vs
SambaNova vs RunInfra
SambaNova sells fast decode on large open models from its own chip. RunInfra sells cheap coding plans on mid-size models and an agent that builds tuned endpoints for you.
By The Subconscious Team · Updated
SambaNova vs RunInfra: key differences
RunInfra is a young platform with two products. Its hosted Model APIs serve a small library, including Nemotron 3.5 Lightning 30B and Qwen 3.8 27B, with coding plans from $10 a month for Claude Code, Codex and similar tools. Its deployment agent benchmarks models across GPUs from L4 to B200, tries AWQ, GPTQ and FP8 variants and ships an endpoint that scales to zero. SambaNova is a hardware company serving larger open models like MiniMax M2.7 and DeepSeek at high decode speeds on its RDU chip.
Model size and team size separate them. RunInfra admits its hosted library sits far from frontier quality, but it gives small teams a cheap flat plan and a way to deploy a custom upload or a voice pipeline without ML ops staff. SambaNova serves bigger models for interactive coding agents and sells racks to neoclouds. RunInfra has little independent benchmarking, and SambaNova's top numbers are vendor benchmarks, so test either before committing.
What SambaNova and RunInfra do
SambaNova
SambaNova designs its own inference chip, the Reconfigurable Dataflow Unit, and sells fast tokens on large open models through SambaCloud. The RDU maps the model graph onto the chip to cut trips to off-chip memory. A three-tier memory design of SRAM, HBM and bulk DRAM lets one system host very large models and hot swap between several of them in milliseconds. SambaCloud serves models like MiniMax M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, with speeds reported by Artificial Analysis.
Example models: MiniMax M2.7, GPT-OSS 120B
Full SambaNova profileRunInfra
RunInfra pitches open models built for agents, with two ways in. Its hosted Model APIs serve a small curated library, including Nemotron 3.5 Lightning 30B, Qwen 3.8 27B and Ornith 1.5 35B, behind one key that works with both the OpenAI and Anthropic SDKs. Cached context bills at a discount. Coding plans start at $10 a month with limits that reset every five hours and every week, and they plug into Claude Code, Codex, OpenCode, Cline, Aider and dozens of other agent CLIs.
Example models: Nemotron 3.5 Lightning 30B, Qwen 3.8 27B
Full RunInfra profileShould you choose SambaNova or RunInfra?
SambaNova vs RunInfra at a glance
| Attribute | SambaNova | RunInfra |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | MiniMax M2.7, GPT-OSS 120B, DeepSeek | Nemotron 3.5 Lightning 30B, Qwen 3.8 27B |
| Speed | ~820 tok/s on MiniMax M2.7 (SN50) | Cold starts under 2s |
| Price | $0.22 in, $0.59 out (GPT-OSS 120B) | Coding plans from $10 a month |
| Customization | Unknown | Uploads up to 50 GB; auto-quantization |
| Deployment | SambaCloud, racks for neoclouds | Model APIs, agent-built endpoints |
| Long context | Up to 192K (MiniMax M2.7) | Varies by model |
Frequently asked questions
What is the difference between SambaNova and RunInfra?
SambaNova sells fast decode on large open models from its own chip. RunInfra sells cheap coding plans on mid-size models and an agent that builds tuned endpoints for you.
When should I choose SambaNova over RunInfra?
Fast decode on large open models; Interactive agents that switch models mid-task; Neoclouds adding premium inference.
When should I choose RunInfra over SambaNova?
Cheap monthly coding plans on mid-size models; Auto-built endpoints that scale to zero; Voice pipelines without in-house ML ops.
Is SambaNova or RunInfra cheaper?
SambaNova: $0.22 in, $0.59 out (GPT-OSS 120B). RunInfra: Coding plans from $10 a month. The cheaper choice depends on the model and workload.
Which has more context, SambaNova or RunInfra?
SambaNova: Up to 192K (MiniMax M2.7). RunInfra: Varies by model.
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.