Qwen3.5-122B-A10B
qwen3.5-122b-a10bThe Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of... Built by Qwen.
Prices updated
Input price
$0.26
per 1M tokens · Standard
Output price
$2.08
per 1M tokens · Standard
Input limit
262K
tokens
Output limit
66K
tokens
Input formats
Output formats
Qwen3.5-122B-A10B price history
2 price records since 9/25/2026
Qwen3.5-122B-A10B cost calculator
$16/month
Standard pricing
Overview
What is Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B is a text & reasoning and vision model from Qwen. The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. In terms of... Its 262K context window and $0.26 input price make it a candidate for cost-sensitive, high-throughput applications.
Benchmarks
Qwen3.5-122B-A10B benchmarks & speed
How Qwen3.5-122B-A10B scores on standardized evaluations, and where it lands among every model we track.
15.6
Intelligence Index
129tok/s
Output speed
Reasoning
GPQA Diamond
85.7%
Graduate-level scientific reasoning · top 41%
HLE
25.2%
Humanity's Last Exam · top 44%
Coding
SciCode
39.7%
Python for scientific computing · top 81%
Latency & design
- Time to first token
- 2.35s
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
Qwen3.5-122B-A10B pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.26
Per 1M tokens
Cached input · Standard
Not available
No listed cached-input rate
Capabilities
Qwen3.5-122B-A10B Tools
Tools available when using Qwen3.5-122B-A10B through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Not supported
Strengths and limitations
Strengths
- Low input cost at $0.26 per million tokens suits high-volume workloads.
- 262K context supports large documents, repositories and extended conversations.
- Supports text & reasoning and vision workloads in one model.
Limitations
- Generated tokens cost 8× 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