As of August 20, 2026, Kimi K2 Instruct is 33% cheaper per million tokens than Inkling-Small. Inkling-Small is $0.30 / $1.20 per million input/output tokens versus Kimi K2 Instruct at $0.50 / $0.50. Sources: https://thinkingmachines.ai and https://platform.kimi.com/docs/pricing/chat
Sources: Thinking Machines Lab pricing (https://thinkingmachines.ai); Moonshot AI pricing (https://platform.kimi.com/docs/pricing/chat)
Inkling-Small
Thinking Machines
Input
$0.30
Output
$1.20
Kimi K2 Instruct
Moonshot AI
Input
$0.50
Output
$0.50
Token pricing, specs, and benchmarks side by side
Inkling-SmallKimi K2 InstructVerdict
Kimi K2 Instruct offers significantly lower pricing, while Inkling-Small leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.
As of August 20, 2026, Kimi K2 Instruct is 33% cheaper on blended LLM API pricing. Kimi K2 Instruct costs $0.50 per million input tokens and $0.50 per million output tokens ($1.00 blended 1M-in + 1M-out). Inkling-Small costs $0.30 / $1.20 per million tokens ($1.50 blended). Sources: https://thinkingmachines.ai and https://platform.kimi.com/docs/pricing/chat. The cheapest LLM for your app still depends on how many output tokens you generate.
Inkling-Small Thinking Machines Lab API pricing is $0.30 input and $1.20 output per million tokens via Thinking Machines Lab. Kimi K2 Instruct Moonshot AI API pricing is $0.50 input and $0.50 output per million tokens via Moonshot AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Inkling-Small leads on SWE-bench Verified: Inkling-Small at 80.2% vs Kimi K2 Instruct at 43.8%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
Inkling-Small supports a 256K token context window, while Kimi K2 Instruct supports 200K tokens. Inkling-Small 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.
Inkling-Small leads on 9 of 10 shared benchmarks versus Kimi K2 Instruct's 1 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 Inkling-Small and Kimi K2 Instruct are production API models. For cost-sensitive production traffic, Kimi K2 Instruct 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 Inkling-Small through Thinking Machines Lab and Kimi K2 Instruct 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 Thinking Machines Lab API pricing and Moonshot AI API pricing, quoted per million tokens. Official rate sheets: https://thinkingmachines.ai 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.
Inkling-Small supports up to 256K output tokens per request, while Kimi K2 Instruct supports up to 200K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Neither Inkling-Small nor Kimi K2 Instruct has published throughput data on this page yet. 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 Inkling-Small or Kimi K2 Instruct 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. Inkling-Small costs $0.30/M input and $1.20/M output via Thinking Machines Lab. Kimi K2 Instruct costs $0.50/M input and $0.50/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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