As of August 30, 2026, Gemini 1.0 Pro is 25% cheaper per million tokens than Kimi-k1.5. Gemini 1.0 Pro is $0.50 / $1.50 per million input/output tokens versus Kimi-k1.5 at $0.15 / $2.50. Sources: https://ai.google.dev/gemini-api/docs/pricing and https://platform.moonshot.ai/docs/pricing
Sources: Gemini API pricing (https://ai.google.dev/gemini-api/docs/pricing); Moonshot AI pricing (https://platform.moonshot.ai/docs/pricing)
Gemini 1.0 Pro
Input
$0.50
Output
$1.50
Kimi-k1.5
Moonshot AI
Input
$0.15
Output
$2.50
Token pricing, specs, and benchmarks side by side
Each bar is share of the current leader on that eval. Click a row to open the board.
MMLU. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.
Gemini 1.0 ProKimi-k1.5Verdict
Gemini 1.0 Pro offers significantly lower pricing, while Kimi-k1.5 leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.
As of August 30, 2026, Gemini 1.0 Pro is 25% cheaper on blended LLM API pricing. Gemini 1.0 Pro costs $0.50 per million input tokens and $1.50 per million output tokens ($2.00 blended 1M-in + 1M-out). Kimi-k1.5 costs $0.15 / $2.50 per million tokens ($2.65 blended). Sources: https://ai.google.dev/gemini-api/docs/pricing and https://platform.moonshot.ai/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
Gemini 1.0 Pro Gemini API pricing is $0.50 input and $1.50 output per million tokens via Google. Kimi-k1.5 Moonshot AI API pricing is $0.15 input and $2.50 output per million tokens via Moonshot AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Neither Gemini 1.0 Pro nor Kimi-k1.5 has a published SWE-bench or LiveCodeBench score on this page yet. Use the comparison table for the evals that do exist.
Gemini 1.0 Pro supports a 33K token context window, while Kimi-k1.5 supports 128K tokens. Kimi-k1.5 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Kimi-k1.5 leads on 3 of 3 shared benchmarks versus Gemini 1.0 Pro's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Both Gemini 1.0 Pro and Kimi-k1.5 are production API models. For cost-sensitive production traffic, Gemini 1.0 Pro has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Yes. Call Gemini 1.0 Pro through Google and Kimi-k1.5 through Moonshot AI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
List rates are the latest published Gemini API pricing and Moonshot AI API pricing, quoted per million tokens. Official rate sheets: https://ai.google.dev/gemini-api/docs/pricing and https://platform.moonshot.ai/docs/pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
Gemini 1.0 Pro supports up to 8K output tokens per request, while Kimi-k1.5 supports up to an unspecified number of output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Gemini 1.0 Pro has a measured throughput of approximately 120 tokens/second. Throughput data for Kimi-k1.5 is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Gemini 1.0 Pro or Kimi-k1.5 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. Gemini 1.0 Pro costs $0.50/M input and $1.50/M output. Kimi-k1.5 costs $0.15/M input and $2.50/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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