As of August 20, 2026, Qwen3-Coder is 96% cheaper per million tokens than Grok 4.5. Grok 4.5 is $2.00 / $6.00 per million input/output tokens versus Qwen3-Coder at $0.18 / $0.18. 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 4.5
xAI
Input
$2.00
Output
$6.00
Qwen3-Coder
Qwen
Input
$0.18
Output
$0.18
Token pricing, specs, and benchmarks side by side
Grok 4.5Qwen3-CoderVerdict
Both models are closely matched on benchmarks. Qwen3-Coder has the pricing advantage, making it the better value unless Grok 4.5's specific capabilities are critical to your workflow.
As of August 20, 2026, Qwen3-Coder is 96% cheaper on blended LLM API pricing. Qwen3-Coder costs $0.18 per million input tokens and $0.18 per million output tokens ($0.36 blended 1M-in + 1M-out). Grok 4.5 costs $2.00 / $6.00 per million tokens ($8.00 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 4.5 xAI API pricing is $2.00 input and $6.00 output per million tokens via xAI. Qwen3-Coder Qwen API pricing is $0.18 input and $0.18 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Grok 4.5 has a published SWE-bench Verified score of 86.6%. Qwen3-Coder does not have that eval on this page yet.
Grok 4.5 supports a 500K token context window, while Qwen3-Coder supports 256K tokens. Grok 4.5 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.
Shared benchmark scores for Grok 4.5 and Qwen3-Coder 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.
Both Grok 4.5 and Qwen3-Coder are production API models. For cost-sensitive production traffic, Qwen3-Coder 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 4.5 through xAI and Qwen3-Coder 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 4.5 supports up to an unspecified number of output tokens per request, while Qwen3-Coder 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.
Grok 4.5 has a measured throughput of approximately 80 tokens/second. Throughput data for Qwen3-Coder 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 Grok 4.5 or Qwen3-Coder 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 4.5 costs $2.00/M input and $6.00/M output. Qwen3-Coder costs $0.18/M input and $0.18/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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