vs
Runware vs Particle.AI
Particle.AI serves cheap Flash-class text models with 1M context. Runware generates images, video and more at low prices. Both compete on cost, in different media.
By The Subconscious Team · Updated
Runware vs Particle.AI: key differences
Runware and Particle.AI both sell low prices, for different outputs. Runware's rate sheet lists 300+ media models across image, video, audio and 3D, with images from fractions of a cent and video like Seedance 2.5 at about $0.10 a second at 480p. It runs on its own Sonic Inference Engine hardware and keeps 400K+ models resident. Particle.AI serves a handful of text 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, with 1M context and $0.03 cache reads.
A cheap consumer app could use both, Particle for text reasoning and prompt writing and Runware for the images or clips. Runware says text workloads fit better elsewhere, and Particle offers no media generation. Particle is a very early company with a tiny catalog and some slow listings, while Runware claims more than 1M developers. Runware's output URLs expire after seven days by default, so storage is on the app. Pick each for its own medium.
What Runware and Particle.AI do
Runware
Runware sells what it calls the lowest-cost API for media generation, and it claims more than 1M developers. One endpoint covers image, video, audio, 3D and text. Every request is a task with the same shape, so switching from a Kling video to a Seedream image mostly means changing the model ID. The published rate sheet lists 300+ priced models, with images from fractions of a cent to a few cents each and video billed per second, like Seedance 2.5 at about $0.10 a second at 480p.
Example models: Seedance 2.5, Qwen-Image-3.0
Full Runware 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 Runware or Particle.AI?
Runware
Choose Runware for
- Low-cost image and video generation
- Batching many media tasks in one request
- Running custom diffusion checkpoints
Particle.AI
Choose Particle.AI for
- Cheap text calls on Flash-class models
- 1M-context prompts with cheap cache reads
- A price-optimized route in Vercel AI Gateway
Runware vs Particle.AI at a glance
| Attribute | Runware |  Particle.AI |
|---|---|---|
| Model access | Hosted media models | Open weights |
| Flagship models | Seedance 2.5, Qwen-Image-3.0 | DeepSeek V4.1 Flash, GLM 5.3 Flash |
| Speed | Unknown | ~157 tok/s on DeepSeek V4.1 Flash |
| Price | Images from fractions of a cent | $0.10 in, $0.40 out (GLM 5.3 Flash) |
| Customization | Fine-tuned diffusion checkpoints | Unknown |
| Deployment | Unified API, raw GPUs | Via Vercel AI Gateway |
| Long context | Not applicable | 1M |
Frequently asked questions
What is the difference between Runware and Particle.AI?
Particle.AI serves cheap Flash-class text models with 1M context. Runware generates images, video and more at low prices. Both compete on cost, in different media.
When should I choose Runware over Particle.AI?
Low-cost image and video generation; Batching many media tasks in one request; Running custom diffusion checkpoints.
When should I choose Particle.AI over Runware?
Cheap text calls on Flash-class models; 1M-context prompts with cheap cache reads; A price-optimized route in Vercel AI Gateway.
Is Runware or Particle.AI cheaper?
Runware: Images from fractions of a cent. 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, Runware or Particle.AI?
Runware: Not applicable. 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.