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Chutes vs SambaNova Cloud: Token Pricing, Speed & Intelligence

Full comparison of Chutes and SambaNova Cloud — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.

Chutes

Open-weight model inference on TEE GPUs

Chutes (chutes.ai) is an inference platform for open-weight models. Workloads run inside Trusted Execution Environments (TEEs) on GPU hardware, with cryptographic attestation of model and input confidentiality. The API is OpenAI-compatible and pricing is per token with no minimum commitment.

Open-weight inferencePrivacy-sensitive workloadsServerless LLM
Open-weight hostHosts open weights

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.

High-throughput inferenceCost-sensitive workloadsOpen-weight models
Open-weight hostHosts open weights

Key metric comparison

Cheapest input ($/1M)

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Cheapest output ($/1M)

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Peak throughput

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Best latency (TTFT)

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Intelligence score

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Context window

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Live token pricing

Strengths and weaknesses

Chutes

TEE-backed inference with cryptographic attestation
OpenAI-compatible API
Serverless, per-token pricing
Supports open-weight models including Llama, Mistral, Qwen, and DeepSeek

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)
Strong open-weight model catalog: Llama, DeepSeek, Gemma, MiniMax
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

Key differentiators

Chutes

Open-weight inference platform running workloads inside TEEs with cryptographic attestation.

SambaNova Cloud

Proprietary RDU chips deliver industry-leading throughput on open-weight models at competitive per-token rates.

Frequently asked questions

Chutes FAQs

What is Chutes?

Chutes is an inference platform for open-weight models. Workloads run inside Trusted Execution Environments (TEEs) on GPU hardware. See chutes.ai for details.

What does TEE inference mean on Chutes?

TEE (Trusted Execution Environment) inference runs model workloads inside a hardware-isolated enclave. Chutes provides cryptographic attestation of this isolation. See their documentation at docs.chutes.ai.

What models does Chutes offer?

Chutes hosts open-weight models including families from Llama, Mistral, Qwen, and DeepSeek. See chutes.ai for the current catalog.

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

Chutes — Open-weight model inference on TEE GPUs

Chutes (chutes.ai) is an inference platform for open-weight models. Workloads run inside Trusted Execution Environments (TEEs) on GPU hardware, with cryptographic attestation of model and input confidentiality. The API is OpenAI-compatible and pricing is per token with no minimum commitment.

Open-weight inference platform running workloads inside TEEs with cryptographic attestation.

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

Chutes

  • TEE-backed inference with cryptographic attestation
  • OpenAI-compatible API
  • Serverless, per-token pricing

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

Chutes

    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

    Chutes is a open source host, founded in 2024. SambaNova Cloud is a inference api, founded in 2017. The category difference means these providers serve partially overlapping use cases — compare the model lists and pricing tables above to find the best fit for your specific workload.

    How to choose between them

    Choose Chutes if you need tee-backed inference with cryptographic attestation. Choose SambaNova Cloud if you need High-throughput inference. 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.