Hugging Face Inference Providers vs Dolphin
Hugging Face routes across 17 established providers. Dolphin is a single decentralized network with one hosted model.
By The Subconscious Team · Updated
Hugging Face Inference Providers vs Dolphin: key differences
Hugging Face's router covers 132 chat models, including DeepSeek V4.1 Flash, on partners like Groq, Fireworks and Together, with pass-through pricing and failover when a provider is flagged unavailable. 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. It publishes no speed, context or SLA, and signup needs a crypto wallet and Telegram.
Hugging Face is the safer default for model choice and failover. Dolphin is worth a look for very cheap background calls on DeepSeek V4.1 Flash and for uncensored models, but its consumer GPUs make latency and uptime less predictable.
What Hugging Face Inference Providers and Dolphin do
Hugging Face Inference Providers
Inference Providers is a router run by Hugging Face that sits in front of partner inference clouds. The current partner list covers Baseten, Cerebras, Cohere, DeepInfra, fal, Featherless AI, Fireworks, Groq, Novita, Nscale, OVHcloud, Public AI, Replicate, Scaleway, Together, WaveSpeedAI and Z.ai, plus Hugging Face's own HF Inference, which now mostly serves CPU workloads like embeddings and classification. Chat traffic goes through an OpenAI-compatible endpoint at router.huggingface.co/v1, and the Python and JavaScript clients add text-to-image, video, speech and embeddings. The router lists 132 chat models today, from GLM 5.3 and Kimi K3 to gpt-oss-120b on eleven providers.
Example models: GLM 5.3, Kimi K3, gpt-oss-120b
Full Hugging Face Inference Providers profileDolphin
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 Hugging Face Inference Providers or Dolphin?
Hugging Face Inference Providers
Choose Hugging Face Inference Providers for
- Many open models on one key and bill
- Automatic failover across hosts
- Comparing providers
Dolphin
Choose Dolphin for
- Very cheap DeepSeek V4.1 Flash calls
- Uncensored models
- Requests nodes cannot log
Hugging Face Inference Providers vs Dolphin at a glance
| Attribute | ||
|---|---|---|
| Model access | Open weights | Open weights, uncensored fine-tunes |
| Flagship models | GLM 5.3, Kimi K3, DeepSeek V4.1 Flash | DeepSeek V4.1 Flash, Dolphin Mistral 24B |
| Speed | Routes to fastest provider by default | Unknown |
| Price | Provider rates, no markup | $0.01 in, $0.07 out (DeepSeek V4.1 Flash) |
| Customization | N/A | Own uncensored fine-tunes |
| Deployment | Serverless router; dedicated Endpoints | Decentralized serverless API |
| Long context | Up to 1M, provider-dependent | Unknown |
Frequently asked questions
What is the difference between Hugging Face Inference Providers and Dolphin?
Hugging Face routes across 17 established providers. Dolphin is a single decentralized network with one hosted model.
When should I choose Hugging Face Inference Providers over Dolphin?
Many open models on one key and bill; Automatic failover across hosts; Comparing providers.
When should I choose Dolphin over Hugging Face Inference Providers?
Very cheap DeepSeek V4.1 Flash calls; Uncensored models; Requests nodes cannot log.
Is Hugging Face Inference Providers or Dolphin cheaper?
Hugging Face Inference Providers: Provider rates, no markup. Dolphin: $0.01 in, $0.07 out (DeepSeek V4.1 Flash). 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.