Qwen3 VL 32B Instruct
by Alibaba (Qwen) · qwen/qwen3-vl-32b-instruct · #86 cheapest of 422 paid models
Prices updated Sep 19, 2026, 6:20 PM UTC · refreshed hourly
Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text...
Compare vs:Claude Sonnet 5Claude Opus 4.6Claude Haiku 4.5GPT-5.6 Sol
Pricing
Input
$0.104
per 1M tokens
Output
$0.416
per 1M tokens
Blended (3:1)
$0.182
3 input : 1 output
Cache read
—
per 1M cached tokens
Cache write
—
per 1M tokens
Cache & batch economics
Effective prices for Qwen3 VL 32B Instruct (no cache-read rate published — hits billed as normal input).
| Cache hit rate | Effective blended $/1M | Example request* | vs no cache |
|---|---|---|---|
| 0% | $0.182 | $0.011 | — |
| 50% | $0.182 | $0.011 | −0% |
| 90% | $0.182 | $0.011 | −0% |
*Example: 100K sticky context + 2K new input + 1K output. Batch discount is an approximate 50% off list rates (available for OpenAI / Anthropic / Google — not flagged for this creator). Confirm on the vendor’s pricing page.
What a request costs
| Workload | Input tokens | Output tokens | Cost / request | Cost / 1K requests |
|---|---|---|---|---|
| Short chat message | 500 | 300 | $0.000177 | $0.1768 |
| Document summary | 8,000 | 1,000 | $0.001248 | $1.25 |
| Codebase question (RAG) | 30,000 | 2,000 | $0.003952 | $3.95 |
| Long-context analysis | 150,000 | 5,000 | $0.0177 | $17.68 |
Performance
Intelligence Index
8.4
AA composite quality
Coding Index
—
Math Index
68.3
Agentic Index
—
Output speed
0 tok/s
median
Time to first token
0s
median
Time to first answer
0s
after reasoning tokens
Artificial Analysis benchmarks
| Benchmark | Score |
|---|---|
| MMLU-Pro | 79.1% |
| GPQA Diamond | 67.1% |
| Humanity's Last Exam | 6.8% |
| LiveCodeBench | 51.4% |
| AIME 2025 | 68.3% |
| IFBench | 39.2% |
| Terminal-Bench Hard | 8.3% |
| τ²-Bench (Telecom) | 29.2% |
Specs
Context window
131K
tokens
Max output
33K
tokens
Input modalities
text, image
Tokenizer
Qwen