qwen3-max vs gemini-3.8-flash
Side-by-side comparison of qwen3-max and gemini-3.8-flash: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gemini-3.8-flash outperforms qwen3-max on 3 of 3 shared benchmarks.
qwen3-max
Input / 1M
$0.86
Output / 1M
$3.44
Context
262K
Model ID
alibaba/qwen3-max
gemini-3.8-flash
Input / 1M
$1.50$0.75
Output / 1M
$7.50$3.75
Context
1.0M
Model ID
vertex/gemini-3.8-flash
Benchmark comparison
Intelligence Indexreasoning
qwen3-max25.0%
gemini-3.8-flash47.1%
Coding Indexcoding
qwen3-maxN/A
gemini-3.8-flash76.3%
GPQA Diamondreasoning
qwen3-max86.1%
gemini-3.8-flash95.3%
Terminal-Bench Hardagentic
qwen3-max24.2%
gemini-3.8-flashN/A
τ²-Benchagentic
qwen3-max83.6%
gemini-3.8-flashN/A
SciCodecoding
qwen3-maxN/A
gemini-3.8-flash56.6%
Humanity's Last Examreasoning
qwen3-max28.0%
gemini-3.8-flash47.8%
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-max | gemini-3.8-flash | |
|---|---|---|
| Input price / 1M | $0.86 | $1.50$0.75 |
| Output price / 1M | $3.44 | $7.50$3.75 |
| Context window | 262K tokens | 1.0M tokens |
| Max output | 66K tokens | 66K tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | N/A | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | Alibaba Cloud | Google LLC (Vertex AI) |
Questions people ask
Is qwen3-max better than gemini-3.8-flash?
gemini-3.8-flash outperforms qwen3-max on 3 of 3 shared benchmarks. See the benchmark comparison above for specifics: qwen3-max and gemini-3.8-flash have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, qwen3-max or gemini-3.8-flash?
qwen3-max is cheaper. qwen3-max costs $0.86/$3.44 per 1M input/output tokens, while gemini-3.8-flash costs $0.75/$3.75. The prices shown are what you pay: gemini-3.8-flash runs at 50% off its list rate of $1.50 per 1M input and $7.50 per 1M output.
Can I use qwen3-max and gemini-3.8-flash 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-max" and "vertex/gemini-3.8-flash", no other code changes needed.
What are the context windows?
qwen3-max supports up to 262K tokens of context. gemini-3.8-flash 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-max and gemini-3.8-flash with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.