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qwen3.8-max vs gemini-2.5-pro

Side-by-side comparison of qwen3.8-max and gemini-2.5-pro: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. qwen3.8-max outperforms gemini-2.5-pro on 4 of 4 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
qwen3.8-max46.9%
gemini-2.5-pro19.0%
Coding Indexcoding
qwen3.8-max71.8%
gemini-2.5-pro33.3%
Math Indexmath
qwen3.8-maxN/A
gemini-2.5-pro87.7%
GPQA Diamondreasoning
qwen3.8-max92.7%
gemini-2.5-pro84.4%
AIME 2025math
qwen3.8-maxN/A
gemini-2.5-pro87.7%
LiveCodeBenchcoding
qwen3.8-maxN/A
gemini-2.5-pro80.1%
Terminal-Bench Hardagentic
qwen3.8-maxN/A
gemini-2.5-pro26.5%
τ²-Benchagentic
qwen3.8-maxN/A
gemini-2.5-pro54.1%
SciCodecoding
qwen3.8-max53.2%
gemini-2.5-proN/A
MMLU Proknowledge
qwen3.8-maxN/A
gemini-2.5-pro86.2%
Humanity's Last Examreasoning
qwen3.8-max43.0%
gemini-2.5-pro22.5%

Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.

Pricing & specifications

qwen3.8-maxgemini-2.5-pro
Input price / 1M$2.00$1.25
Output price / 1M$6.00$10.00
Context window1.0M tokens1.0M tokens
Max output131K tokens66K tokens
Vision inputN/AYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer useN/AN/A
ProviderAlibaba CloudGoogle LLC (Gemini API)

Questions people ask

Is qwen3.8-max better than gemini-2.5-pro?
qwen3.8-max outperforms gemini-2.5-pro on 4 of 4 shared benchmarks. See the benchmark comparison above for specifics: qwen3.8-max and gemini-2.5-pro have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, qwen3.8-max or gemini-2.5-pro?
qwen3.8-max is cheaper. qwen3.8-max costs $2.00/$6.00 per 1M input/output tokens, while gemini-2.5-pro costs $1.25/$10.00.
Can I use qwen3.8-max and gemini-2.5-pro through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "alibaba/qwen3.8-max" and "google/gemini-2.5-pro", no other code changes needed.
What are the context windows?
qwen3.8-max supports up to 1.0M tokens of context. gemini-2.5-pro supports up to 1.0M tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.

Switch between qwen3.8-max and gemini-2.5-pro with one line of code

Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.