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DeepSeek vs Hyperbolic: Token Pricing, Speed & Intelligence

Full comparison of DeepSeek and Hyperbolic — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.

DeepSeek

Chinese frontier lab — DeepSeek V3 and R1 at remarkably low prices

DeepSeek is a Chinese AI lab that has released highly capable open-weight models at prices far below Western competitors. DeepSeek V3 matches GPT-4 class performance at $0.27/1M input tokens, while DeepSeek R1 is a reasoning model competitive with o1 at a fraction of the cost. Both models are open-weight.

Cost-efficiencyReasoningCodingOpen-sourceSelf-hosting
Proprietary models

Hyperbolic

Open-source inference marketplace — Llama, DeepSeek R1, and more

Hyperbolic provides a marketplace for open-source model inference, hosting Llama 3.3, DeepSeek R1, and other popular models at competitive prices. Their platform emphasises accessibility and affordability, making frontier open-weight models available to developers and researchers at low cost.

Cost-efficiencyResearchOpen-sourceExperimentationBudget workloads
Open-weight hostHosts open weights

Key metrics

Cheapest input ($/1M)

Cheapest output ($/1M)

Peak throughput

Best latency (TTFT)

Intelligence score

Context window

Live token pricing

Strengths & weaknesses

DeepSeek

DeepSeek V3 matches GPT-4 class at $0.27/1M input — 10× cheaper
R1 reasoning model competitive with o1 at a fraction of the cost
Both V3 and R1 are open-weight — can be self-hosted
Mixture-of-Experts architecture for efficient inference
Strong coding and math benchmarks
Data residency in China — may not meet compliance requirements
API reliability can lag Western providers during peak demand
Limited multimodal capability vs. Gemini or GPT-4o

Hyperbolic

Among the lowest prices for open-weight model inference
DeepSeek R1 and Llama 3.3 available at competitive rates
Marketplace model — broad model selection
OpenAI-compatible API
Good for research and experimentation
Less established reliability than larger providers
Throughput lower than Groq/Cerebras for speed-critical apps
No fine-tuning support

Key differentiators

DeepSeek

DeepSeek V3 delivers GPT-4 class intelligence at $0.27/1M input tokens — the most disruptive price-to-performance ratio in the LLM market.

Hyperbolic

One of the most affordable inference marketplaces for open-weight models — ideal for researchers and cost-sensitive workloads.

Frequently asked questions

DeepSeek FAQs

How much does DeepSeek cost?

DeepSeek V3 costs $0.27/1M input and $1.10/1M output tokens — roughly 10× cheaper than GPT-4o for comparable capability. DeepSeek R1 is $0.55/1M input and $2.19/1M output.

Is DeepSeek open-weight?

Yes. Both DeepSeek V3 and DeepSeek R1 are open-weight models available on Hugging Face. You can self-host them on your own GPU infrastructure, though they require significant compute (671B parameters for R1).

How does DeepSeek R1 compare to OpenAI o1?

DeepSeek R1 scores comparably to OpenAI o1 on math and coding benchmarks at a fraction of the cost. R1 is open-weight and can be self-hosted, while o1 is proprietary. R1 is available via multiple inference providers including Fireworks AI and Together AI.

Hyperbolic FAQs

What models does Hyperbolic offer?

Hyperbolic hosts Llama 3.3 70B, DeepSeek R1, and other popular open-weight models. Their marketplace approach means the catalog evolves frequently.

How does Hyperbolic pricing compare to competitors?

Hyperbolic is among the most affordable options for open-weight model inference, often undercutting Together AI and Fireworks AI on price. This makes it attractive for high-volume or cost-sensitive workloads.

Is Hyperbolic reliable for production use?

Hyperbolic is newer and less established than providers like Together AI or Fireworks AI. It's well-suited for research, prototyping, and cost-sensitive workloads, but for mission-critical production use, a more established provider may be preferable.

Provider resources

DeepSeekChinese frontier lab — DeepSeek V3 and R1 at remarkably low prices

DeepSeek is a Chinese AI lab that has released highly capable open-weight models at prices far below Western competitors. DeepSeek V3 matches GPT-4 class performance at $0.27/1M input tokens, while DeepSeek R1 is a reasoning model competitive with o1 at a fraction of the cost. Both models are open-weight.

DeepSeek V3 delivers GPT-4 class intelligence at $0.27/1M input tokens — the most disruptive price-to-performance ratio in the LLM market.

HyperbolicOpen-source inference marketplace — Llama, DeepSeek R1, and more

Hyperbolic provides a marketplace for open-source model inference, hosting Llama 3.3, DeepSeek R1, and other popular models at competitive prices. Their platform emphasises accessibility and affordability, making frontier open-weight models available to developers and researchers at low cost.

One of the most affordable inference marketplaces for open-weight models — ideal for researchers and cost-sensitive workloads.

Key strengths compared

DeepSeek

  • DeepSeek V3 matches GPT-4 class at $0.27/1M input — 10× cheaper
  • R1 reasoning model competitive with o1 at a fraction of the cost
  • Both V3 and R1 are open-weight — can be self-hosted

Hyperbolic

  • Among the lowest prices for open-weight model inference
  • DeepSeek R1 and Llama 3.3 available at competitive rates
  • Marketplace model — broad model selection

Provider category context

DeepSeek is a frontier lab, founded in 2023. Hyperbolic is a inference api, founded in 2023. DeepSeek as a frontier lab trains and serves its own proprietary models. Hyperbolic as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.

How to choose between them

Choose DeepSeek if you need deepseek v3 matches gpt-4 class at $0.27/1m input — 10× cheaper. Choose Hyperbolic if you need among the lowest prices for open-weight model inference. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.