OpenAI vs General Compute

OpenAI sells closed frontier models with 1M+ context. General Compute serves a few open models on ASIC decode hardware at low per-token prices.

By The Subconscious Team · Updated October 27, 2026

OpenAI vs General Compute: key differences

OpenAI's lineup runs from GPT-6 Astra at $10 in and $50 out per million tokens to GPT-6 Luna at $0.10 in and $0.50 out, all with 1.05M context, plus hosted tools, the Agents SDK and Batch discounts. General Compute runs open models with GPU prefill and decode on ASICs from Cerebras, SambaNova, Positron AI and d-Matrix. Its OpenAI-compatible API serves MiniMax M2.7, DeepSeek V3.2, DeepSeek V3.1 and OpenAI's own open-weight GPT-OSS 120B from $0.21 in and $0.38 out. It reports over 1,000 tokens per second on GPT-OSS 120B in its own benchmark.

OpenAI is the pick for frontier quality, long contexts and the largest tool ecosystem. General Compute fits agent loops and voice apps where decode speed sets the wait and an open model is good enough. Since it speaks the OpenAI format, moving a workload over is mostly a base URL change. Its context tops out at 192K, and it runs in one region, us-west-2.

What OpenAI and General Compute do

OpenAI

OpenAI runs the most widely adopted closed-model API. Its October 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 sit GPT-6.1 Sol, the default for coding, research and computer use at $2 in and $10 out, and GPT-6 Luna for high-volume jobs at $0.10 in and $0.50 out. All three carry a 1.05M token context window with up to 128K output.

Example models: GPT-6 Astra, GPT-6.1 Sol, GPT-6 Luna

Full OpenAI 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 OpenAI or General Compute?

OpenAI

Choose OpenAI for

Frontier coding and computer use
Long agent runs with 1M+ context
Hosted tools and the Agents SDK

General Compute

Choose General Compute for

Fast decode on open models
Cheap GPT-OSS 120B tokens
Reserved ASIC capacity under contract

OpenAI vs General Compute at a glance

Attribute	OpenAI	General Compute
Model access	Closed, plus open gpt-oss	Open weights
Flagship models	GPT-6 Astra, GPT-6.1 Sol, GPT-6 Luna	MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B
Speed	Fast mode; Ultrafast on GPT-6 Astra	1,000+ tok/s on GPT-OSS 120B (vendor)
Price	$0.10–$10 in, $0.50–$50 out per 1M	$0.21–$0.28 in, $0.38–$1.20 out per 1M
Customization	N/A	Custom LoRA and fine-tuned checkpoints
Deployment	API, Azure OpenAI, Bedrock	Serverless API, dedicated racks, bare metal
Long context	1.05M; 2x input past 272K	192K (MiniMax M2.7)

Frequently asked questions

What is the difference between OpenAI and General Compute?

OpenAI sells closed frontier models with 1M+ context. General Compute serves a few open models on ASIC decode hardware at low per-token prices.

When should I choose OpenAI over General Compute?

Frontier coding and computer use; Long agent runs with 1M+ context; Hosted tools and the Agents SDK.

When should I choose General Compute over OpenAI?

Fast decode on open models; Cheap GPT-OSS 120B tokens; Reserved ASIC capacity under contract.

Is OpenAI or General Compute cheaper?

OpenAI: $0.10–$10 in, $0.50–$50 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, OpenAI or General Compute?

OpenAI: 1.05M; 2x input past 272K. 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.

Subconscious vs OpenAI Subconscious vs General Compute