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Dolphin vs General Compute
Dolphin sells DeepSeek V4.1 Flash at very low prices on consumer GPUs. General Compute sells speed on open models with ASIC decode.
By The Subconscious Team · Updated
Dolphin vs General Compute: key differences
Dolphin's API launched in October 2026 with 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. General Compute does not serve V4.1 Flash. Its catalog is MiniMax M2.7, DeepSeek V3.2, DeepSeek V3.1 and GPT-OSS 120B in us-west-2, from $0.21 in per million tokens. In its own benchmark it measured over 1,000 tokens per second on GPT-OSS 120B.
Pick Dolphin for the lowest price on latency-tolerant batch work, or for uncensored fine-tunes. Pick General Compute when response speed matters, as in agent loops and voice, or when procurement needs standard plans, contracts and a throughput SLA.
What Dolphin and General Compute do
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 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 profileShould you choose Dolphin or General Compute?
Dolphin
Choose Dolphin for
- The lowest price on DeepSeek V4.1 Flash
- Uncensored fine-tunes
- Latency-tolerant batch work
General Compute
Choose General Compute for
- Fast output in agent and voice loops
- Standard plans and contracts
- Throughput SLAs on dedicated racks
Dolphin vs General Compute at a glance
| Attribute |  Dolphin |  General Compute |
|---|---|---|
| Model access | Open weights, uncensored fine-tunes | Open weights |
| Flagship models | DeepSeek V4.1 Flash, Dolphin Mistral 24B | MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B |
| Speed | Unknown | 1,000+ tok/s on GPT-OSS 120B (vendor) |
| Price | $0.01 in, $0.07 out (DeepSeek V4.1 Flash) | $0.21–$0.28 in, $0.38–$1.20 out per 1M |
| Customization | Own uncensored fine-tunes | Custom LoRA and fine-tuned checkpoints |
| Deployment | Decentralized serverless API | Serverless API, dedicated racks, bare metal |
| Long context | Unknown | 192K (MiniMax M2.7) |
Frequently asked questions
What is the difference between Dolphin and General Compute?
Dolphin sells DeepSeek V4.1 Flash at very low prices on consumer GPUs. General Compute sells speed on open models with ASIC decode.
When should I choose Dolphin over General Compute?
The lowest price on DeepSeek V4.1 Flash; Uncensored fine-tunes; Latency-tolerant batch work.
When should I choose General Compute over Dolphin?
Fast output in agent and voice loops; Standard plans and contracts; Throughput SLAs on dedicated racks.
Is Dolphin or General Compute cheaper?
Dolphin: $0.01 in, $0.07 out (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.
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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.