Which is cheaper, LongCat-Flash-Thinking or Qwen2-VL-72B-Instruct?
As of August 30, 2026, LongCat-Flash-Thinking is 17% cheaper on blended LLM API pricing. LongCat-Flash-Thinking costs $0.30 per million input tokens and $1.20 per million output tokens ($1.50 blended 1M-in + 1M-out). Qwen2-VL-72B-Instruct costs $0.80 / $1.00 per million tokens ($1.80 blended). Sources: https://anotherwrapper.com/tools/llm-pricing and https://openrouter.ai/qwen/qwen2.5-vl-72b-instruct. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does LongCat-Flash-Thinking vs Qwen2-VL-72B-Instruct cost per million tokens?
LongCat-Flash-Thinking Meituan API pricing is $0.30 input and $1.20 output per million tokens via Meituan. Qwen2-VL-72B-Instruct OpenRouter API pricing is $0.80 input and $1.00 output per million tokens via OpenRouter. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, LongCat-Flash-Thinking or Qwen2-VL-72B-Instruct?
LongCat-Flash-Thinking has a published SWE-bench Verified score of 59.4%. Qwen2-VL-72B-Instruct does not have that eval on this page yet.
What is the context window for LongCat-Flash-Thinking vs Qwen2-VL-72B-Instruct?
LongCat-Flash-Thinking supports a 128K token context window, while Qwen2-VL-72B-Instruct supports 131K tokens. Qwen2-VL-72B-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.
Which model performs better on benchmarks, LongCat-Flash-Thinking or Qwen2-VL-72B-Instruct?
Shared benchmark scores for LongCat-Flash-Thinking and Qwen2-VL-72B-Instruct are still limited. Check the comparison table for the evals each model has published. 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.
Is LongCat-Flash-Thinking or Qwen2-VL-72B-Instruct better for production use?
Both LongCat-Flash-Thinking and Qwen2-VL-72B-Instruct are production API models. For cost-sensitive production traffic, LongCat-Flash-Thinking 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.
Can I switch between LongCat-Flash-Thinking and Qwen2-VL-72B-Instruct in my app?
Yes. Call LongCat-Flash-Thinking through Meituan and Qwen2-VL-72B-Instruct 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.
How accurate is this LongCat-Flash-Thinking vs Qwen2-VL-72B-Instruct pricing data?
List rates are the latest published Meituan API pricing and OpenRouter API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-pricing and https://openrouter.ai/qwen/qwen2.5-vl-72b-instruct. 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.
What is the output token limit for LongCat-Flash-Thinking and Qwen2-VL-72B-Instruct?
LongCat-Flash-Thinking supports up to 128K output tokens per request, while Qwen2-VL-72B-Instruct 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.
Which model has better throughput, LongCat-Flash-Thinking or Qwen2-VL-72B-Instruct?
LongCat-Flash-Thinking has a measured throughput of approximately 100 tokens/second. Throughput data for Qwen2-VL-72B-Instruct 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.
How do I switch the models in this LongCat-Flash-Thinking vs Qwen2-VL-72B-Instruct comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open LongCat-Flash-Thinking or Qwen2-VL-72B-Instruct from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
