As of August 20, 2026, Qwen3 VL 32B Instruct is 89% cheaper per million tokens than Sakana Namazu. Qwen3 VL 32B Instruct is $0.10 / $0.42 per million input/output tokens versus Sakana Namazu at $0.95 / $4.00. Sources: https://openrouter.ai/api/v1/models and https://sakana.ai
Sources: OpenRouter pricing (https://openrouter.ai/api/v1/models); Sakana AI pricing (https://sakana.ai)
Qwen3 VL 32B Instruct
Qwen
Input
$0.10
Output
$0.42
Sakana Namazu
Sakana AI
Input
$0.95
Output
$4.00
Token pricing, specs, and benchmarks side by side
Qwen3 VL 32B InstructSakana NamazuVerdict
Qwen3 VL 32B Instruct 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 VL 32B Instruct is 89% cheaper on blended LLM API pricing. Qwen3 VL 32B Instruct costs $0.10 per million input tokens and $0.42 per million output tokens ($0.52 blended 1M-in + 1M-out). Sakana Namazu costs $0.95 / $4.00 per million tokens ($4.95 blended). Sources: https://openrouter.ai/api/v1/models and https://sakana.ai. The cheapest LLM for your app still depends on how many output tokens you generate.
Qwen3 VL 32B Instruct OpenRouter API pricing is $0.10 input and $0.42 output per million tokens via OpenRouter. 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.
Neither Qwen3 VL 32B Instruct nor Sakana Namazu has a published SWE-bench or LiveCodeBench score on this page yet. Use the comparison table for the evals that do exist.
Qwen3 VL 32B Instruct supports a 262K token context window, while Sakana Namazu supports 256K tokens. Qwen3 VL 32B Instruct 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 VL 32B Instruct'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 VL 32B Instruct and Sakana Namazu are production API models. For cost-sensitive production traffic, Qwen3 VL 32B Instruct 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 VL 32B Instruct through OpenRouter 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 OpenRouter API pricing and Sakana AI API pricing, quoted per million tokens. Official rate sheets: https://openrouter.ai/api/v1/models 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 VL 32B Instruct supports up to an unspecified number of 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.
Neither Qwen3 VL 32B Instruct nor Sakana Namazu 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 Qwen3 VL 32B Instruct 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 VL 32B Instruct costs $0.10/M input and $0.42/M output via OpenRouter. 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.
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