AI model comparison
Qwen3.5-122B-A10B vs Qwen3.5 397B A17B
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
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.
- Input / 1M
- $0.26
- Output / 1M
- $2.08
- Context
- 262K
The Qwen3.5 series 397B-A17B 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.
- Input / 1M
- $0.55
- Output / 1M
- $3.50
- Context
- 262K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Qwen3.5-122B-A10B
1.8x cheaper for a typical chat
Higher intelligence score
Qwen3.5 397B A17B
21.4 vs 17.7 on Artificial Analysis
Larger context window
Tie
262K vs 262K tokens
Newer release
Qwen3.5-122B-A10B
Released February 25, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.5-122B-A10B17.7Qwen3.5 397B A17B21.4Coding index
Qwen3.5-122B-A10B43.3Qwen3.5 397B A17BNot availableAgentic index
Qwen3.5-122B-A10BNot availableQwen3.5 397B A17BNot availablePricing
Qwen3.5-122B-A10B vs Qwen3.5 397B A17B API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.5-122B-A10B | Qwen3.5 397B A17B |
|---|---|---|
| Input tokensPer 1M tokens | $0.26 | $0.55 |
| Output tokensPer 1M tokens | $2.08 | $3.50 |
| Cached input (read)Per 1M tokens | Not available | $0.22 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Qwen3.5-122B-A10B$1.56Qwen3.5 397B A17B$2.85Coding task
30K in, 4K out
Qwen3.5-122B-A10B$16.12Qwen3.5 397B A17B$30.50$20.75 cachedLong document summary
150K in, 2K out
Qwen3.5-122B-A10B$43.16Qwen3.5 397B A17B$89.50$40.75 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3.5-122B-A10B | Qwen3.5 397B A17B |
|---|---|---|
| Context window | 262K tokens | 262K tokens |
| Max output | 66K tokens | 236K tokens |
| Input types | Image, Text, Video | Image, Text, Video |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | February 25, 2026 | February 16, 2026 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.5-122B-A10B | Qwen3.5 397B A17B |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
Qwen3.5-122B-A10BView full model details- Qwen3.5-122B-A10B vs Qwen3.6 27B
- Qwen3.5-122B-A10B vs GPT-5 Mini
- Qwen3.5-122B-A10B vs Qwen3.5-35B-A3B
- Qwen3.5-122B-A10B vs GLM 4.6
- Qwen3.5-122B-A10B vs Qwen3.6 35B A3B
- Qwen3.5-122B-A10B vs Muse Glimmer 30B
- Qwen3.5-122B-A10B vs Gemini 3.1 Flash Lite
- Qwen3.5-122B-A10B vs Claude Haiku 4.5
- Qwen3.5-122B-A10B vs Gemini 2.5 Flash
- Qwen3.5-122B-A10B vs Kimi K2 0905
Qwen3.5 397B A17BView full model details- Qwen3.5 397B A17B vs DeepSeek V4 Flash 0423
- Qwen3.5 397B A17B vs Gemini 3 Flash Preview
- Qwen3.5 397B A17B vs GPT-5.4 Mini
- Qwen3.5 397B A17B vs GLM 5V Turbo
- Qwen3.5 397B A17B vs Gemini 3.5 Flash Lite
- Qwen3.5 397B A17B vs Qwen3.5-27B
- Qwen3.5 397B A17B vs GLM 4.7
- Qwen3.5 397B A17B vs Kimi K2 Thinking
- Qwen3.5 397B A17B vs Qwen3.6 27B
- Qwen3.5 397B A17B vs Claude Sonnet 4.5
- Qwen3.5 397B A17B vs GPT-5 Mini
- Qwen3.5 397B A17B vs GPT-5.1-Codex-Mini
- Qwen3.5 397B A17B vs Claude Sonnet 4
Our take
Qwen3.5-122B-A10B is 1.8x cheaper for a typical chat. Qwen3.5 397B A17B scores higher on the Artificial Analysis Intelligence Index (21.4 vs 17.7). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Qwen3.5-122B-A10B or Qwen3.5 397B A17B cheaper?
Qwen3.5-122B-A10B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3.5-122B-A10B costs $0.26 per 1M input tokens and $2.08 per 1M output tokens, while Qwen3.5 397B A17B costs $0.55 per 1M input tokens and $3.50 per 1M output tokens.
Which has a bigger context window, Qwen3.5-122B-A10B or Qwen3.5 397B A17B?
Qwen3.5-122B-A10B supports up to 262K tokens of context, compared with 262K for Qwen3.5 397B A17B.
Is Qwen3.5-122B-A10B smarter than Qwen3.5 397B A17B?
On the Artificial Analysis Intelligence Index, Qwen3.5-122B-A10B scores 17.7 and Qwen3.5 397B A17B scores 21.4, putting Qwen3.5 397B A17B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3.5-122B-A10B and Qwen3.5 397B A17B at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3.5-122B-A10B and Qwen3.5 397B A17B answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3.5-122B-A10B and Qwen3.5 397B A17B at the same time. Compare the answers side by side and keep the best one.