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Cohere vs SambaNova
SambaNova sells fast decode on large open models from its own chip. Cohere sells its own models, with retrieval tools and private deployment for enterprises.
By The Subconscious Team · Updated
Cohere vs SambaNova: key differences
SambaNova competes on speed for big open models. Its RDU chip serves MiniMax M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, the last at $0.22 in and $0.59 out, and SambaNova claims a SambaRack SN50 runs MiniMax M2.7 near 820 tokens per second. Model hot swapping in milliseconds suits agents that bounce between models, and MiniMax M2.7 runs up to 192K context. Cohere claims 375 tokens per second on Command A+ in 4-bit form. Its Command A lists at $2.50 in and $10 out with 256K context, and Cohere says Command A+ trails MiniMax and DeepSeek models on agentic coding.
Cohere's strengths are enterprise ones. It offers fine-tuning, including inside private VPC and on-prem deployments, while SambaNova lists none. Cohere sells through Bedrock, Azure AI Foundry and OCI, and adds Embed 4, Rerank 4, Aya and Transcribe. SambaNova's value arrives more through hardware sales to neoclouds than a large self-serve platform, and many headline figures are vendor benchmarks on the SN50, which only starts shipping in the second half of 2026. Pick SambaNova for interactive coding agents on large open models. Pick Cohere for private enterprise RAG.
What Cohere and SambaNova do
Cohere
Cohere is a Toronto-based lab that sells models and platforms to banks, governments and large enterprises rather than consumers. Its generative line is the Command family. Command A+, released May 20, 2026, is a 218B-parameter mixture-of-experts model with 25B active, published under Apache 2.0 with a 128K context window, and it combines reasoning, vision, translation and tool use in one set of weights. Command A has a 256K window and lists at $2.50 in and $10 out per million tokens, while Command R7B costs $0.0375 in. June 2026 added North Mini Code, a 30B Apache 2.0 coding model, and the lineup also includes Aya multilingual models and Transcribe for speech.
Example models: Command A+, Command A, Embed 4, Rerank 4
Full Cohere 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 Cohere or SambaNova?
Cohere vs SambaNova at a glance
| Attribute | Cohere | SambaNova |
|---|---|---|
| Model access | Closed, plus open Command A+ | Open weights |
| Flagship models | Command A+, Command A, Embed 4, Rerank 4 | MiniMax M2.7, GPT-OSS 120B, DeepSeek |
| Speed | 375 tok/s on Command A+ W4A4, per Cohere | ~820 tok/s on MiniMax M2.7 (SN50) |
| Price | $0.0375–$2.50 in, $0.15–$10 out per 1M | $0.22 in, $0.59 out (GPT-OSS 120B) |
| Customization | Enterprise fine-tuning, incl. private | Unknown |
| Deployment | API, Bedrock, Azure, OCI, VPC, on-prem | SambaCloud, racks for neoclouds |
| Long context | 256K on Command A; 128K on A+ | Up to 192K (MiniMax M2.7) |
Frequently asked questions
What is the difference between Cohere and SambaNova?
SambaNova sells fast decode on large open models from its own chip. Cohere sells its own models, with retrieval tools and private deployment for enterprises.
When should I choose Cohere over SambaNova?
Fine-tuned models inside a private network; Enterprise search with Embed and Rerank; Multilingual assistants on Aya.
When should I choose SambaNova over Cohere?
Fast decode on MiniMax M2.7 and DeepSeek; Agents that hot swap between several models; Neoclouds adding a premium speed tier.
Is Cohere or SambaNova cheaper?
Cohere: $0.0375–$2.50 in, $0.15–$10 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, Cohere or SambaNova?
Cohere: 256K on Command A; 128K on A+. 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.