Inference.net vs Inception

Inference.net sells cheap batch inference on spare GPUs and distills custom models from traces. Inception sells fast real-time output from its own diffusion LLMs.

By The Subconscious Team · Updated October 11, 2026

Inference.net vs Inception: key differences

Inference.net's Batch API takes up to 1M requests per file with 24-hour to 7-day windows, priced off discounted spare capacity, and its gateway turns production traffic into datasets for fine-tuned models served on dedicated GPUs with a 99.99% uptime target. Inception's Mercury 2.5 is a closed diffusion reasoning model with tool use and 260K context at $0.20 in and $0.75 out. Inception reports 1,100+ tokens per second; Artificial Analysis measures about 640.

The two sit at opposite ends of latency. Inference.net fits large offline jobs and teams replacing a closed API with their own distilled model. Inception fits interactive work like autocomplete and voice, where a fast cost-optimized model beats a slow strong one.

What Inference.net and Inception do

Inference.net

Inference.net started as a buyer of last resort for idle GPU time. Its scheduler aggregates small unused chunks of capacity across data centers and runs models on them, and it passes the steep discounts it gets from those data centers on to customers. That origin still shows in its OpenAI-compatible Batch API, which takes up to 1M requests per file with completion windows from 24 hours to 7 days and far higher headroom than synchronous limits.

Example models: GLM-5.2, Kimi K2.6, Schematron, customer fine-tunes

Full Inference.net profile

Inception

Inception builds diffusion large language models (dLLMs). Every other LLM on this list generates text one token at a time; Inception's Mercury models start from a rough draft of a whole block and refine it over a few passes, producing many tokens in parallel. That ties speed less to output length and lets the models run fast on ordinary NVIDIA GPUs rather than custom chips. The company was founded by professors from Stanford, UCLA and Cornell behind core work on diffusion, Flash Attention and DPO, and is led by Stanford's Stefano Ermon. It raised a $50M seed in November 2025 led by Menlo Ventures, with Mayfield, M12, NVentures, Snowflake and Databricks, plus Andrew Ng and Andrej Karpathy as angels.

Example models: Mercury 2.5, Mercury 2

Full Inception profile

Should you choose Inference.net or Inception?

Inference.net

Choose Inference.net for

Large offline batch jobs
Distilling traces into a custom model
Dedicated GPUs for fine-tunes

Inception

Choose Inception for

Real-time output at high speed
Code autocomplete and voice agents
Low per-token prices for a reasoning model

Inference.net vs Inception at a glance

Attribute	Inference.net	Inception
Model access	Open, closed and custom	Closed weights (Mercury dLLMs)
Flagship models	Schematron, ClipTagger, customer fine-tunes	Mercury 2.5, Mercury 2
Speed	Batch windows of 24h to 7 days	1,100+ tok/s (vendor); ~640 measured
Price	Free pay-as-you-go; Growth $250/mo; B200 $9.98/hr	$0.20 in, $0.75 out (Mercury 2.5)
Customization	Distill traces into custom models	Fine-tuning on request
Deployment	Batch API, gateway, dedicated GPUs	Serverless API, Bedrock, Azure, private
Long context	Varies by model	260K

Frequently asked questions

What is the difference between Inference.net and Inception?

Inference.net sells cheap batch inference on spare GPUs and distills custom models from traces. Inception sells fast real-time output from its own diffusion LLMs.

When should I choose Inference.net over Inception?

Large offline batch jobs; Distilling traces into a custom model; Dedicated GPUs for fine-tunes.

When should I choose Inception over Inference.net?

Real-time output at high speed; Code autocomplete and voice agents; Low per-token prices for a reasoning model.

Is Inference.net or Inception cheaper?

Inference.net: Free pay-as-you-go; Growth $250/mo; B200 $9.98/hr. Inception: $0.20 in, $0.75 out (Mercury 2.5). The cheaper choice depends on the model and workload.

Which has more context, Inference.net or Inception?

Inference.net: Varies by model. Inception: 260K.

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 Inference.net Subconscious vs Inception