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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 $0.10 in and $0.50 out, which Particle undercuts on output on its GLM 5.3 Flash and DeepSeek V4 Flash 0731 listings.
The trade-off is certainty. Particle has a tiny catalog and little public track record. Some listings trail faster hosts on latency, such as 1.9 seconds on GLM 5.3 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 October 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 sit GPT-6.1 Sol, the default for coding, research and computer use at $2 in and $10 out, and GPT-6 Luna for high-volume jobs at $0.10 in and $0.50 out. All three carry a 1.05M token context window with up to 128K output.
Example models: GPT-6 Astra, GPT-6.1 Sol, GPT-6 Luna
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. Mixpanel founder Suhail Doshi started it, with backing from Y Combinator, 8VC, Caffeinated Capital and angels including Patrick Collison, Adam D'Angelo and Aaron Levie.
Example models: DeepSeek V4.1 Flash, GLM 5.3 Flash
Full Particle.AI profileShould 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
| Attribute | OpenAI |  Particle.AI |
|---|---|---|
| Model access | Closed, plus open gpt-oss | Open weights |
| Flagship models | GPT-6 Astra, GPT-6.1 Sol, GPT-6 Luna | DeepSeek V4.1 Flash, GLM 5.3 Flash |
| Speed | Fast mode; Ultrafast on GPT-6 Astra | ~193 tok/s on DeepSeek V4.1 Flash |
| Price | $0.10–$10 in, $0.50–$50 out per 1M | $0.10 in, $0.40 out (GLM 5.3 Flash) |
| Customization | N/A | Unknown |
| Deployment | API, Azure OpenAI, Bedrock | Via Vercel AI Gateway |
| Long context | 1.05M; 2x input past 272K | 1M |
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: $0.10–$10 in, $0.50–$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.
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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.