AI model comparison
Qwen3.5-122B-A10B vs Qwen3 235B A22B Thinking 2507
Side by side comparison of Qwen3.5-122B-A10B and Qwen3 235B A22B Thinking 2507 on pricing, benchmark scores, context window, and more.
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
- $0.40
- Output / 1M
- $3.20
- Context
- 262K
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks.
- Input / 1M
- $0.45
- Output / 1M
- $3.50
- Context
- 128K
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Qwen3.5-122B-A10B
1.1x cheaper for a typical chat
Higher intelligence score
Qwen3.5-122B-A10B
17.7 vs 12.7 on Artificial Analysis
Larger context window
Qwen3.5-122B-A10B
262K vs 128K 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 235B A22B Thinking 250712.7Coding index
Qwen3.5-122B-A10B43.3Qwen3 235B A22B Thinking 250722.1Agentic index
Qwen3.5-122B-A10BNot availableQwen3 235B A22B Thinking 25071.3Pricing
Qwen3.5-122B-A10B vs Qwen3 235B A22B Thinking 2507 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.5-122B-A10B | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Input tokensPer 1M tokens | $0.40 | $0.45 |
| Output tokensPer 1M tokens | $3.20 | $3.50 |
| Cached input (read)Per 1M tokens | Not available | Not available |
| 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$2.40Qwen3 235B A22B Thinking 2507$2.65Coding task
30K in, 4K out
Qwen3.5-122B-A10B$24.80Qwen3 235B A22B Thinking 2507$27.50Long document summary
150K in, 2K out
Qwen3.5-122B-A10B$66.40Qwen3 235B A22B Thinking 2507$74.50Specs
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 235B A22B Thinking 2507 |
|---|---|---|
| Context window | 262K tokens | 128K tokens |
| Max output | 66K tokens | 16K tokens |
| Input types | Image, Text, Video | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | February 25, 2026 | July 25, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.5-122B-A10B | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Not supported |
| JSON mode | Supported | Not supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Not 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.
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Our take
Qwen3.5-122B-A10B is 1.1x cheaper for a typical chat. Qwen3.5-122B-A10B scores higher on the Artificial Analysis Intelligence Index (17.7 vs 12.7). Qwen3.5-122B-A10B has the larger context window (262K vs 128K tokens). 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 235B A22B Thinking 2507 cheaper?
Qwen3.5-122B-A10B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3.5-122B-A10B costs $0.40 per 1M input tokens and $3.20 per 1M output tokens, while Qwen3 235B A22B Thinking 2507 costs $0.45 per 1M input tokens and $3.50 per 1M output tokens.
Which has a bigger context window, Qwen3.5-122B-A10B or Qwen3 235B A22B Thinking 2507?
Qwen3.5-122B-A10B supports up to 262K tokens of context, compared with 128K for Qwen3 235B A22B Thinking 2507.
Is Qwen3.5-122B-A10B smarter than Qwen3 235B A22B Thinking 2507?
On the Artificial Analysis Intelligence Index, Qwen3.5-122B-A10B scores 17.7 and Qwen3 235B A22B Thinking 2507 scores 12.7, putting Qwen3.5-122B-A10B 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 235B A22B Thinking 2507 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 235B A22B Thinking 2507 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3.5-122B-A10B and Qwen3 235B A22B Thinking 2507 at the same time. Compare the answers side by side and keep the best one.