As of August 20, 2026, MAI-Code-1.1-Flash is 7% cheaper per million tokens than Inkling-Small. Inkling-Small is $0.30 / $1.20 per million input/output tokens versus MAI-Code-1.1-Flash at $0.20 / $1.20. Sources: https://thinkingmachines.ai and https://ai.azure.com
Sources: Thinking Machines Lab pricing (https://thinkingmachines.ai); Microsoft pricing (https://ai.azure.com)
Inkling-Small
Thinking Machines
Input
$0.30
Output
$1.20
MAI-Code-1.1-Flash
Microsoft
Input
$0.20
Output
$1.20
Token pricing, specs, and benchmarks side by side
Inkling-SmallMAI-Code-1.1-FlashVerdict
MAI-Code-1.1-Flash 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, MAI-Code-1.1-Flash is 7% cheaper on blended LLM API pricing. MAI-Code-1.1-Flash 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://thinkingmachines.ai and https://ai.azure.com. 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. MAI-Code-1.1-Flash Microsoft API pricing is $0.20 input and $1.20 output per million tokens via Microsoft. 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 MAI-Code-1.1-Flash at 72.6%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
Inkling-Small supports a 256K token context window, while MAI-Code-1.1-Flash supports 256K tokens. Both models have the same context window size. 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 2 of 2 shared benchmarks versus MAI-Code-1.1-Flash'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 Inkling-Small and MAI-Code-1.1-Flash are production API models. For cost-sensitive production traffic, MAI-Code-1.1-Flash 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 MAI-Code-1.1-Flash through Microsoft 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 Microsoft API pricing, quoted per million tokens. Official rate sheets: https://thinkingmachines.ai and https://ai.azure.com. 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 MAI-Code-1.1-Flash 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.
Neither Inkling-Small nor MAI-Code-1.1-Flash 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 MAI-Code-1.1-Flash 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. MAI-Code-1.1-Flash costs $0.20/M input and $1.20/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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