Favicon for qwen

Qwen: Qwen3 VL 235B A22B Instruct

qwen/qwen3-vl-235b-a22b-instruct

Model weights

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 extraction, multilingual OCR). The series emphasizes robust perception (recognition of diverse real-world and synthetic categories), spatial understanding (2D/3D grounding), and long-form visual comprehension, with competitive results on public multimodal benchmarks for both perception and reasoning.

Beyond analysis, Qwen3-VL supports agentic interaction and tool use: it can follow complex instructions over multi-image, multi-turn dialogues; align text to video timelines for precise temporal queries; and operate GUI elements for automation tasks. The models also enable visual coding workflows—turning sketches or mockups into code and assisting with UI debugging—while maintaining strong text-only performance comparable to the flagship Qwen3 language models. This makes Qwen3-VL suitable for production scenarios spanning document AI, multilingual OCR, software/UI assistance, spatial/embodied tasks, and research on vision-language agents.

Modalities
In / out price
$0.20 / $0.88per 1M
Context
262K
Released
Sep 23, 2025
Knowledge cutoff
Mar 2025

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input
$0.1545/M tokens
Output
$1.617/M tokens
Price history
No effective price data for this selection

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput
52tok/s

P50, best across providers

Latency
0.66s

P50, best provider

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)The model was reachable. Request routed to a provider.
100.00%
Availability (3d)The model returned inference from any provider. Errors and empty responses count against it.
99.96%

Availability over the last 3 days

Last 72 hours
Availability 99.96%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
99.93%
Without Routing
96.44%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Qwen: Qwen3 VL 235B A22B Instruct (Artificial Analysis)
SourceBenchmarkScore
Artificial AnalysisQwen3 VL 235B A22B Instruct GPQA Diamond71.2%
Artificial AnalysisQwen3 VL 235B A22B Instruct HLE6.6%
Artificial AnalysisQwen3 VL 235B A22B Instruct IFBench42.7%
Artificial AnalysisQwen3 VL 235B A22B Instruct τ²-Bench Telecom35.1%
Artificial AnalysisQwen3 VL 235B A22B Instruct AA-LCR32.7%
Artificial AnalysisQwen3 VL 235B A22B Instruct CritPt0.0%
Artificial AnalysisQwen3 VL 235B A22B Instruct LiveCodeBench59.4%
Artificial AnalysisQwen3 VL 235B A22B Instruct Terminal-Bench Hard6.8%
Artificial AnalysisQwen3 VL 235B A22B Instruct MMLU-Pro82.3%
Artificial AnalysisQwen3 VL 235B A22B Instruct AIME 202570.7%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) GPQA Diamond61.3%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) HLE4.2%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) IFBench36.6%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) τ²-Bench Telecom27.2%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) AA-LCR0.0%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) CritPt0.0%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) LiveCodeBench34.3%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) Terminal-Bench Hard6.1%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) MMLU-Pro76.2%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) AIME 202523.7%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) AIME32.7%
Artificial AnalysisQwen3 235B A22B (Non-reasoning) MATH-50090.2%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

1.
2.14Btokens
3.
1.01Btokens
4.
895Mtokens
5.
849Mtokens
Rest of OpenRouter
931M
Top 5 Apps
29.2M

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Not currently available through EU in-region routing. In-region routing docs

Frequently asked questions