Qwen3-Coder-Next
Code-specialized model on the Qwen3-Next architecture, an 80B MoE with 3B active, trained with reinforcement learning on executable tasks.
- Input
- $0.30 / 1M tokens
- Output
- $1.50 / 1M tokens
Cheapest: $0.08 / $0.98 per 1M tokens via Geodd
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 | |
|---|---|---|---|---|
|
|
$0.08 | $0.98 | $2.76 | View |
|
|
$0.20 | $1.50 | $5.00 | View |
|
|
$0.30 | $1.50 | $6.00 | 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-Coder-Next 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 634M 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
|
634M tokens / mo
|
|
| 8-bitFP8 / INT8 |
85 GB
|
$346
|
691M tokens / mo
|
|
| 16-bitFP16 / BF16 |
165 GB
|
$979
|
2B 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-Coder-Next by blended rate, each at its own cheapest provider.
| Model | Blended / 1M | Input / 1M | Output / 1M | Context | Cutoff | vs Qwen3-Coder-Next |
|---|---|---|---|---|---|---|
|
|
$0.225 | $0.15 | $0.60 | 128K | Jun 2024 | −2% |
|
|
$0.225 | $0.15 | $0.60 | 128K | Oct 2023 | −2% |
|
|
$0.225 | $0.15 | $0.60 | 205K | −2% | |
|
|
$0.225 | $0.15 | $0.60 | 256K | −2% | |
|
|
$0.225 | $0.17 | $0.50 | 262K | −2% | |
|
|
$0.23 | $0.08 | $0.98 | 262K | ||
|
|
$0.24 | $0.16 | $0.64 | 10M | Aug 2024 | +4% |
|
|
$0.2533 | $0.12 | $0.92 | 262K | +10% | |
|
|
$0.2833 | $0.20 | $0.70 | 1M | Aug 2024 | +23% |
|
|
$0.2833 | $0.20 | $0.70 | 262K | +23% | |
|
|
$0.30 | $0.20 | $0.80 | 131K | Jan 2026 | +30% |
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-Coder-Next good for?
Coding agents and local development, from an 80B mixture of experts with 3B active. Apache 2.0 weights, servable on a single high-memory GPU.
When is Qwen3-Coder-Next not a good fit?
Tasks that need a reasoning trace: it is non-thinking only. No image or video input, no built-in web search, though a host or your own tool loop can add one, and it takes more memory to serve than the Coder-30B-A3B sibling.
What is the cheapest way to run Qwen3-Coder-Next?
Hosted, unless you push serious volume. Alibaba Cloud charges $0.30 in / $1.50 out per 1M tokens. The cheapest rental that fits is 4x RTX 4060 Ti at $317 a month, which costs the same as about 634M tokens a month on that API.
Can I self-host Qwen3-Coder-Next?
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 | $0.17 | $0.50 |
|
|
16K | $0.16 | $0.49 |
|
|
262K | $0.12 | $0.92 |
|
|
262K | $0.15 | $0.50 |
|
|
1M | $0.15 | $0.47 |
|
|
262K | $0.09 | $0.69 |
|
|
262K | $0.20 | $0.70 |
|
|
33K | $0.30 | $0.30 |