Whisper Large V3 vs Qwen 2.5 VL 72B

Compare Whisper Large V3 and Qwen 2.5 VL 72B: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

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

All OpenAI models All Alibaba models What is an LLM API? Python Quickstart What is inference?
Feature Whisper Large V3 Qwen 2.5 VL 72B
CategorySpeechVision
Parameters1.55B72B
Context Window30s128K
Input Price$0.01/min/1M tokens$0.05/1M tokens
Output PriceN/A/1M tokens$0.10/1M tokens
Latency~200ms~400ms

Choose Whisper Large V3 when:

  • ✓ Voice astrology apps
  • ✓ Temple voice assistants
  • ✓ Transcription
Key Strengths:

14+ Indian languages, Robust to accents, Real-time capable

Choose Qwen 2.5 VL 72B when:

  • ✓ Document analysis
  • ✓ Chart reading
  • ✓ Visual Q&A
Key Strengths:

Vision + language, Strong Asian text OCR, Good reasoning

Verdict: Whisper Large V3 vs Qwen 2.5 VL 72B

For cost efficiency, Whisper Large V3 wins at $0.01/min/1M input tokens. For speed, Whisper Large V3 is faster at ~200ms. Whisper Large V3 excels at Voice astrology apps while Qwen 2.5 VL 72B is better for 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

Whisper Large V3 costs $0.01/min/1M input tokens and N/A/1M output tokens. Qwen 2.5 VL 72B costs $0.05 input and $0.10 output. Whisper Large V3 is 5.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Whisper Large V3 has a 30s context window with ~200ms latency. Qwen 2.5 VL 72B offers 128K context at ~400ms. Qwen 2.5 VL 72B has the larger context window.

Best For

Whisper Large V3 (Speech) is optimized for: Voice astrology apps, Temple voice assistants, Transcription. Qwen 2.5 VL 72B (Vision) works best for: Document analysis, Chart reading, Visual Q&A.

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 Whisper Large V3
response_a = client.chat.completions.create(
    model="whisper-large-v3",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Qwen 2.5 VL 72B
response_b = client.chat.completions.create(
    model="qwen-2-5-vl-72b",
    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, Whisper Large V3 or Qwen 2.5 VL 72B?

Whisper Large V3 (Speech, 1.55B) offers 14+ Indian languages. Qwen 2.5 VL 72B (Vision, 72B) offers Vision + language. Choose Whisper Large V3 for Voice astrology apps or Qwen 2.5 VL 72B for Document analysis.

How much does Whisper Large V3 cost vs Qwen 2.5 VL 72B?

Whisper Large V3: $0.01/min/1M input, N/A/1M output. Qwen 2.5 VL 72B: $0.05/1M input, $0.10/1M 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 Whisper Large V3 and Qwen 2.5 VL 72B by changing the model parameter. No code changes needed.

Related Comparisons

Whisper Large V3 vs Vedika Vision Whisper Large V3 vs Llama 3.2 90B Vision Whisper Large V3 vs Llama 3.2 11B Vision Whisper Large V3 vs Qwen 2.5 VL 7B Whisper Large V3 vs Pixtral Large Whisper Large V3 vs Pixtral 12B

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