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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 token, delivering performance comparable to models with 10 to 20x higher active compute, which makes it well suited for cost-sensitive, always-on agent deployment. The model is trained with a strong agentic focus and performs reliably on long-horizon coding tasks, complex tool usage, and recovery from execution failures. With a native 256k context window, it integrates cleanly into real-world CLI and IDE environments and adapts well to common agent scaffolds used by modern coding tools. The model operates exclusively in non-thinking mode and does not emit <think> blocks, simplifying integration for production coding agents.
Quality Index
28.3
113th of 444
Top 26%
Coding Index
22.9
127th of 354
Top 36%
Price/1M
$0.60
409th cheapest
100% above median
Top 60%
Speed
149 tok/s
Top 13%
TTFT
0.87s
Context Window
262K
61st largest
Top 25%
Input
$0.35
per 1M tokens
Output
$1.20
per 1M tokens
Blended
$0.60
per 1M tokens
Cheaper than 40% of models. Median price is $0.30/1M tokens.
Daily
$0.60
Monthly
$18.00
149
tokens/sec
Faster than 87% of models
0.87
seconds
Faster than 34% of models
0.87
seconds
Faster than 41% of models
Market Median
45 tok/s
228% faster
Median TTFT
0.42s
108% slower
Throughput/Dollar
248
tok/s per $/1M
Speed Comparison
Context Window
262K
tokens
Larger than 75% of models
Max Output
66K
tokens
25% of context