Which is cheaper, GPT-5.1 Codex Mini or Kimi-k1.5?
As of August 30, 2026, GPT-5.1 Codex Mini is 15% cheaper on blended LLM API pricing. GPT-5.1 Codex Mini costs $0.25 per million input tokens and $2.00 per million output tokens ($2.25 blended 1M-in + 1M-out). Kimi-k1.5 costs $0.15 / $2.50 per million tokens ($2.65 blended). Sources: https://developers.openai.com/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.
How much does GPT-5.1 Codex Mini vs Kimi-k1.5 cost per million tokens?
GPT-5.1 Codex Mini OpenAI API pricing is $0.25 input and $2.00 output per million tokens via OpenAI. 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.
Which is better for coding, GPT-5.1 Codex Mini or Kimi-k1.5?
Neither GPT-5.1 Codex Mini 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.
What is the context window for GPT-5.1 Codex Mini vs Kimi-k1.5?
GPT-5.1 Codex Mini supports a 400K token context window, while Kimi-k1.5 supports 128K tokens. GPT-5.1 Codex Mini 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.
Which model performs better on benchmarks, GPT-5.1 Codex Mini or Kimi-k1.5?
GPT-5.1 Codex Mini leads on 1 of 1 shared benchmarks versus Kimi-k1.5'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.
Is GPT-5.1 Codex Mini or Kimi-k1.5 better for production use?
Both GPT-5.1 Codex Mini and Kimi-k1.5 are production API models. For cost-sensitive production traffic, GPT-5.1 Codex Mini 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.
Can I switch between GPT-5.1 Codex Mini and Kimi-k1.5 in my app?
Yes. Call GPT-5.1 Codex Mini through OpenAI 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.
How accurate is this GPT-5.1 Codex Mini vs Kimi-k1.5 pricing data?
List rates are the latest published OpenAI API pricing and Moonshot AI API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/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.
What is the output token limit for GPT-5.1 Codex Mini and Kimi-k1.5?
GPT-5.1 Codex Mini supports up to 128K 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.
Which model has better throughput, GPT-5.1 Codex Mini or Kimi-k1.5?
GPT-5.1 Codex Mini has a measured throughput of approximately 200 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.
How do I switch the models in this GPT-5.1 Codex Mini vs Kimi-k1.5 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-5.1 Codex Mini 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.
