Qwen 2.5 VL 7B vs Mistral Small 3.1
Compare Qwen 2.5 VL 7B and Mistral Small 3.1: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.
Updated 2026-05-21 · By Abhishek Raj · Our methodology
| Feature | Qwen 2.5 VL 7B | Mistral Small 3.1 |
|---|---|---|
| Category | Vision | Compact |
| Parameters | 7B | 24B |
| Context Window | 128K | 128K |
| Input Price | $0.01/1M tokens | $0.02/1M tokens |
| Output Price | $0.02/1M tokens | $0.04/1M tokens |
| Latency | ~150ms | ~120ms |
Choose Qwen 2.5 VL 7B when:
- ✓ Budget image analysis
- ✓ Simple OCR
- ✓ Quick visual Q&A
Low cost vision, Asian language OCR, Fast
Choose Mistral Small 3.1 when:
- ✓ Lightweight tasks
- ✓ Classification
- ✓ Simple generation
128K context, Low cost, Fast
Verdict: Qwen 2.5 VL 7B vs Mistral Small 3.1
For cost efficiency, Qwen 2.5 VL 7B wins at $0.01/1M input tokens. For speed, Mistral Small 3.1 is faster at ~120ms. Qwen 2.5 VL 7B excels at Budget image analysis while Mistral Small 3.1 is better for Lightweight tasks. 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. Mistral Small 3.1 costs $0.02 input and $0.04 output. Qwen 2.5 VL 7B is 2.0x 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. Mistral Small 3.1 offers 128K context at ~120ms. Both have identical context windows.
Best For
Qwen 2.5 VL 7B (Vision) is optimized for: Budget image analysis, Simple OCR, Quick visual Q&A. Mistral Small 3.1 (Compact) works best for: Lightweight tasks, Classification, Simple generation.
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 Mistral Small 3.1
response_b = client.chat.completions.create(
model="mistral-small-3-1",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Qwen 2.5 VL 7B or Mistral Small 3.1?
Qwen 2.5 VL 7B (Vision, 7B) offers Low cost vision. Mistral Small 3.1 (Compact, 24B) offers 128K context. Choose Qwen 2.5 VL 7B for Budget image analysis or Mistral Small 3.1 for Lightweight tasks.
How much does Qwen 2.5 VL 7B cost vs Mistral Small 3.1?
Qwen 2.5 VL 7B: $0.01/1M input, $0.02/1M output. Mistral Small 3.1: $0.02/1M input, $0.04/1M 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 Mistral Small 3.1 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.