Modal vs SambaNova Cloud: Token Pricing, Speed & Intelligence
Full comparison of Modal and SambaNova Cloud — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Modal
Managed inference API — 10 shared-endpoint models with per-token pricing
Modal Shared Endpoints serve a fixed catalog of models from Modal-managed pools. Modal manages the hardware and autoscaling, and usage is billed per token. Shared Endpoints have model-specific concurrency limits on concurrent in-flight requests. Prices are published rates from modal.com/docs/guide/supported-models.md, re-read 2026-10-31.
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.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Modal
SambaNova Cloud
Key differentiators
Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.
Proprietary RDU chips deliver industry-leading throughput on open-weight models at competitive per-token rates.
Frequently asked questions
Modal FAQs
What models does Modal offer on Shared Endpoints?
Modal Shared Endpoints currently serve 10 models: GLM 5.3 Flash NVFP4, DeepSeek V4.1 Flash 1017, DeepSeek V4.1 Flash, GLM 5.3 Flash, Muse Spark Open, GLM 5.3, Inkling NVFP4, Qwen3.8-Max, Qwen3.8-Max VL, and Kimi K3. Use the model table above for per-model pricing and capability details. Source: Modal's published Shared Endpoints catalog, re-read 2026-10-31.
How much does Modal charge per 1M tokens?
Modal Shared Endpoints input prices range from $0.15/1M (GLM 5.3 Flash NVFP4) to $3.00/1M (Kimi K3). All models include cached-input pricing. See the model table for full per-model rates.
Does Modal offer prompt caching?
Yes. All 10 models in the Modal Shared Endpoints catalog have published cached-input pricing, ranging from $0.005/1M (DeepSeek V4.1 Flash 1017) to $0.30/1M (Kimi K3). Depending on the model, the cached-input rate is 77.5% to 98% below the standard input rate. Source: Modal's published Shared Endpoints rates, re-read 2026-10-31.
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).
Provider resources
Modal — Managed inference API — 10 shared-endpoint models with per-token pricing
Modal Shared Endpoints serve a fixed catalog of models from Modal-managed pools. Modal manages the hardware and autoscaling, and usage is billed per token. Shared Endpoints have model-specific concurrency limits on concurrent in-flight requests. Prices are published rates from modal.com/docs/guide/supported-models.md, re-read 2026-10-31.
Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.
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.
Key strengths compared
Modal
- Managed hardware and autoscaling — no infrastructure to operate
- Published per-token rates including cached-input pricing
- OpenAI-style per-token billing across all 10 models
- Small fixed catalog of 10 models
- Model-specific concurrency limits on shared pools
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
Key weaknesses compared
Modal
- Small fixed catalog of 10 models
- Model-specific concurrency limits on shared pools
- Prices are published rates re-read 2026-10-31, not continuously collected
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
Provider category context
Modal is a inference api. SambaNova Cloud is a inference api, founded in 2017. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Modal and SambaNova Cloud host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.