As of August 20, 2026, Nemotron Nano 9B v2 is 100% cheaper per million tokens than Inkling-Small. Inkling-Small is $0.30 / $1.20 per million input/output tokens versus Nemotron Nano 9B v2 at $0.00 / $0.00. Sources: https://thinkingmachines.ai and https://openrouter.ai/api/v1/models
Sources: Thinking Machines Lab pricing (https://thinkingmachines.ai); OpenRouter pricing (https://openrouter.ai/api/v1/models)
Inkling-Small
Thinking Machines
Input
$0.30
Output
$1.20
Nemotron Nano 9B v2
NVIDIA
Input
$0.00
Output
$0.00
Token pricing, specs, and benchmarks side by side
Inkling-SmallNemotron Nano 9B v2Verdict
Nemotron Nano 9B v2 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, Nemotron Nano 9B v2 is 100% cheaper on blended LLM API pricing. Nemotron Nano 9B v2 costs $0.00 per million input tokens and $0.00 per million output tokens ($0.00 blended 1M-in + 1M-out). Inkling-Small costs $0.30 / $1.20 per million tokens ($1.50 blended). Sources: https://thinkingmachines.ai and https://openrouter.ai/api/v1/models. 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. Nemotron Nano 9B v2 OpenRouter API pricing is $0.00 input and $0.00 output per million tokens via OpenRouter. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Inkling-Small has a published SWE-bench Verified score of 80.2%. Nemotron Nano 9B v2 does not have that eval on this page yet.
Inkling-Small supports a 256K token context window, while Nemotron Nano 9B v2 supports 128K 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 3 of 3 shared benchmarks versus Nemotron Nano 9B v2'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 Nemotron Nano 9B v2 are production API models. For cost-sensitive production traffic, Nemotron Nano 9B v2 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 Nemotron Nano 9B v2 through OpenRouter 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 OpenRouter API pricing, quoted per million tokens. Official rate sheets: https://thinkingmachines.ai and https://openrouter.ai/api/v1/models. 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 Nemotron Nano 9B v2 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 Nemotron Nano 9B v2 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 Nemotron Nano 9B v2 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. Nemotron Nano 9B v2 costs $0.00/M input and $0.00/M output via OpenRouter.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
The index
280 models across 33 providers. Search or jump to a lab — every model page stays linked here.
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