As of August 20, 2026, QwQ-32B-Preview is 96% cheaper per million tokens than Grok-4. Grok-4 is $3.00 / $15.00 per million input/output tokens versus QwQ-32B-Preview at $0.15 / $0.60. Sources: https://docs.x.ai/docs/models and https://bailian.console.aliyun.com/
Sources: xAI API pricing (https://docs.x.ai/docs/models); Qwen pricing (https://bailian.console.aliyun.com/)
Grok-4
xAI
Input
$3.00
Output
$15.00
QwQ-32B-Preview
Qwen
Input
$0.15
Output
$0.60
Token pricing, specs, and benchmarks side by side
Grok-4QwQ-32B-PreviewVerdict
QwQ-32B-Preview offers significantly lower pricing, while Grok-4 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, QwQ-32B-Preview is 96% cheaper on blended LLM API pricing. QwQ-32B-Preview costs $0.15 per million input tokens and $0.60 per million output tokens ($0.75 blended 1M-in + 1M-out). Grok-4 costs $3.00 / $15.00 per million tokens ($18.00 blended). Sources: https://docs.x.ai/docs/models and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
Grok-4 xAI API pricing is $3.00 input and $15.00 output per million tokens via xAI. QwQ-32B-Preview Qwen API pricing is $0.15 input and $0.60 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Grok-4 has a published SWE Bench score of 75%. QwQ-32B-Preview does not have that eval on this page yet.
Grok-4 supports a 256K token context window, while QwQ-32B-Preview supports 33K tokens. Grok-4 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.
Grok-4 leads on 3 of 3 shared benchmarks versus QwQ-32B-Preview'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 Grok-4 and QwQ-32B-Preview are production API models. For cost-sensitive production traffic, QwQ-32B-Preview 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 Grok-4 through xAI and QwQ-32B-Preview 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 xAI API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://docs.x.ai/docs/models 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.
Grok-4 supports up to 8K output tokens per request, while QwQ-32B-Preview supports up to 33K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Grok-4 runs at approximately 100 tokens/second while QwQ-32B-Preview runs at 76.04 tokens/second. Grok-4 is faster in raw throughput. 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 Grok-4 or QwQ-32B-Preview 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. Grok-4 costs $3.00/M input and $15.00/M output. QwQ-32B-Preview costs $0.15/M input and $0.60/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
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