Which is cheaper, Claude 3.5 Haiku or Kimi K3?
As of August 20, 2026, Claude 3.5 Haiku is 73% cheaper on blended LLM API pricing. Claude 3.5 Haiku costs $0.80 per million input tokens and $4.00 per million output tokens ($4.80 blended 1M-in + 1M-out). Kimi K3 costs $3.00 / $15.00 per million tokens ($18.00 blended). Sources: https://platform.claude.com/docs/en/about-claude/pricing and https://platform.kimi.com/docs/pricing/chat. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Claude 3.5 Haiku vs Kimi K3 cost per million tokens?
Claude 3.5 Haiku Claude API pricing from Anthropic is $0.80 input and $4.00 output per million tokens via Anthropic. Kimi K3 Moonshot AI API pricing is $3.00 input and $15.00 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, Claude 3.5 Haiku or Kimi K3?
Kimi K3 leads on SWE-bench Verified: Claude 3.5 Haiku at 40.6% vs Kimi K3 at 93.4%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for Claude 3.5 Haiku vs Kimi K3?
Claude 3.5 Haiku supports a 200K token context window, while Kimi K3 supports 1M tokens. Kimi K3 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, Claude 3.5 Haiku or Kimi K3?
Kimi K3 leads on 11 of 11 shared benchmarks versus Claude 3.5 Haiku'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 Claude 3.5 Haiku or Kimi K3 better for production use?
Both Claude 3.5 Haiku and Kimi K3 are production API models. For cost-sensitive production traffic, Claude 3.5 Haiku 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 Claude 3.5 Haiku and Kimi K3 in my app?
Yes. Call Claude 3.5 Haiku through Anthropic and Kimi K3 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 Claude 3.5 Haiku vs Kimi K3 pricing data?
List rates are the latest published Claude API pricing from Anthropic and Moonshot AI API pricing, quoted per million tokens. Official rate sheets: https://platform.claude.com/docs/en/about-claude/pricing and https://platform.kimi.com/docs/pricing/chat. 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 Claude 3.5 Haiku and Kimi K3?
Claude 3.5 Haiku supports up to 200K output tokens per request, while Kimi K3 supports up to 1M 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, Claude 3.5 Haiku or Kimi K3?
Claude 3.5 Haiku runs at approximately 104 tokens/second while Kimi K3 runs at 8.253358168863906 tokens/second. Claude 3.5 Haiku is faster in raw throughput. 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 Claude 3.5 Haiku vs Kimi K3 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Claude 3.5 Haiku or Kimi K3 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
