Qwen 2.5 VL 7B vs Yi Large

Compare Qwen 2.5 VL 7B and Yi Large: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

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Feature Qwen 2.5 VL 7B Yi Large
CategoryVisionOpen Source
Parameters7B300B
Context Window128K200K
Input Price$0.01/1M tokens$0.06/1M tokens
Output Price$0.02/1M tokens$0.12/1M tokens
Latency~150ms~450ms

Choose Qwen 2.5 VL 7B when:

  • ✓ Budget image analysis
  • ✓ Simple OCR
  • ✓ Quick visual Q&A
Key Strengths:

Low cost vision, Asian language OCR, Fast

Choose Yi Large when:

  • ✓ Long document analysis
  • ✓ Research
  • ✓ Complex tasks
Key Strengths:

200K context, Strong analysis, Good reasoning

Verdict: Qwen 2.5 VL 7B vs Yi Large

For cost efficiency, Qwen 2.5 VL 7B wins at $0.01/1M input tokens. For speed, Qwen 2.5 VL 7B is faster at ~150ms. Qwen 2.5 VL 7B excels at Budget image analysis while Yi Large is better for Long document analysis. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Qwen 2.5 VL 7B costs $0.01/1M input tokens and $0.02/1M output tokens. Yi Large costs $0.06 input and $0.12 output. Qwen 2.5 VL 7B is 6.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Qwen 2.5 VL 7B has a 128K context window with ~150ms latency. Yi Large offers 200K context at ~450ms. Yi Large has the larger context window.

Best For

Qwen 2.5 VL 7B (Vision) is optimized for: Budget image analysis, Simple OCR, Quick visual Q&A. Yi Large (Open Source) works best for: Long document analysis, Research, Complex tasks.

Try Both on XALEN

Both models are available through XALEN's OpenAI-compatible API. Switch between them by changing the model parameter:

from xalen import XALEN

client = XALEN(api_key="xln_test_YOUR_KEY")

# Use Qwen 2.5 VL 7B
response_a = client.chat.completions.create(
    model="qwen-2-5-vl-7b",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Yi Large
response_b = client.chat.completions.create(
    model="yi-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Qwen 2.5 VL 7B or Yi Large?

Qwen 2.5 VL 7B (Vision, 7B) offers Low cost vision. Yi Large (Open Source, 300B) offers 200K context. Choose Qwen 2.5 VL 7B for Budget image analysis or Yi Large for Long document analysis.

How much does Qwen 2.5 VL 7B cost vs Yi Large?

Qwen 2.5 VL 7B: $0.01/1M input, $0.02/1M output. Yi Large: $0.06/1M input, $0.12/1M output. Both available on XALEN with batch processing at 50% discount.

Can I use both models on XALEN?

Yes. XALEN provides 200+ models through a single OpenAI-compatible API. Switch between Qwen 2.5 VL 7B and Yi Large by changing the model parameter. No code changes needed.

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Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.