DeepInfra vs General Compute

DeepInfra is the price floor across 150+ open models. General Compute serves four open models with decode on ASICs and sells speed first.

By The Subconscious Team · Updated October 27, 2026

DeepInfra vs General Compute: key differences

DeepInfra serves 150+ open models through an OpenAI-compatible API with no minimums, from $0.02 per million tokens on Llama 3.1 8B and $0.09 in and $0.18 out on DeepSeek V4 Flash, with 1M context on DeepSeek V4 Pro. Some endpoints run FP4 quantization. General Compute charges $0.21 to $0.28 in and $0.38 to $1.20 out per million tokens on MiniMax M2.7, DeepSeek V3.2, DeepSeek V3.1 and GPT-OSS 120B, with context up to 192K. It runs decode on ASICs and reports over 1,000 tokens per second on GPT-OSS 120B in its own benchmark.

DeepInfra is the pick for cost-first bulk work across a wide catalog, as long as teams check precision per model. General Compute fits workloads that pay for speed, like agent loops and voice. It also serves custom LoRA or fine-tuned checkpoints behind a private model ID and sells dedicated racks under a tokens-per-second SLA.

What DeepInfra and General Compute do

DeepInfra

DeepInfra is the price floor for open-model inference. Developers treat it as the reference point for what a token should cost, with small models like Llama 3.1 8B at $0.02 per million and DeepSeek V4 Flash at $0.09 in and $0.18 out. The catalog covers 150+ open models across text, image and speech behind a fully OpenAI-compatible API. There are no minimums, setup fees or contracts on the shared API.

Example models: DeepSeek V4 Flash, Llama 3.1 8B

Full DeepInfra 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 DeepInfra or General Compute?

DeepInfra

Choose DeepInfra for

Lowest per-token prices
Bulk extraction and tagging
Broad open-model catalog

General Compute

Choose General Compute for

Decode speed for agent loops
Private fine-tuned model IDs
Throughput SLAs on dedicated racks

DeepInfra vs General Compute at a glance

Attribute	DeepInfra	General Compute
Model access	Open weights	Open weights
Flagship models	DeepSeek V4 Flash, Llama 3.1 8B	MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B
Speed	Unknown	1,000+ tok/s on GPT-OSS 120B (vendor)
Price	From $0.02 per 1M	$0.21–$0.28 in, $0.38–$1.20 out per 1M
Customization	No managed fine-tuning	Custom LoRA and fine-tuned checkpoints
Deployment	Shared API, no contracts	Serverless API, dedicated racks, bare metal
Long context	1M on DeepSeek V4 Pro	192K (MiniMax M2.7)

Frequently asked questions

What is the difference between DeepInfra and General Compute?

DeepInfra is the price floor across 150+ open models. General Compute serves four open models with decode on ASICs and sells speed first.

When should I choose DeepInfra over General Compute?

Lowest per-token prices; Bulk extraction and tagging; Broad open-model catalog.

When should I choose General Compute over DeepInfra?

Decode speed for agent loops; Private fine-tuned model IDs; Throughput SLAs on dedicated racks.

Is DeepInfra or General Compute cheaper?

DeepInfra: From $0.02 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, DeepInfra or General Compute?

DeepInfra: 1M on DeepSeek V4 Pro. 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 DeepInfra Subconscious vs General Compute