Qwen3 Coder Next
qwen3-coder-nextQwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per... Built by Qwen.
Prices updated
Input price
$0.12
per 1M tokens · Standard
Output price
$0.80
per 1M tokens · Standard
Input limit
262K
tokens
Output limit
236K
tokens
Input formats
Output formats
Qwen3 Coder Next price history
2 price records since 9/25/2026
Qwen3 Coder Next cost calculator
$6.40/month
Standard pricing
Overview
What is Qwen3 Coder Next?
Qwen3 Coder Next is a text & reasoning and code & slms model from Qwen. Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per... Its 262K context window and $0.12 input price make it a candidate for cost-sensitive, high-throughput applications.
Benchmarks
Qwen3 Coder Next benchmarks & speed
How Qwen3 Coder Next scores on standardized evaluations, and where it lands among every model we track.
9.2
Intelligence Index
101tok/s
Output speed
Reasoning
GPQA Diamond
73.7%
Graduate-level scientific reasoning · top 66%
HLE
10.1%
Humanity's Last Exam · top 66%
Coding
SciCode
36.2%
Python for scientific computing · top 87%
Latency & design
- Time to first token
- 1.4s
Independent scores from Artificial Analysis and DesignArena · updated 10/5/2026. Higher is better; ranks compare against every model we track with that score.
Rates
Qwen3 Coder Next pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.12
Per 1M tokens
Cached input · Standard
$0.07
Per 1M tokens
Capabilities
Qwen3 Coder Next Tools
Tools available when using Qwen3 Coder Next through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Not supported
Built-in web search
Not supported
Log probabilities
Supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Supported
Strengths and limitations
Strengths
- Low input cost at $0.12 per million tokens suits high-volume workloads.
- 262K context supports large documents, repositories and extended conversations.
- Supports text & reasoning and code & slms workloads in one model.
Limitations
- Generated tokens cost 7× more than input tokens, which matters for verbose responses.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
Same provider
