DeepSeek vs Moonshot AI: Token Pricing, Speed & Intelligence

Full comparison of DeepSeek and Moonshot AI — 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

Moonshot AI

Kimi — long-context frontier models from China's leading AI lab

Moonshot AI is a Chinese AI startup behind the Kimi model family. Kimi K2 is a 1-trillion-parameter MoE model released as open-weight, competitive with frontier models on coding and agentic tasks. The Kimi API offers long-context processing up to 128K tokens with competitive pricing.

CodingAgentsLong-contextReasoningMultilingual

Proprietary modelsHosts open weights

Key metrics

Cheapest input ($/1M)

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Cheapest output ($/1M)

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Peak throughput

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Best latency (TTFT)

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Intelligence score

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Context window

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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

Moonshot AI

Kimi K2 is a 1T MoE open-weight model with strong coding scores

Competitive on agentic and tool-use benchmarks

Long-context support up to 128K tokens

Open-weight release enables self-hosting

Strong performance on Chinese-language tasks

API primarily targets Chinese market — international latency may vary

Smaller ecosystem than OpenAI or Anthropic

Fewer third-party integrations available

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.

Moonshot AI

Kimi K2 is a 1-trillion-parameter open-weight MoE model that scores competitively with Claude Sonnet on coding and agentic benchmarks.

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.

Moonshot AI FAQs

What is Kimi K2?

Kimi K2 is a 1-trillion-parameter mixture-of-experts model from Moonshot AI, released as open-weight. It activates approximately 32B parameters per token and is designed for coding, agentic tasks, and long-context reasoning.

Is Kimi K2 open-weight?

Yes. Kimi K2 weights are publicly available on Hugging Face, making it one of the largest open-weight models available. Teams can self-host it on multi-GPU clusters or access it via the Moonshot API.

How does Kimi K2 compare to Claude Sonnet?

Kimi K2 scores competitively with Claude Sonnet 4 on coding benchmarks including SWE-bench. It is particularly strong on agentic tasks that require tool use and multi-step planning.

Provider resources

DeepSeek

Provider page Website Pricing Docs

Moonshot AI

Provider page Website Pricing Docs

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

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

Moonshot AI — Kimi — long-context frontier models from China's leading AI lab

Kimi K2 is a 1-trillion-parameter open-weight MoE model that scores competitively with Claude Sonnet on coding and agentic benchmarks.

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

Moonshot AI

▸Kimi K2 is a 1T MoE open-weight model with strong coding scores
▸Competitive on agentic and tool-use benchmarks
▸Long-context support up to 128K tokens

Provider category context

DeepSeek is a frontier lab, founded in 2023. Moonshot AI is a frontier lab, founded in 2023. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.

How to choose between them

Both DeepSeek and Moonshot AI are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: DeepSeek leads on deepseek v3 matches gpt-4 class at $0.27/1m input — 10× cheaper, while Moonshot AI leads on kimi k2 is a 1t moe open-weight model with strong coding scores. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.