Qwen3 VL 235B A22B Thinkingvs
Gemini 2.5 Flash Preview 09-2025
Compare performance metrics, pricing, and capabilities of these AI models.
Key Differences
Context Length
Lower
Qwen3 VL 235B A22B Thinking: 66K (disadvantage)
Gemini 2.5 Flash Preview 09-2025: 1.0M (advantage)
Cost Efficiency
Higher Cost
Prompt: $0.50M vs $0.30M
Completion: $3.50M vs $2.50M
Capabilities
Qwen3 VL 235B A22B Thinking
Modality: text+image->text
Inputs: text, image
Gemini 2.5 Flash Preview 09-2025
Modality: text+image->text
Inputs: image, file, text
Q
Qwen3 VL 235B A22B Thinking
qwen/qwen3-vl-235b-a22b-thinking
Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking ...
Context Length66K
Prompt Price$0.50M
ReleasedSeptember 23, 2025
Supports:
text+image->textG
Gemini 2.5 Flash Preview 09-2025
google/gemini-2.5-flash-preview-09-2025
Gemini 2.5 Flash Preview September 2025 Checkpoint is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding,...
Context Length1.0M
Prompt Price$0.30M
ReleasedSeptember 25, 2025
Supports:
text+image->textDetailed Comparison
| Feature | | |
|---|---|---|
| Context Length | 66K | 1.0M |
| Prompt Price | $0.50M | $0.30M |
| Completion Price | $3.50M | $2.50M |
| Modality | text+image->text | text+image->text |
| Release Date | September 23, 2025 | September 25, 2025 |
Analysis & Recommendations
Quick Summary
This comparison reveals key trade-offs between Qwen3 VL 235B A22B Thinking and Gemini 2.5 Flash Preview 09-2025. Gemini 2.5 Flash Preview 09-2025 offers a larger context window of 1.0M compared to Qwen3 VL 235B A22B Thinking's 66K, though Qwen3 VL 235B A22B Thinking comes at a higher cost.
Qwen3 VL 235B A22B Thinking Strengths
- •Competitive context size (66K)
- •Premium pricing for high-quality output
- •Multimodal capabilities for image analysis
- •Proven and stable model
Gemini 2.5 Flash Preview 09-2025 Strengths
- •Larger context window (1.0M) for processing longer documents
- •More cost-effective per token
- •Multimodal capabilities for image analysis
- •Latest generation model
When to Use Each Model
Choose Qwen3 VL 235B A22B Thinking when:
- • You need competitive context capability for complex tasks
- • Cost efficiency is not the primary concern in your use case
- • Working with images and text that benefit from deep analysis
Choose Gemini 2.5 Flash Preview 09-2025 when:
- • You need the larger context window for long-form content
- • Cost efficiency is important for your budget
- • Working with images and text that require vision capabilities
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