As of August 20, 2026, Inkling-Small is 58% cheaper per million tokens than Qwen3.5-122B-A10B. Inkling-Small is $0.30 / $1.20 per million input/output tokens versus Qwen3.5-122B-A10B at $0.40 / $3.20. Sources: https://thinkingmachines.ai and https://bailian.console.aliyun.com/
Sources: Thinking Machines Lab pricing (https://thinkingmachines.ai); Qwen pricing (https://bailian.console.aliyun.com/)
Inkling-Small
Thinking Machines
Input
$0.30
Output
$1.20
Qwen3.5-122B-A10B
Qwen
Input
$0.40
Output
$3.20
Token pricing, specs, and benchmarks side by side
Inkling-SmallQwen3.5-122B-A10BVerdict
Inkling-Small 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, Inkling-Small is 58% cheaper on blended LLM API pricing. Inkling-Small costs $0.30 per million input tokens and $1.20 per million output tokens ($1.50 blended 1M-in + 1M-out). Qwen3.5-122B-A10B costs $0.40 / $3.20 per million tokens ($3.60 blended). Sources: https://thinkingmachines.ai and https://bailian.console.aliyun.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. Qwen3.5-122B-A10B Qwen API pricing is $0.40 input and $3.20 output per million tokens via Qwen. 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 Qwen3.5-122B-A10B at 72%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
Inkling-Small supports a 256K token context window, while Qwen3.5-122B-A10B supports 262K tokens. Qwen3.5-122B-A10B 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 5 of 8 shared benchmarks versus Qwen3.5-122B-A10B's 3 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 Qwen3.5-122B-A10B are production API models. For cost-sensitive production traffic, Inkling-Small 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 Qwen3.5-122B-A10B through Qwen 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 Qwen API pricing, quoted per million tokens. Official rate sheets: https://thinkingmachines.ai and https://bailian.console.aliyun.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 Qwen3.5-122B-A10B supports up to 64K 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 Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B 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. Qwen3.5-122B-A10B costs $0.40/M input and $3.20/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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