vs

OpenAI vs Particle.AI

Particle serves cheap Flash-class open models with 1M context through Vercel AI Gateway. It competes with OpenAI's Luna on price, not with GPT-6 Astra on capability.

By The Subconscious Team · Updated

OpenAI vs Particle.AI: key differences

Particle.AI is an early San Francisco startup whose product is visible mainly through Vercel AI Gateway. There it serves a small set of Flash-class open models with 1M token context: GLM 5.3 Flash at $0.10 in and $0.40 out, DeepSeek V4 Flash 0731 at $0.14 in and $0.28 out, and DeepSeek V4.1 Flash at $0.25 in and $1 out. All three offer cache reads at $0.03 per million. Against OpenAI, the relevant comparison is Luna at $0.20 in and $1.20 out, which Particle undercuts on output across all three listings.

The trade-off is certainty. Particle has a tiny catalog, little public track record and thin public detail about funding and founders. Some listings trail faster hosts on latency, such as 3.5 seconds on DeepSeek V4.1 Flash. OpenAI offers the full range from Luna to GPT-6 Astra, hosted tools and enterprise distribution through Azure and Bedrock. Because Particle sits inside a gateway, teams can try it with no new contract, usually as a fallback or price-optimized route next to a main provider like OpenAI rather than as a replacement.

What OpenAI and Particle.AI do

OpenAI

OpenAI runs the most widely adopted closed-model API. Its September 2026 lineup has GPT-6 Astra at the top for computer use, coding and long agentic runs, priced at $10 in and $50 out per million tokens. Below it sits the GPT-5.6 family: Sol for hard professional work, Terra as the balanced default, and Luna for high-volume jobs at $0.20 in and $1.20 out. All of them carry a 1.05M token context window with up to 128K output.

Example models: GPT-6 Astra, GPT-5.6 Terra

Full OpenAI 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 OpenAI or Particle.AI?

OpenAI

Choose OpenAI for

  • Frontier tasks beyond Flash-class capability
  • Hosted tools and the Agents SDK
  • Enterprises needing an established vendor

Particle.AI

Choose Particle.AI for

  • Cheap high-volume calls on DeepSeek and GLM Flash models
  • A price-optimized fallback route inside Vercel AI Gateway
  • 1M context on a tight budget

OpenAI vs Particle.AI at a glance

AttributeOpenAIParticle.AI
Model accessClosed, plus open gpt-ossOpen weights
Flagship modelsGPT-6 Astra, GPT-5.6 Sol, Terra, LunaDeepSeek V4.1 Flash, GLM 5.3 Flash
SpeedFast mode: up to 2.5x at 2x price~157 tok/s on DeepSeek V4.1 Flash
Price$0.20–$10 in, $1.20–$50 out per 1M$0.10 in, $0.40 out (GLM 5.3 Flash)
CustomizationN/AUnknown
DeploymentAPI, Azure OpenAI, BedrockVia Vercel AI Gateway
Long context1.05M; 2x input past 272K1M

Frequently asked questions

What is the difference between OpenAI and Particle.AI?

Particle serves cheap Flash-class open models with 1M context through Vercel AI Gateway. It competes with OpenAI's Luna on price, not with GPT-6 Astra on capability.

When should I choose OpenAI over Particle.AI?

Frontier tasks beyond Flash-class capability; Hosted tools and the Agents SDK; Enterprises needing an established vendor.

When should I choose Particle.AI over OpenAI?

Cheap high-volume calls on DeepSeek and GLM Flash models; A price-optimized fallback route inside Vercel AI Gateway; 1M context on a tight budget.

Is OpenAI or Particle.AI cheaper?

OpenAI: $0.20–$10 in, $1.20–$50 out per 1M. 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, OpenAI or Particle.AI?

OpenAI: 1.05M; 2x input past 272K. 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.