Qwen3-VL-235B-A22B Instruct
Flagship Qwen3-VL vision-language model, a 235B MoE with 22B active, built for long video understanding.
- Params
- 235B, 22B active
- Context
- 262K tokens
- Max output
- 66K
- License
- Apache 2.0
Hosted API price
List price via Alibaba Cloud · per 1M tokens
- Input
- $0.40 /1M
- Output
- $1.60 /1M
- Cheapest
- $0.30 / $1.50 via Novita
- Hosted by
-
2 providers
Hosted API pricing
How we price
Order
Providers are listed cheapest input rate first, then by output rate, a tie going to the creator's own listing. A provider that lists the model without a published rate sits at the end.
Prices
Base-tier, on-demand rates in USD per 1M tokens, converted at ECB reference rates where a provider publishes in another currency. Cached-input and batch rates show only where a provider publishes them. "Cheapest" marks the one provider with the lowest input and output pair; a tie wears no badge.
Cost
Input rate times the input tokens plus output rate times the output tokens, at the monthly volume set above the table. Cached-input, batch, long-context and reasoning-token billing are not modelled.
Transparency and funding
- Affiliates: Affiliate links are marked. We may earn a commission if you click them, but commissions never affect the order.
Every provider serving Qwen3-VL-235B-A22B Instruct, cheapest input first. Set your monthly volume to see what each would bill.
| Provider | Input /1M | Output /1M | Cost at 10M in + 2M out | Link |
|---|---|---|---|---|
|
|
$0.30 | $1.50 | $6.00 | Visit website |
|
|
$0.40 | $1.60 | $7.20 | Visit website |
Heads up: Base-tier, on-demand rates per 1M tokens; cached, batch and long-context tiers excluded. A provider may serve a shorter context or a quantized build than the creator's release. Verify before provisioning. More on how we price.
Estimated cost to self-host
Qwen3-VL-235B-A22B Instruct needs about 137 GB of GPU memory at 4-bit with 32K context. The cheapest rental that fits is 8× RTX 3090 at about $1,440 a month.
That costs the same as roughly 2B tokens a month on Alibaba Cloud's API. Self-hosting is more expensive below that volume.
| Precision | Memory | Cheapest fit (32K context) | Cost /mo | Break-even vs API |
|---|---|---|---|---|
| 4-bit INT4 / FP4 | 137 GB |
|
$1,440 | 2B tokens /mo |
| 8-bit FP8 / INT8 | 243 GB |
|
$3,283 | 5B tokens /mo |
| 16-bit FP16 / BF16 | 478 GB |
|
$9,850 | 16B tokens /mo |
Estimates based on median on-demand rates for Nvidia GPUs. Memory is weights plus KV cache for one request, using FP8 KV cache where supported and FP16/BF16 otherwise. Break-even assumes a 5:1 input-to-output ratio. No guarantee of runtime support, usable performance, or that a matching quantized build exists. Pricing methodology.
Similarly priced models
The models nearest Qwen3-VL-235B-A22B Instruct by blended rate, each at its own cheapest provider.
| Model | Blended /1M | Input /1M | Output /1M | Context | Cutoff | vs Qwen3-VL-235B-A22B Instruct |
|---|---|---|---|---|---|---|
|
|
$0.4333 | $0.20 | $1.60 | 262K | −13% | |
|
|
$0.45 | $0.30 | $1.20 | 1M | −10% | |
|
|
$0.45 | $0.30 | $1.20 | 205K | −10% | |
|
|
$0.4583 | $0.25 | $1.50 | 1M | Jan 2025 | −8% |
|
|
$0.4583 | $0.25 | $1.50 | 1M | −8% | |
|
|
$0.50 | $0.30 | $1.50 | 262K | ||
|
|
$0.5075 | $0.435 | $0.87 | 1M | +2% | |
|
|
$0.5233 | $0.45 | $0.89 | 1M | +5% | |
|
|
$0.5417 | $0.25 | $2.00 | 400K | May 2024 | +8% |
|
|
$0.55 | $0.40 | $1.30 | 64K | +10% | |
|
|
$0.5667 | $0.20 | $2.40 | 262K | +13% |
USD per 1M tokens at each model's cheapest listed provider. Blended is the cost of 10M input plus 2M output tokens, spread over the 12M.
Capabilities
What Qwen3-VL-235B-A22B Instruct accepts and can do, as published by Alibaba Cloud.
- Text Accepts and generates natural-language text.
- Image Accepts images as input alongside text.
- Video Accepts video as input.
- Function calling Connect to external tools, APIs, and systems.
- Structured output Return responses in structured formats like JSON.
Common questions
What is Qwen3-VL-235B-A22B Instruct good for?
Hours-long video, multi-image understanding, operating GUIs and reading code from screenshots. Apache 2.0 weights, on a multi-GPU node.
When is Qwen3-VL-235B-A22B Instruct not a good fit?
Audio input, and tasks that need a reasoning trace, which the Thinking sibling covers. Memory follows the full 235B parameters, not the 22B active, so self-hosting takes a multi-GPU node.
What is the cheapest way to run Qwen3-VL-235B-A22B Instruct?
Hosted, unless you push serious volume. Alibaba Cloud charges $0.40 in / $1.60 out per 1M tokens. The cheapest rental that fits is 8x RTX 3090 at $1,440 a month, which costs the same as about 2B tokens a month on that API.
Can I self-host Qwen3-VL-235B-A22B Instruct?
Yes. The weights are Apache 2.0 licensed. At 4-bit it needs about 137 GB of GPU memory, which starts at roughly $1,440 a month on the cheapest rental that fits.
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