Google vs Moonshot AI: Token Pricing, Speed & Intelligence

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

Google

Gemini 2.5 — the largest context window at the lowest frontier price

Google DeepMind's Gemini family offers some of the most competitive frontier pricing, with Gemini 2.5 Pro delivering top-tier intelligence at $1.25/1M input tokens. The 1M+ token context window is the largest available. Gemini 2.5 Flash is a standout efficient model for vision and multimodal tasks.

VisionLong-contextCodingMultimodalCost-efficiency

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

Google

1M+ token context window — largest available

Best price-per-intelligence at frontier tier ($1.25/1M input)

Native multimodal: text, image, audio, video

Gemini 2.5 Flash is the best efficient vision model

Free tier available via Google AI Studio

No open-weight models

Complex tiered pricing based on context length

API reliability has historically lagged OpenAI

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

Google

Gemini 2.5 Pro delivers frontier-tier intelligence at $1.25/1M input tokens — the best price-to-performance ratio among all frontier models.

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

Google FAQs

How much does the Google Gemini API cost?

Gemini 2.5 Pro costs $1.25/1M input tokens (up to 200K context) and $10/1M output. Gemini 2.5 Flash is $0.15/$0.60 per 1M tokens. Gemini 2.0 Flash is even cheaper at $0.10/$0.40 per 1M tokens.

What is the context window for Gemini models?

Gemini 2.5 Pro and Flash both support a 1,048,576-token (1M+) context window — the largest available from any major LLM provider. This makes them ideal for processing entire codebases, books, or long document collections.

Does Gemini support vision and multimodal inputs?

Yes. All Gemini 2.x models natively support images, audio, and video inputs alongside text. Gemini 2.5 Flash is particularly strong for vision tasks at a low cost.

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

Google

Provider page Website Pricing Docs

Moonshot AI

Provider page Website Pricing Docs

Google — Gemini 2.5 — the largest context window at the lowest frontier price

Gemini 2.5 Pro delivers frontier-tier intelligence at $1.25/1M input tokens — the best price-to-performance ratio among all frontier models.

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

Google

▸1M+ token context window — largest available
▸Best price-per-intelligence at frontier tier ($1.25/1M input)
▸Native multimodal: text, image, audio, video

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

Google is a frontier lab, founded in 1998. 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 Google and Moonshot AI are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: Google leads on 1m+ token context window — largest available, 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.