As of August 20, 2026, Qwen3.5-27B is 45% cheaper per million tokens than Sakana Namazu. Qwen3.5-27B is $0.30 / $2.40 per million input/output tokens versus Sakana Namazu at $0.95 / $4.00. Sources: https://bailian.console.aliyun.com/ and https://sakana.ai
Sources: Qwen pricing (https://bailian.console.aliyun.com/); Sakana AI pricing (https://sakana.ai)
Qwen3.5-27B
Qwen
Input
$0.30
Output
$2.40
Sakana Namazu
Sakana AI
Input
$0.95
Output
$4.00
Token pricing, specs, and benchmarks side by side
Qwen3.5-27BSakana NamazuVerdict
Qwen3.5-27B offers significantly lower pricing, while Sakana Namazu 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, Qwen3.5-27B is 45% cheaper on blended LLM API pricing. Qwen3.5-27B costs $0.30 per million input tokens and $2.40 per million output tokens ($2.70 blended 1M-in + 1M-out). Sakana Namazu costs $0.95 / $4.00 per million tokens ($4.95 blended). Sources: https://bailian.console.aliyun.com/ and https://sakana.ai. The cheapest LLM for your app still depends on how many output tokens you generate.
Qwen3.5-27B Qwen API pricing is $0.30 input and $2.40 output per million tokens via Qwen. Sakana Namazu Sakana AI API pricing is $0.95 input and $4.00 output per million tokens via Sakana AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Qwen3.5-27B has a published SWE-bench Verified score of 72.4%. Sakana Namazu does not have that eval on this page yet.
Qwen3.5-27B supports a 262K token context window, while Sakana Namazu supports 256K tokens. Qwen3.5-27B 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.
Sakana Namazu leads on 2 of 2 shared benchmarks versus Qwen3.5-27B'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 Qwen3.5-27B and Sakana Namazu are production API models. For cost-sensitive production traffic, Qwen3.5-27B 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 Qwen3.5-27B through Qwen and Sakana Namazu through Sakana 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 Qwen API pricing and Sakana AI API pricing, quoted per million tokens. Official rate sheets: https://bailian.console.aliyun.com/ and https://sakana.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.
Qwen3.5-27B supports up to 66K output tokens per request, while Sakana Namazu 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.
Qwen3.5-27B has a measured throughput of approximately 6.735706278284246 tokens/second. Throughput data for Sakana Namazu 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 Qwen3.5-27B or Sakana Namazu 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. Qwen3.5-27B costs $0.30/M input and $2.40/M output. Sakana Namazu costs $0.95/M input and $4.00/M output.
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.
Next step
Auth, billing, and the API layer are already decided. Fork 8 finished AI apps, or have us build the first version with you.
