Models

ERNIE 4.5 vs Qwen3.8 Max Preview

Compare ERNIE 4.5 from Baidu 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.

BaiduERNIE 4.5QwenQwen3.8 Max Preview
Baidu logo
ERNIE 4.5
Baidu · text, image → text

Wenxin Large Model 4.5 is a next-generation native multimodal foundational model independently developed by Baidu. It achieves collaborative optimization through joint modeling of multiple modalities, demonstrating excellent multimodal understanding capabilities; it possesses more advanced language abilities, with comprehensive improvements in comprehension, generation, logic, and memory, as well as significant enhancements in hallucination reduction, logical reasoning, and coding capabilities.ERNIE-4.5-21B-A3B is an aligned open-source model with a MoE structure, having a total of 21 billion parameters and 3 billion activated parameters.

Input$0.07 /M
Output$0.27 /M
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$0.34 /M
Output$1.01 /M

Pricing & Specifications

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

ERNIE 4.5
Qwen3.8 Max Preview
Input /M
$0.07
$0.34
Output /M
$0.27
$1.01
Cache read /M
$0.07
$0.03
Context length
160,000
983,616
Max output
64,000
131,072
Time to First Token
0.9 s
2.4 s
Throughput
98.7 tok/s
48.1 tok/s
Modalities
textimage
textimage
Supported Parameters
toolsfunction callingstructured outputs
toolsfunction callingstructured outputsweblong contextthinking
API Formats
Released
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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.

ernie-4.5qwen3.8-max-preview

Tokens / day

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Requests / day

-

Performance Past 3 Days

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

ernie-4.5qwen3.8-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.

ERNIE 4.5
$8.16 /mo
Qwen3.8 Max Preview
$35.49 /mo

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

FAQ

Which is cheaper: ERNIE 4.5, Qwen3.8 Max Preview?

ERNIE 4.5: $0.27/M output tokens; Qwen3.8 Max Preview: $1.01/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

ERNIE 4.5: 0.9s 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?

ERNIE 4.5 accepts 160,000 and Qwen3.8 Max Preview accepts 983,616 input tokens. Maximum output per request is 64,000 tokens on ERNIE 4.5 and 131,072 tokens on Qwen3.8 Max Preview.

Which one generates tokens faster?

ERNIE 4.5 at 98.7 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?

ERNIE 4.5 accepts text and image input and supports tool calling, function calling and structured outputs; 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 ERNIE 4.5 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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