As of August 20, 2026, Qwen3.5-27B is 51% cheaper per million tokens than Muse Spark 1.1. Muse Spark 1.1 is $1.25 / $4.25 per million input/output tokens versus Qwen3.5-27B at $0.30 / $2.40. Sources: https://llama.meta.com/ and https://bailian.console.aliyun.com/
Sources: Meta pricing (https://llama.meta.com/); Qwen pricing (https://bailian.console.aliyun.com/)
Muse Spark 1.1
Meta
Input
$1.25
Output
$4.25
Qwen3.5-27B
Qwen
Input
$0.30
Output
$2.40
Token pricing, specs, and benchmarks side by side
Muse Spark 1.1Qwen3.5-27BVerdict
Qwen3.5-27B offers significantly lower pricing, while Muse Spark 1.1 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, Qwen3.5-27B is 51% cheaper on blended LLM API pricing. Qwen3.5-27B costs $0.30 per million input tokens and $2.40 per million output tokens ($2.70 blended 1M-in + 1M-out). Muse Spark 1.1 costs $1.25 / $4.25 per million tokens ($5.50 blended). Sources: https://llama.meta.com/ and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
Muse Spark 1.1 Meta API pricing is $1.25 input and $4.25 output per million tokens via Meta. Qwen3.5-27B Qwen API pricing is $0.30 input and $2.40 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Muse Spark 1.1 leads on SWE-bench Verified: Muse Spark 1.1 at 82% vs Qwen3.5-27B at 72.4%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
Muse Spark 1.1 supports a 1M token context window, while Qwen3.5-27B supports 262K tokens. Muse Spark 1.1 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.
Muse Spark 1.1 leads on 8 of 8 shared benchmarks versus Qwen3.5-27B'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 Muse Spark 1.1 and Qwen3.5-27B are production API models. For cost-sensitive production traffic, Qwen3.5-27B 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 Muse Spark 1.1 through Meta and Qwen3.5-27B 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 Meta API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://llama.meta.com/ 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.
Muse Spark 1.1 supports up to 131K output tokens per request, while Qwen3.5-27B supports up to 66K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Muse Spark 1.1 runs at approximately 6.152425085592334 tokens/second while Qwen3.5-27B runs at 6.735706278284246 tokens/second. Qwen3.5-27B 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 Muse Spark 1.1 or Qwen3.5-27B 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. Muse Spark 1.1 costs $1.25/M input and $4.25/M output. Qwen3.5-27B costs $0.30/M input and $2.40/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
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