vs
OpenAI vs SambaNova
A closed model lab against a chip company selling fast decode on large open models. SambaNova even serves OpenAI's gpt-oss, so the overlap is real but narrow.
By The Subconscious Team · Updated
OpenAI vs SambaNova: key differences
SambaNova sells speed, not models. Its Reconfigurable Dataflow Unit maps a model graph onto the chip, and SambaCloud serves large open models such as MiniMax M2.7, DeepSeek and GPT-OSS 120B, OpenAI's own open-weight release. SambaNova reports that a SambaRack SN50 runs MiniMax M2.7 near 820 tokens per second in its fastest configuration. OpenAI's route to speed is Fast mode, up to 2.5x at double the price, on its closed GPT models. For teams that want frontier-scale open weights at interactive speed, SambaNova is the more direct option.
Many of SambaNova's headline numbers are vendor benchmarks on hardware still ramping, including its claims of 5x the peak speed of an NVIDIA B200 and 10M token contexts on SN50. Its public catalog is small, and much of its business runs through hardware sales and neocloud partnerships rather than a large self-serve platform. OpenAI is the opposite: a huge developer ecosystem, published tiers from Luna to Astra and a 1.05M window. SambaNova's millisecond model hot swapping does suit agents that bounce between several open models.
What OpenAI and SambaNova do
OpenAI
OpenAI runs the most widely adopted closed-model API. Its September 2026 lineup has GPT-6 Astra at the top for computer use, coding and long agentic runs, priced at $10 in and $50 out per million tokens. Below it sits the GPT-5.6 family: Sol for hard professional work, Terra as the balanced default, and Luna for high-volume jobs at $0.20 in and $1.20 out. All of them carry a 1.05M token context window with up to 128K output.
Example models: GPT-6 Astra, GPT-5.6 Terra
Full OpenAI profileSambaNova
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 profileShould you choose OpenAI or SambaNova?
OpenAI
Choose OpenAI for
- Closed frontier quality for coding and computer use
- Self-serve teams that want a large SDK ecosystem
- A broad range of tiers from Luna to Astra on one key
SambaNova
Choose SambaNova for
- Interactive coding copilots on big open models
- Agents that switch between several models in one flow
- Neoclouds adding a premium speed tier
OpenAI vs SambaNova at a glance
| Attribute | OpenAI | SambaNova |
|---|---|---|
| Model access | Closed, plus open gpt-oss | Open weights |
| Flagship models | GPT-6 Astra, GPT-5.6 Sol, Terra, Luna | MiniMax M2.7, GPT-OSS 120B, DeepSeek |
| Speed | Fast mode: up to 2.5x at 2x price | ~820 tok/s on MiniMax M2.7 (SN50) |
| Price | $0.20–$10 in, $1.20–$50 out per 1M | $0.22 in, $0.59 out (GPT-OSS 120B) |
| Customization | N/A | Unknown |
| Deployment | API, Azure OpenAI, Bedrock | SambaCloud, racks for neoclouds |
| Long context | 1.05M; 2x input past 272K | Up to 192K (MiniMax M2.7) |
Frequently asked questions
What is the difference between OpenAI and SambaNova?
A closed model lab against a chip company selling fast decode on large open models. SambaNova even serves OpenAI's gpt-oss, so the overlap is real but narrow.
When should I choose OpenAI over SambaNova?
Closed frontier quality for coding and computer use; Self-serve teams that want a large SDK ecosystem; A broad range of tiers from Luna to Astra on one key.
When should I choose SambaNova over OpenAI?
Interactive coding copilots on big open models; Agents that switch between several models in one flow; Neoclouds adding a premium speed tier.
Is OpenAI or SambaNova cheaper?
OpenAI: $0.20–$10 in, $1.20–$50 out per 1M. SambaNova: $0.22 in, $0.59 out (GPT-OSS 120B). The cheaper choice depends on the model and workload.
Which has more context, OpenAI or SambaNova?
OpenAI: 1.05M; 2x input past 272K. SambaNova: Up to 192K (MiniMax M2.7).
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.