fast inference capped near 131K. Context and price against latency.
By The Subconscious Team · Updated
Groq vs Particle.AI: key differences
Particle.AI is an early startup whose product is mostly visible on Vercel AI Gateway. It serves DeepSeek V4.1 Flash at $0.25 in and $1 out, GLM 5.3 Flash at $0.10 in and $0.40 out, and DeepSeek V4 Flash 0731 at $0.14 in and $0.28 out, each with 1M context and $0.03 cache reads. Latency is its weak point, with 3.5 seconds listed on DeepSeek V4.1 Flash and about 157 tokens per second. Groq is the reverse: several hundred tokens per second and tight tails, but context capped around 131K and no DeepSeek or GLM on its list.
Maturity favors Groq, founded in 2016, though its independence changed after NVIDIA hired most of its staff. Particle has a tiny catalog, little public track record and thin public detail about founders and funding. Its low prices and gateway access make it a good fallback route. Groq fits the user-facing turn, and Particle fits long-context background calls where a few seconds do not matter.
What Groq and Particle.AI 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 3.6 27B
Full Groq profile
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. Public detail about funding and founders is thin as of this writing.
Example models: DeepSeek V4.1 Flash, GLM 5.3 Flash
Full Particle.AI profileShould you choose Groq or Particle.AI?
Groq
Choose Groq for
- User-facing turns where every second counts
- Voice apps with Whisper and a fast LLM
- An established API with cache and Batch discounts
Particle.AI
Choose Particle.AI for
- Cheap 1M context calls on Flash models
- Fallback routing inside Vercel AI Gateway
- Long-document background jobs on DeepSeek or GLM
Groq vs Particle.AI at a glance
| Attribute | Groq |  Particle.AI |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | DeepSeek V4.1 Flash, GLM 5.3 Flash |
| Speed | 500–1,000 tok/s | ~157 tok/s on DeepSeek V4.1 Flash |
| Price | Near the floor on small models | $0.10 in, $0.40 out (GLM 5.3 Flash) |
| Customization | No fine-tuned model hosting | Unknown |
| Deployment | GroqCloud API | Via Vercel AI Gateway |
| Long context | Around 131K max | 1M |
Frequently asked questions
What is the difference between Groq and Particle.AI?
Particle.AI sells cheap Flash-class models with 1M context through Vercel AI Gateway. Groq sells fast inference capped near 131K. Context and price against latency.
When should I choose Groq over Particle.AI?
User-facing turns where every second counts; Voice apps with Whisper and a fast LLM; An established API with cache and Batch discounts.
When should I choose Particle.AI over Groq?
Cheap 1M context calls on Flash models; Fallback routing inside Vercel AI Gateway; Long-document background jobs on DeepSeek or GLM.
Is Groq or Particle.AI cheaper?
Groq: Near the floor on small models. Particle.AI: $0.10 in, $0.40 out (GLM 5.3 Flash). The cheaper choice depends on the model and workload.
Which has more context, Groq or Particle.AI?
Groq: Around 131K max. Particle.AI: 1M.
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