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SambaNova SN40LGoogle TPU Ironwood
| Attribute | SambaNova SN40L SambaNova | Google TPU Ironwood |
|---|---|---|
| Segment | Chips & Compute | Chips & Compute |
| Version | SN40L | 7th-generation (Ironwood) |
| Entry cost | Free tier available; pay-as-you-go developer and subscription-based enterprise plans offered. | from $5.4/unit |
| Pricing tiers | Free free · Developer Pay as you go free | On Demand (us-central1) $12 · DWS Flex-start (us-central1) $6 · DWS Calendar Mode (us-central1) $8.4 · 1-year Commitment (us-central1) $8.4 · 3-year Commitment (us-central1) $5.4 · On Demand (europe-west2) $13.2 · DWS Flex-start (europe-west2) $6 · DWS Calendar Mode (europe-west2) $8.4 |
| Model stack | DeepSeek-V3.1 · gpt-oss-120b · Llama / DeepSeek open weights · Llama 3 · Llama 3.1 · Llama 3.1 (8B, 70B, 405B) · Llama 3.1 405B · Llama 3.1 70B · Llama 3.1 8B · MiniMax M2.7 · MiniMax M3.1 Flash · Production & Preview models · RDU · RDU dataflow · SambaNova RDU · SambaNova SN40L RDUs · SambaRack SN40-16 · SN40L RDU | Gemini · Google TPU Ironwood · Ironwood · Ironwood (TPU v7) · Ironwood TPU · Ironwood TPU (7th Generation) · TPU v7 · TPU7x · TPU7x (Ironwood) · XLA compiler |
| Context window | — | — |
| Public API | ||
| Routes models | ||
| Changes / 30d | 2 | 11 |
| Origin | Global | Global |
| Capabilities | three-tier memory, many models per node, fast open-model serving, Reconfigurable Dataflow Unit (RDU), Three-tier memory architecture, Dataflow processing, Low power inference, Multi-model concurrency | 9,216-chip pods, inference optimised, liquid cooled, JAX + PyTorch/XLA, Large-scale training, Reasoning and inference, 9,216 liquid-cooled chips per pod, 42.5 ExaFlops performance |