Qwen3 Next 80B A3B Thinking
Alibaba
Qwen3-Next uses a highly sparse MoE design: 80B total parameters, but only ~3B activated per inference step. Experiments show that, with global load balancing, increasing total expert parameters while keeping activated experts fixed steadily reduces training loss.Compared to Qwen3’s MoE (128 total experts, 8 routed), Qwen3-Next expands to 512 total experts, combining 10 routed experts + 1 shared expert — maximizing resource usage without hurting performance. The Qwen3-Next-80B-A3B-Thinking excels at complex reasoning tasks — outperforming higher-cost models like Qwen3-30B-A3B-Thinking-2507 and Qwen3-32B-Thinking, outpeforming the closed-source Gemini-2.5-Flash-Thinking on multiple benchmarks, and approaching the performance of our top-tier model Qwen3-235B-A22B-Thinking-2507.
- Language
- Reasoning
- Tool use
- Structured output
- open weights
- Context
- 262K
- Max output
- 262K
- Input / 1M
- $0.150
- Output / 1M
- $1.20
Quickstart
Point any OpenAI-compatible client at Maxynetic Systems and pass alibaba/qwen3-next-80b-a3b-thinking as the model.
curl https://api.maxynetic.com/v1/chat/completions \
-H "Authorization: Bearer $MAXYNETIC_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "alibaba/qwen3-next-80b-a3b-thinking",
"messages": [{ "role": "user", "content": "Explain routing in one line." }]
}'Pricing
Billed per token with no markup on the underlying provider rate.
Input
Per 1M prompt tokens
$0.150
Output
Per 1M completion tokens
$1.20
A 1M-token prompt with 250K tokens of output costs about $0.450.