OpenScale vs General Compute

OpenScale sells DeepSeek V4.1 Flash cheaply with 1M context. General Compute sells fast decode on older open models from a US region.

By The Subconscious Team · Updated October 27, 2026

OpenScale vs General Compute: key differences

OpenScale, a Y Combinator-backed API out of Singapore, serves DeepSeek V4.1 Flash at $0.06 in, $0.003 cached and $0.24 out per million tokens under a 50% promotion, at 200+ tokens per second, with 1M context. It speaks Chat Completions, the OpenAI Responses API and Anthropic Messages. General Compute serves MiniMax M2.7, DeepSeek V3.2, DeepSeek V3.1 and GPT-OSS 120B in us-west-2 through an OpenAI-compatible API only. In its own benchmark it measured over 1,000 tokens per second on GPT-OSS 120B, priced at $0.21 in and $0.79 out.

Pick OpenScale for a cheap backend in Claude Code or other coding agents, cache-heavy traffic and long context. Pick General Compute when output speed matters more than price, or when you need fine-tuned checkpoints or dedicated capacity, which OpenScale does not offer.

What OpenScale and General Compute do

OpenScale

OpenScale is a Y Combinator-backed inference API built by LatentSpace and run out of Singapore. It sells open models behind one endpoint that speaks Chat Completions, the OpenAI Responses API and Anthropic Messages, so Claude Code, Codex, OpenCode, Cline, GitHub Copilot, Zed and other coding agents can point at it with a base URL and key. Its public catalog today is DeepSeek V4.1 Flash in two versions, standard and fast, both with a 1M token context window and up to 384K output tokens.

Example models: DeepSeek V4.1 Flash

Full OpenScale 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 OpenScale or General Compute?

OpenScale

Choose OpenScale for

Low prices on cached input
1M token context
Anthropic Messages for coding agents

General Compute

Choose General Compute for

Fast output on GPT-OSS 120B
Custom fine-tuned checkpoints
Dedicated racks and SLAs

OpenScale vs General Compute at a glance

Attribute	OpenScale	General Compute
Model access	Open weights	Open weights
Flagship models	DeepSeek V4.1 Flash	MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B
Speed	200+ tok/s; fast tier ~2x	1,000+ tok/s on GPT-OSS 120B (vendor)
Price	$0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash)	$0.21–$0.28 in, $0.38–$1.20 out per 1M
Customization	N/A	Custom LoRA and fine-tuned checkpoints
Deployment	Serverless API	Serverless API, dedicated racks, bare metal
Long context	1M context	192K (MiniMax M2.7)

Frequently asked questions

What is the difference between OpenScale and General Compute?

OpenScale sells DeepSeek V4.1 Flash cheaply with 1M context. General Compute sells fast decode on older open models from a US region.

When should I choose OpenScale over General Compute?

Low prices on cached input; 1M token context; Anthropic Messages for coding agents.

When should I choose General Compute over OpenScale?

Fast output on GPT-OSS 120B; Custom fine-tuned checkpoints; Dedicated racks and SLAs.

Is OpenScale or General Compute cheaper?

OpenScale: $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash). 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, OpenScale or General Compute?

OpenScale: 1M context. 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 OpenScale Subconscious vs General Compute