SambaNova
Listed at https://cloud.sambanova.ai
💰 Token Pricing
| Type | Price | Note |
|---|---|---|
| Input | Llama 3.3 70B: $0.50/M, DeepSeek-R1: $0.80/M, Qwen 72B: $0.40/M | per million tokens |
| Output | Llama 3.3 70B: $0.50/M, DeepSeek-R1: $0.80/M, Qwen 72B: $0.40/M | per million tokens |
🤖 Supported Models (8)
✨ Pros
- ✓SN40L custom chip + Dataflow architecture
- ✓Llama 3.3 70B reaches 1400+ tok/s
- ✓Very competitive pricing ($0.50/M tokens)
- ✓SnapTrack for real-time inference accuracy monitoring
- ✓OpenAI-compatible API
- ✓Enterprise SN40L chip deployment
⚠️ Cons
- ×China requires proxy
- ×Limited model selection (8)
- ×No multimodal support
- ×No Function Calling support
- ×Less brand recognition than Groq/Cerebras
🎯 Best For
High-speed open-source inference; Llama high-performance workloads; cost-sensitive high-throughput apps
💰 Pricing & Plans
| Model | Cached Input ($/M) | Input ($/M) | Output ($/M) | Notes |
|---|---|---|---|---|
| MiniMax-M2.7 | $0.06 | $0.60 | $2.40 | Budget MoE for everyday chat/tasks |
| MiniMax-M3 | — | $0.60 | $2.40 | Newer MiniMax generation, same price band |
| Meta-Llama-3.3-70B-Instruct | — | $0.60 | $1.20 | Fast, open 70B flagship |
| gemma-4-31B-it | — | $0.38 | $1.15 | Lightweight, cheap general model |
| gpt-oss-120b | — | $0.22 | $0.59 | Open-weight OpenAI; lowest output price |
| DeepSeek-V3.1 | — | $3.00 | $4.50 | High-capability reasoning MoE |
| DeepSeek-V3.2 | — | $3.00 | $4.50 | Latest DeepSeek reasoning tier |
🔧 API & Developer Experience
- •OpenAI Compatibility: Drop-in /v1/chat/completions endpoint at api.sambanova.ai combined with SambaNova Cloud keys — most OpenAI SDK code runs unchanged.
- •Ultra-Low Latency: SN40L/SN7600 Dataflow hardware sustains token rates far above typical GPU clouds; ideal for agent loops and real-time assistants where first-token and inter-token latency dominate UX.
- •Streaming & Tool Use: SSE-streaming supported out of the box; function calling / tool use is available on supported hosted models for chained agent calls.
- •SDKs & Runtimes: Official Python/TypeScript SDKs plus OpenAI SDK, LangChain/LlamaIndex and LiteLLM integrations; community wrappers cover most frameworks.
- •SnapTrack: SambaNova's real-time drift/accuracy monitoring surfaces inference-quality regressions per task so teams can catch model changes before they hit users.
- •Preview Models: Developer plan unlocks Preview (pre-production) models on top of the Production catalog, giving early access ahead of general availability.
⚡ Dataflow Architecture & Ultra-Fast Inference
SambaNova's differentiator is its purpose-built SN40L (and newer SN7600) reconfigurable dataflow unit (RDU) paired with the SambaFlow compiler. Instead of feeding a general-purpose GPU with kernels, the compiler statically schedules the entire model graph onto the chip's processing elements and on-chip SRAM, cutting the memory-bandwidth bottlenecks that throttle transformer inference. The result is throughput that rivals or beats Cerebras and Groq on open-weight models; Llama 3.3 70B, for example, is served well past 1,000+ tokens/s on the platform, making token-cost-per-latency uniquely attractive. For agent-heavy or real-time workloads where every request spins a short, high-frequency generation loop, this translates directly into lower per-call cost and snappier UX. Because the SambaNova Cloud is OpenAI-compatible, teams adopt these speedups without rewriting their serving layer.
🌐 Regional Availability & Latency
SambaNova Cloud (api.sambanova.ai) is served from US-based data centers and, like most US inference providers, is not directly reachable from mainland China — mainland developers need a proxy, an overseas VPS, or a third-party reseller. From within mainland China, direct latency is high (500ms-2s+); routed through a Hong Kong, Singapore, or Tokyo proxy this typically drops to 200-500ms round-trip. Global latency away from China is strong: US east/west and EU-first regions see very low first-token times on short generations, and the OpenAI-compatible surface means existing OpenAI/LiteLLM clients can fail over to api.sambanova.ai as an overseas low-latency primary or backup. For teams serving end users in China, pairing SambaNova (compute) with a domestic or Asia-Pac edge is the standard pattern.