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RunInfra vs Particle.AI
Two young open-model startups. RunInfra builds tuned endpoints and sells coding plans; Particle AI serves cheap Flash-class models with 1M context.
By The Subconscious Team · Updated
RunInfra vs Particle.AI: key differences
Both companies are early and small, so the choice is about which narrow job you need done. RunInfra offers two things: hosted Model APIs over a tiny library like Nemotron 3.5 Lightning 30B and Qwen 3.8 27B, with coding plans from $10 a month for Claude Code, Codex and Aider, and an agent that benchmarks GPUs, searches quantized variants and ships a custom endpoint that scales to zero. Particle AI sells tokens on a few Flash-class models through Vercel AI Gateway, such as GLM 5.3 Flash at $0.10 in and $0.40 out and DeepSeek V4.1 Flash at $0.25 in and $1 out, all with 1M context.
Particle's edge is context and gateway access. Full 1M windows and $0.03 cache reads suit cheap high-volume calls, and teams can try it with no new contract, though some listings are slow, like 3.5 seconds on DeepSeek V4.1 Flash. RunInfra's edge is customization: uploads up to 50 GB, automatic quantization toward a latency target and voice pipelines. Neither has much independent benchmarking, so test both on real traffic.
What RunInfra and Particle.AI do
RunInfra
RunInfra pitches open models built for agents, with two ways in. Its hosted Model APIs serve a small curated library, including Nemotron 3.5 Lightning 30B, Qwen 3.8 27B and Ornith 1.5 35B, behind one key that works with both the OpenAI and Anthropic SDKs. Cached context bills at a discount. Coding plans start at $10 a month with limits that reset every five hours and every week, and they plug into Claude Code, Codex, OpenCode, Cline, Aider and dozens of other agent CLIs.
Example models: Nemotron 3.5 Lightning 30B, Qwen 3.8 27B
Full RunInfra 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 RunInfra or Particle.AI?
RunInfra
Choose RunInfra for
- A flat-rate coding plan inside agent CLIs
- Deploying a custom or tuned model without ML ops staff
- Chained speech, LLM and TTS pipelines
Particle.AI
Choose Particle.AI for
- Cheap DeepSeek and GLM Flash calls with 1M context
- Price-optimized routing inside Vercel AI Gateway
- Trying a new host without signing a contract
RunInfra vs Particle.AI at a glance
| Attribute | RunInfra |  Particle.AI |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | Nemotron 3.5 Lightning 30B, Qwen 3.8 27B | DeepSeek V4.1 Flash, GLM 5.3 Flash |
| Speed | Cold starts under 2s | ~157 tok/s on DeepSeek V4.1 Flash |
| Price | Coding plans from $10 a month | $0.10 in, $0.40 out (GLM 5.3 Flash) |
| Customization | Uploads up to 50 GB; auto-quantization | Unknown |
| Deployment | Model APIs, agent-built endpoints | Via Vercel AI Gateway |
| Long context | Varies by model | 1M |
Frequently asked questions
What is the difference between RunInfra and Particle.AI?
Two young open-model startups. RunInfra builds tuned endpoints and sells coding plans; Particle AI serves cheap Flash-class models with 1M context.
When should I choose RunInfra over Particle.AI?
A flat-rate coding plan inside agent CLIs; Deploying a custom or tuned model without ML ops staff; Chained speech, LLM and TTS pipelines.
When should I choose Particle.AI over RunInfra?
Cheap DeepSeek and GLM Flash calls with 1M context; Price-optimized routing inside Vercel AI Gateway; Trying a new host without signing a contract.
Is RunInfra or Particle.AI cheaper?
RunInfra: Coding plans from $10 a month. 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, RunInfra or Particle.AI?
RunInfra: Varies by model. Particle.AI: 1M.
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