Novita AI vs Particle.AI

Particle.AI serves a few Flash-class models with 1M context through Vercel AI Gateway. Novita serves 200+ models directly and through gateways, plus GPUs.

By The Subconscious Team · Updated September 30, 2026

Novita AI vs Particle.AI: key differences

Particle.AI is a narrow, early player. Through 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, all with 1M context and $0.03 cache reads. Novita also distributes through Vercel and OpenRouter but runs its own API too, with 200+ models across modalities and LLM prices from $0.02 per million. Both carry long context on DeepSeek, with Novita offering the full 1M on DeepSeek V4 Pro.

Scale and maturity favor Novita. It has a GPU cloud, dedicated endpoints with LoRA hot swapping, an Agent Sandbox and a history back to late 2023. Particle is still hiring its founding team, has a tiny catalog and shows 3.5 seconds of latency on its DeepSeek V4.1 Flash listing. Particle's appeal is a low-cost route on Flash models that teams can try without a new contract. Inside a multi-provider gateway, both could sit on the same routing table.

What Novita AI and Particle.AI do

Novita AI

Novita AI is a San Francisco inference cloud founded in late 2023 by Frank Lewis and Junyu Huang, and it competes on price and breadth. Its serverless API covers 200+ open models across LLMs, image, video, speech, voice cloning and embeddings, with LLM prices starting at $0.02 per million tokens. The API speaks both OpenAI and Anthropic formats. It became an official Hugging Face Inference Partner in April 2026 and was the day-zero launch partner for Google's Gemma 4.

Example models: DeepSeek V4 Pro, Gemma 4

Full Novita AI 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 profile

Should you choose Novita AI or Particle.AI?

Novita AI

Choose Novita AI for

A primary host with broad model coverage
Dedicated endpoints and GPU rental
Full 1M context on DeepSeek V4 Pro

Particle.AI

Choose Particle.AI for

Cheap Flash-class calls in Vercel AI Gateway
A price-optimized fallback route
GLM 5.3 Flash at $0.10 in, $0.40 out

Novita AI vs Particle.AI at a glance

Attribute	Novita AI	Particle.AI
Model access	Open weights	Open weights
Flagship models	DeepSeek V4 Pro, Gemma 4	DeepSeek V4.1 Flash, GLM 5.3 Flash
Speed	~36 tok/s on DeepSeek V4 Pro	~157 tok/s on DeepSeek V4.1 Flash
Price	From $0.02 per 1M; batch 50% off	$0.10 in, $0.40 out (GLM 5.3 Flash)
Customization	Hot-swappable LoRA adapters	Unknown
Deployment	Serverless, GPU cloud, dedicated	Via Vercel AI Gateway
Long context	Full 1M on DeepSeek V4 Pro	1M

Frequently asked questions

What is the difference between Novita AI and Particle.AI?

Particle.AI serves a few Flash-class models with 1M context through Vercel AI Gateway. Novita serves 200+ models directly and through gateways, plus GPUs.

When should I choose Novita AI over Particle.AI?

A primary host with broad model coverage; Dedicated endpoints and GPU rental; Full 1M context on DeepSeek V4 Pro.

When should I choose Particle.AI over Novita AI?

Cheap Flash-class calls in Vercel AI Gateway; A price-optimized fallback route; GLM 5.3 Flash at $0.10 in, $0.40 out.

Is Novita AI or Particle.AI cheaper?

Novita AI: From $0.02 per 1M; batch 50% off. 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, Novita AI or Particle.AI?

Novita AI: Full 1M on DeepSeek V4 Pro. Particle.AI: 1M.

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.

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