As of August 20, 2026, GPT-5.6 Luna is 7% cheaper per million tokens than Inkling-Small. GPT-5.6 Luna is $0.20 / $1.20 per million input/output tokens versus Inkling-Small at $0.30 / $1.20. Sources: https://developers.openai.com/api/docs/pricing and https://thinkingmachines.ai
Sources: OpenAI API pricing (https://developers.openai.com/api/docs/pricing); Thinking Machines Lab pricing (https://thinkingmachines.ai)
GPT-5.6 Luna
OpenAI
Input
$0.20
Output
$1.20
Inkling-Small
Thinking Machines
Input
$0.30
Output
$1.20
Token pricing, specs, and benchmarks side by side
GPT-5.6 LunaInkling-SmallVerdict
GPT-5.6 Luna offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.
As of August 20, 2026, GPT-5.6 Luna is 7% cheaper on blended LLM API pricing. GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens ($1.40 blended 1M-in + 1M-out). Inkling-Small costs $0.30 / $1.20 per million tokens ($1.50 blended). Sources: https://developers.openai.com/api/docs/pricing and https://thinkingmachines.ai. The cheapest LLM for your app still depends on how many output tokens you generate.
GPT-5.6 Luna OpenAI API pricing is $0.20 input and $1.20 output per million tokens via OpenAI. Inkling-Small Thinking Machines Lab API pricing is $0.30 input and $1.20 output per million tokens via Thinking Machines Lab. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
GPT-5.6 Luna leads on SWE-bench Verified: GPT-5.6 Luna at 93% vs Inkling-Small at 80.2%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
GPT-5.6 Luna supports a 1M token context window, while Inkling-Small supports 256K tokens. GPT-5.6 Luna 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.
GPT-5.6 Luna leads on 23 of 28 shared benchmarks versus Inkling-Small's 5 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 GPT-5.6 Luna and Inkling-Small are production API models. For cost-sensitive production traffic, GPT-5.6 Luna 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 GPT-5.6 Luna through OpenAI and Inkling-Small through Thinking Machines Lab 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 OpenAI API pricing and Thinking Machines Lab API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://thinkingmachines.ai. 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.
GPT-5.6 Luna supports up to 128K output tokens per request, while Inkling-Small supports up to 256K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
GPT-5.6 Luna has a measured throughput of approximately 48.45216448188169 tokens/second. Throughput data for Inkling-Small 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 GPT-5.6 Luna or Inkling-Small 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. GPT-5.6 Luna costs $0.20/M input and $1.20/M output. Inkling-Small costs $0.30/M input and $1.20/M output via Thinking Machines Lab.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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