Cohere vs General Compute

Cohere sells enterprise models for RAG and search with private deployment. General Compute sells fast serverless decode on open models.

By The Subconscious Team · Updated October 27, 2026

Cohere vs General Compute: key differences

Cohere's Command A lists at $2.50 in and $10 out per million tokens with a 256K context, and the open Command A+ runs 375 tokens per second in Cohere's own W4A4 test. Embed 5 and Rerank 4 form a cheap retrieval stack, and models run on Cohere's API, Bedrock, Azure, OCI, a private VPC or on-prem. General Compute serves MiniMax M2.7, DeepSeek V3.2, DeepSeek V3.1 and GPT-OSS 120B from $0.21 in, in us-west-2 only. In its own benchmark it measured over 1,000 tokens per second on GPT-OSS 120B.

Cohere is the pick for regulated enterprises that need RAG, reranking and agents inside their own network, with fine-tuning in that environment. General Compute fits teams that need fast generation for agent loops or chat and are fine with a single US region. It sells dedicated racks and bare metal on contract, but has no on-prem or VPC product.

What Cohere and General Compute 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 5, Rerank 4

Full Cohere profile

General Compute

General Compute is a San Francisco inference cloud built on alternative chips. It splits each request across hardware, with NVIDIA GPUs handling prefill and ASICs from Cerebras, SambaNova, Positron AI and d-Matrix handling decode. In its own open benchmark on GPT-OSS 120B it measured 1,025 to 1,234 output tokens per second against 100 to 121 on an unnamed GPU cloud, and up to 16.2x faster end to end. Founders Finn Puklowski and Jason Goodison raised a $15M seed led by FUSE, an up to $400M debt facility from Upper90 and, on October 27, 2026, a $100M Series A co-led by Blackbird and Abstract.

Example models: MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B

Full General Compute profile

Should you choose Cohere or General Compute?

Cohere

Choose Cohere for

Private VPC or on-prem deployment
Embeddings and reranking
Multilingual enterprise assistants

General Compute

Choose General Compute for

Fast generation in agent loops
Low prices on open models
Bring-your-own fine-tunes

Cohere vs General Compute at a glance

Attribute	Cohere	General Compute
Model access	Closed, plus open Command A+	Open weights
Flagship models	Command A+, Command A, Embed 5, Rerank 4	MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B
Speed	375 tok/s on Command A+ W4A4, per Cohere	1,000+ tok/s on GPT-OSS 120B (vendor)
Price	$0.0375–$2.50 in, $0.15–$10 out per 1M	$0.21–$0.28 in, $0.38–$1.20 out per 1M
Customization	Enterprise fine-tuning, incl. private	Custom LoRA and fine-tuned checkpoints
Deployment	API, Bedrock, Azure, OCI, VPC, on-prem	Serverless API, dedicated racks, bare metal
Long context	256K on Command A; 128K on A+	192K (MiniMax M2.7)

Frequently asked questions

What is the difference between Cohere and General Compute?

Cohere sells enterprise models for RAG and search with private deployment. General Compute sells fast serverless decode on open models.

When should I choose Cohere over General Compute?

Private VPC or on-prem deployment; Embeddings and reranking; Multilingual enterprise assistants.

When should I choose General Compute over Cohere?

Fast generation in agent loops; Low prices on open models; Bring-your-own fine-tunes.

Is Cohere or General Compute cheaper?

Cohere: $0.0375–$2.50 in, $0.15–$10 out per 1M. General Compute: $0.21–$0.28 in, $0.38–$1.20 out per 1M. The cheaper choice depends on the model and workload.

Which has more context, Cohere or General Compute?

Cohere: 256K on Command A; 128K on A+. General Compute: 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.

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