Qwen3-Next-80B-A3B Instruct
An 80B MoE with 3B active across 512 experts, using a hybrid of Gated DeltaNet and standard attention.
Key Specifications
- Context window
- 262K tokens
- Max output
- 66K tokens
- Parameters
- 80B, 3B active
- Inputs
- Text
- Capabilities Show details
- Function calling Connect to external tools, APIs, and systems. Structured output Return responses in structured formats like JSON.
Hosted API pricing
| Provider | Input /1M tokens | Output /1M tokens | Cost at 10M in + 2M out | |
|---|---|---|---|---|
|
|
$0.15 | $1.20 | $3.90 | View |
|
|
$0.15 | $1.50 | $4.50 | View |
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-Next-80B-A3B Instruct needs about 48 GB of GPU memory at 4-bit with 32K context. The cheapest rental that fits is 4× RTX 4060 Ti at about $317 a month.
That costs the same as roughly 975M 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-bitINT4 / FP4 |
48 GB
|
$317
|
975M tokens /mo
|
|
| 8-bitFP8 / INT8 |
85 GB
|
$346
|
1B tokens /mo
|
|
| 16-bitFP16 / BF16 |
165 GB
|
$979
|
3B 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. How we estimate costs.
Similarly priced models
The models nearest Qwen3-Next-80B-A3B Instruct by blended rate, each at its own cheapest provider.
| Model | Blended /1M | Input /1M | Output /1M | Context | Cutoff | vs Qwen3-Next-80B-A3B Instruct |
|---|---|---|---|---|---|---|
|
|
$0.30 | $0.20 | $0.80 | 131K | Jan 2026 | −8% |
|
|
$0.30 | $0.30 | $0.30 | 33K | −8% | |
|
|
$0.30 | $0.20 | $0.80 | 33K | −8% | |
|
|
$0.3133 | $0.17 | $1.03 | 262K | −4% | |
|
|
$0.3167 | $0.20 | $0.90 | 1M | −3% | |
|
|
$0.325 | $0.15 | $1.20 | 262K | ||
|
|
$0.325 | $0.15 | $1.20 | 262K | 0% | |
|
|
$0.3333 | $0.25 | $0.75 | 16K | +3% | |
|
|
$0.3333 | $0.25 | $0.75 | 33K | +3% | |
|
|
$0.3417 | $0.25 | $0.80 | 131K | +5% | |
|
|
$0.35 | $0.30 | $0.60 | 262K | +8% |
Prices are 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.
Frequently Asked Questions
What is Qwen3-Next-80B-A3B Instruct good for?
Long-context instruction following at low active compute: an 80B mixture of experts with 3B active across 512 experts. Apache 2.0 weights, on a single high-memory GPU.
When is Qwen3-Next-80B-A3B Instruct not a good fit?
Tasks that need a reasoning trace: this is instruct mode only, and the Thinking sibling covers that. No image or video input.
What is the cheapest way to run Qwen3-Next-80B-A3B Instruct?
Hosted, unless you push serious volume. Alibaba Cloud charges $0.15 in / $1.20 out per 1M tokens. The cheapest rental that fits is 4x RTX 4060 Ti at $317 a month, which costs the same as about 975M tokens a month on that API.
Can I self-host Qwen3-Next-80B-A3B Instruct?
Yes. The weights are Apache 2.0 licensed. At 4-bit it needs about 48 GB of GPU memory, which starts at roughly $317 a month on the cheapest rental that fits.
More from Alibaba Cloud
| Model | Context | Input /1M | Output /1M |
|---|---|---|---|
|
|
262K | $0.15 | $1.20 |
|
|
33K | $0.25 | $0.75 |
|
|
16K | $0.25 | $0.75 |
|
|
262K | $0.17 | $1.03 |
|
|
262K | $0.30 | $0.60 |
|
|
33K | $0.30 | $0.30 |
|
|
33K | $0.20 | $0.80 |
|
|
262K | $0.20 | $0.70 |