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Inception vs Dolphin
Inception sells closed diffusion models built for speed. Dolphin sells one open model at a very low price on consumer GPUs.
By The Subconscious Team · Updated
Inception vs Dolphin: key differences
Inception sells closed Mercury diffusion models that refine a block of tokens in parallel instead of one at a time. Mercury 2.5 is a reasoning model with tool use and 260K context at $0.20 in and $0.75 out per million tokens; Inception reports over 1,100 tokens per second, and Artificial Analysis measures about 640. It is also sold through AWS Bedrock, Azure Foundry and OpenRouter. Dolphin's API launched in October 2026 with one model, DeepSeek V4.1 Flash, at $0.01 in and $0.07 out per million tokens, served on idle consumer GPUs across a decentralized network. It publishes no speed, context or SLA, and signup runs through a crypto wallet and Telegram.
Inception fits latency-critical work like autocomplete, voice agents and real-time chat, with standard cloud procurement. Dolphin is far cheaper per token but has no published speed or SLA, so it fits background jobs and products that need uncensored models.
What Inception and Dolphin do
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
Dolphin
Dolphin began in 2023 as Eric Hartford's series of open-source, uncensored fine-tunes, trained to drop the refusals and baked-in guidelines of their base models so that the developer sets the rules through the system prompt. Current releases include Dolphin Llama 3.1 8B and Dolphin Mistral 24B Venice Edition, built with Venice, and the project publishes nearly 100 models on Hugging Face. It also runs a chat app, a Telegram bot and a synthetic data service that generates answers to commonly refused prompts.
Example models: DeepSeek V4.1 Flash, Dolphin Mistral 24B
Full Dolphin profileShould you choose Inception or Dolphin?
Inception vs Dolphin at a glance
| Attribute |  Inception |  Dolphin |
|---|---|---|
| Model access | Closed weights (Mercury dLLMs) | Open weights, uncensored fine-tunes |
| Flagship models | Mercury 2.5, Mercury 2 | DeepSeek V4.1 Flash, Dolphin Mistral 24B |
| Speed | 1,100+ tok/s (vendor); ~640 measured | Unknown |
| Price | $0.20 in, $0.75 out (Mercury 2.5) | $0.01 in, $0.07 out (DeepSeek V4.1 Flash) |
| Customization | Fine-tuning on request | Own uncensored fine-tunes |
| Deployment | Serverless API, Bedrock, Azure, private | Decentralized serverless API |
| Long context | 260K | Unknown |
Frequently asked questions
What is the difference between Inception and Dolphin?
Inception sells closed diffusion models built for speed. Dolphin sells one open model at a very low price on consumer GPUs.
When should I choose Inception over Dolphin?
Very fast output on standard GPUs; Cheap reasoning with tool use and 260K context; Buying through AWS Bedrock or Azure.
When should I choose Dolphin over Inception?
Very low prices on DeepSeek V4.1 Flash; Cheap background or batch calls; Models without vendor-imposed refusals.
Is Inception or Dolphin cheaper?
Inception: $0.20 in, $0.75 out (Mercury 2.5). Dolphin: $0.01 in, $0.07 out (DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
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.