As of August 30, 2026, Qwen2.5 7B Instruct is 67% cheaper per million tokens than QwQ-32B. Qwen2.5 7B Instruct is $0.30 / $0.30 per million input/output tokens versus QwQ-32B at $0.90 / $0.90. Sources: https://bailian.console.aliyun.com/ and https://fireworks.ai/pricing
Sources: Qwen pricing (https://bailian.console.aliyun.com/); Fireworks pricing (https://fireworks.ai/pricing)
Qwen2.5 7B Instruct
Qwen
Input
$0.30
Output
$0.30
QwQ-32B
Qwen
Input
$0.90
Output
$0.90
Token pricing, specs, and benchmarks side by side
Each bar is share of the current leader on that eval. Click a row to open the board.
GPQA. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.
Qwen2.5 7B InstructQwQ-32BVerdict
Qwen2.5 7B Instruct offers significantly lower pricing, while QwQ-32B leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.
As of August 30, 2026, Qwen2.5 7B Instruct is 67% cheaper on blended LLM API pricing. Qwen2.5 7B Instruct costs $0.30 per million input tokens and $0.30 per million output tokens ($0.60 blended 1M-in + 1M-out). QwQ-32B costs $0.90 / $0.90 per million tokens ($1.80 blended). Sources: https://bailian.console.aliyun.com/ and https://fireworks.ai/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
Qwen2.5 7B Instruct Qwen API pricing is $0.30 input and $0.30 output per million tokens via Qwen. QwQ-32B Fireworks API pricing is $0.90 input and $0.90 output per million tokens via Fireworks. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
QwQ-32B leads on LiveCodeBench: Qwen2.5 7B Instruct at 28.7% vs QwQ-32B at 63.4%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
Qwen2.5 7B Instruct supports a 131K token context window, while QwQ-32B supports 131K tokens. Both models have the same context window size. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
QwQ-32B leads on 4 of 4 shared benchmarks versus Qwen2.5 7B 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 Qwen2.5 7B Instruct and QwQ-32B are production API models. For cost-sensitive production traffic, Qwen2.5 7B 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 Qwen2.5 7B Instruct through Qwen and QwQ-32B through Fireworks 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 Fireworks API pricing, quoted per million tokens. Official rate sheets: https://bailian.console.aliyun.com/ and https://fireworks.ai/pricing. 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.
Qwen2.5 7B Instruct supports up to 8K output tokens per request, while QwQ-32B 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.
Qwen2.5 7B Instruct has a measured throughput of approximately 138 tokens/second. Throughput data for QwQ-32B 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 Qwen2.5 7B Instruct or QwQ-32B 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. Qwen2.5 7B Instruct costs $0.30/M input and $0.30/M output. QwQ-32B costs $0.90/M input and $0.90/M output via Fireworks.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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