SambaNova Cloud vs Stability AI: Token Pricing, Speed & Intelligence
Full comparison of SambaNova Cloud and Stability AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
SambaNova Cloud
High-throughput inference on SambaNova RDU chips — gpt-oss-120b, GLM-5.3, Llama
SambaNova Cloud runs inference on SambaNova's proprietary Reconfigurable Dataflow Unit (RDU) chips, delivering very high throughput (800+ tokens/sec on gpt-oss-120b). The catalog covers gpt-oss-120b, GLM-5.3, MiniMax-M3, DeepSeek-V3.2, Meta-Llama-3.3-70B, and Gemma 4 31B. Pricing is PAYG with prompt caching on select models.
Stability AI
Stable Diffusion 3.5 Large and Stable Image Ultra — open-weight image generation
Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation.
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Live token pricing
Strengths and weaknesses
SambaNova Cloud
Stability AI
Key differentiators
Proprietary RDU chips deliver industry-leading throughput on open-weight models at competitive per-token rates.
Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.
Frequently asked questions
SambaNova Cloud FAQs
What makes SambaNova Cloud different?
SambaNova runs inference on its own Reconfigurable Dataflow Unit (RDU) chips rather than NVIDIA GPUs. This delivers very high throughput — over 800 tokens/sec on gpt-oss-120b — at competitive per-token rates.
What models does SambaNova Cloud offer?
As of October 2026: gpt-oss-120b ($0.22/$0.59), GLM-5.3 ($1.40/$4.40, cached $0.14), MiniMax-M3 ($0.60/$2.40, cached $0.06), DeepSeek-V3.2 ($3.00/$4.50), Meta-Llama-3.3-70B ($0.60/$1.20), and Gemma 4 31B ($0.38/$1.15). See cloud.sambanova.ai/plans/pricing for current rates.
Does SambaNova offer prompt caching?
Yes, on GLM-5.3 (cached input $0.14/1M vs $1.40/1M standard) and MiniMax-M3 (cached input $0.06/1M vs $0.60/1M standard).
Stability AI FAQs
What is Stable Diffusion 3.5?
Stable Diffusion 3.5 is Stability AI's latest generation of open-weight text-to-image models. SD 3.5 Large offers the highest quality; SD 3.5 Medium is a balanced option for production use. Both are available for self-hosting.
How does Stability AI compare to FLUX?
FLUX 1.1 Pro generally outperforms SD 3.5 on photorealism and prompt adherence benchmarks. However, SD 3.5 has a much larger community ecosystem of fine-tuned variants and LoRAs, making it more flexible for specialised use cases.
Can I self-host Stable Diffusion 3.5?
Yes. SD 3.5 Large and Medium weights are publicly available under the Stability AI Community License. You can run them on any GPU with sufficient VRAM — SD 3.5 Medium requires ~8GB VRAM; SD 3.5 Large requires ~24GB.
Provider resources
SambaNova Cloud — High-throughput inference on SambaNova RDU chips — gpt-oss-120b, GLM-5.3, Llama
SambaNova Cloud runs inference on SambaNova's proprietary Reconfigurable Dataflow Unit (RDU) chips, delivering very high throughput (800+ tokens/sec on gpt-oss-120b). The catalog covers gpt-oss-120b, GLM-5.3, MiniMax-M3, DeepSeek-V3.2, Meta-Llama-3.3-70B, and Gemma 4 31B. Pricing is PAYG with prompt caching on select models.
Proprietary RDU chips deliver industry-leading throughput on open-weight models at competitive per-token rates.
Stability AI — Stable Diffusion 3.5 Large and Stable Image Ultra — open-weight image generation
Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation.
Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.
Key strengths compared
SambaNova Cloud
- Proprietary RDU chips deliver very high throughput — 800+ tokens/sec on gpt-oss-120b
- Competitive pricing on gpt-oss-120b ($0.22/$0.59 per 1M)
- Prompt caching on GLM-5.3 (cached input at $0.14/1M)
- Smaller model catalog vs OpenRouter or Together AI
- No proprietary frontier models — inference-only platform
Stability AI
- Open-weight SD 3.5 models — self-host on any GPU cloud
- Largest community ecosystem of fine-tuned variants and LoRAs
- Stable Image Ultra for photorealistic output
- Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
- Company has faced financial challenges and leadership changes
Key weaknesses compared
SambaNova Cloud
- Smaller model catalog vs OpenRouter or Together AI
- No proprietary frontier models — inference-only platform
- RDU architecture may behave differently from GPU inference for some workloads
Stability AI
- Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
- Company has faced financial challenges and leadership changes
- SD 3.5 adoption slower than FLUX in the community
Provider category context
SambaNova Cloud is a inference api, founded in 2017. Stability AI is a frontier lab, founded in 2020. SambaNova Cloud as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. Stability AI as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose SambaNova Cloud if you need High-throughput inference. Choose Stability AI if you need open-weight sd 3.5 models — self-host on any gpu cloud. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.