Qwen3 VL 235B A22B Instruct
ActiveQwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
Overview
Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...
History
Qwen3 VL 235B A22B Instruct became available via the Alibaba API on 2025-09-23.
Training & availability
Training data has a knowledge cutoff of 2025-03-31 — information about events after that date is unlikely to appear in the model's responses. Alibaba has not released the underlying model weights — access is via their hosted API only.
Capabilities
-
Context window: 262K tokens.
-
Input modalities: text, image.
Recommended for: vision, long-context, cheap.
Limitations
- The knowledge cutoff is 12 months old — this model will not know about recent events, releases, or API changes.
Pricing
- Input: $0.2000 per 1M tokens
- Output: $0.8800 per 1M tokens
Use the cost calculator above to estimate monthly spend for your workload.
Quick start
Minimal example using the OpenRouter API. Copy, paste, replace the key.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="sk-or-...",
)
resp = client.chat.completions.create(
model="alibaba/qwen3-vl-235b-a22b-instruct",
messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)Cost calculator
Estimate your monthly bill. Presets are typical workload sizes.
Providers & performance
7 providersMulti-provider inference routes for this model — sorted by throughput. Latency is time-to-first-token; throughput is output tokens per second. Data from OpenRouter, measured over the last 30 minutes.
| Provider | Throughput | Latency (TTFT) | Input $ / 1M | Output $ / 1M | Context | Quant | Supports |
|---|---|---|---|---|---|---|---|
| Alibaba | 36tok/s | 737ms | $0.26 | $1.04 | 131K | — | tools · json |
| Venice | 14tok/s | 2.04s | $0.25 | $1.5 | 256K | fp8 | tools · json |
| DeepInfra | 9tok/s |
Popularity
Signals from open-source communities — not a quality measure, but useful for gauging adoption among developers.
Integrations & tooling support
- Tool calling
- Not supported
- Structured outputs
- Not supported
Price vs quality
Priced low — good for high-volume tasks. Quality tier pending more benchmark coverage.
- Quality percentile
- —
- Effective price
- $0.71/1M
- Pricing breakdown
- $0.2/1M in
$0.88/1M out
Community ratings
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Comments
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