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Muse Spark 1.3 vs Qwen3.8 Max Preview

Compare Muse Spark 1.3 from Meta and Qwen3.8 Max Preview from Qwen on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

MetaMuse Spark 1.3QwenQwen3.8 Max Preview
+ Add model · 2/4
Meta logo
Muse Spark 1.3
Meta · text, image, audio, video → text

Muse Spark 1.3 is Meta’s multimodal reasoning model, designed for long-running agentic, multi-agent, and complex coding workflows. It can maintain context and task constraints across extended workflows, reconcile conflicting information, and request clarification or confirmation when needed. Compared with Muse Spark 1.2, Muse Spark 1.3 improves efficiency across long-horizon agentic and coding tasks, with fewer unnecessary turns, tool calls, and tokens, while producing more concise outputs.

Input$1.375 /M
Output$4.675 /M
Cache read$0.165 /M
Details
Qwen logo
Qwen3.8 Max Preview
Qwen · text, image → text

Qwen 3.8 Max Preview(Qwen3.8-Max-Preview) is the latest-generation foundation model in the Qwen family, packing 2.4T parameters and still evolving. Compared with the previous flagship Qwen 3.7 Max, it delivers major gains in core capabilities like Coding and Cowork (professional productivity), with world-leading performance on complex, long-horizon tasks such as full-stack development, data analysis, and Office workflows. Launch offer: Credits are consumed at just 20% of the standard rate, effectively 5× your usage. Limited time only.

Input$0.338 /M
Output$1.014 /M
Cache read$0.0338 /M
Details

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

Muse Spark 1.3
Qwen3.8 Max Preview
Input /M
$1.375
$0.338
Output /M
$4.675
$1.014
Cache read /M
$0.165
$0.0338
Context length
1,000,000
983,616
Max output
1,000,000
131,072
Time to First Token
2.7 s
2.4 s
Throughput
90.1 tok/s
48.1 tok/s
Modalities
textimageaudiovideo
textimage
Supported Parameters
thinkingtools
toolsfunction callingstructured outputsweblong contextthinking
API Formats
Released
September 3, 2026
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Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

muse-spark-1.3qwen3.8-max-preview

Tokens / day

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Requests / day

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Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

muse-spark-1.3qwen3.8-max-preview

Throughput (tok/s)

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TTFT (s)

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Uptime (%)

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Cost calculator

Estimate your monthly bill for the same workload on each model.

Qwen3.8 Max Preview
$35.49 /mo
Muse Spark 1.3
$153 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: Muse Spark 1.3, Qwen3.8 Max Preview?

Qwen3.8 Max Preview: $1.014/M output tokens; Muse Spark 1.3: $4.675/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

Qwen3.8 Max Preview: 2.4s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

Muse Spark 1.3 accepts 1,000,000 and Qwen3.8 Max Preview accepts 983,616 input tokens. Maximum output per request is 1,000,000 tokens on Muse Spark 1.3 and 131,072 tokens on Qwen3.8 Max Preview.

Which one generates tokens faster?

Muse Spark 1.3 at 90.1 tok/s and Qwen3.8 Max Preview at 48.1 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

Muse Spark 1.3 accepts text, image, audio and video input and supports thinking and tool calling; Qwen3.8 Max Preview accepts text and image input and supports tool calling, function calling, structured outputs, web search, long context and thinking.

Can I call Muse Spark 1.3 and Qwen3.8 Max Preview with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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