AI model comparison
Ling 3.0 Flash vs Qwen3.5-9B
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
inclusionAI
Ling 3.0 Flash
*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*.
- Input / 1M
- $0.02
- Output / 1M
- $0.06
- Context
- 262K
Qwen
Qwen3.5-9B
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture.
Qwen3.5-9B is scheduled to be retired on October 21, 2026. Consider Qwen3.8 27B instead.
- Input / 1M
- $0.10
- Output / 1M
- $0.15
- Context
- 262K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Ling 3.0 Flash
3.7x cheaper for a typical chat
Higher intelligence score
Ling 3.0 Flash
20.1 vs 13.3 on Artificial Analysis
Larger context window
Tie
262K vs 262K tokens
Newer release
Ling 3.0 Flash
Released July 23, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.5-9B13.3Coding index
Qwen3.5-9B23.5Agentic index
Qwen3.5-9BNot availablePricing
Ling 3.0 Flash vs Qwen3.5-9B API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.5-9B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.02 | $0.10 |
| Output tokensPer 1M tokens | $0.06 | $0.15 |
| Cached input (read)Per 1M tokens | $0.00 | 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
Qwen3.5-9B$0.27Coding task
30K in, 4K out
Qwen3.5-9B$3.60Long document summary
150K in, 2K out
Qwen3.5-9B$15.30Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3.5-9B | |
|---|---|---|
| Context window | 262K tokens | 262K tokens |
| Max output | 33K tokens | 33K tokens |
| Input types | Text | Image, Text, Video |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | July 23, 2026 | March 10, 2026 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.5-9B | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Not 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.
- Ling 3.0 Flash vs Hy3
- Ling 3.0 Flash vs DeepSeek V4 Flash 0423
- Ling 3.0 Flash vs Solar Mini 4
- Ling 3.0 Flash vs Qwen3.6 35B A3B
- Ling 3.0 Flash vs MiMo-V2.5
- Ling 3.0 Flash vs Gemma 4 26B A4B
- Ling 3.0 Flash vs DeepSeek V3.2
- Ling 3.0 Flash vs Mistral Nemo
- Ling 3.0 Flash vs Ling 3.0 Flash VL
- Ling 3.0 Flash vs Step 3.5 Flash
Qwen3.5-9BView full model details- Qwen3.5-9B vs Gemini 2.5 Flash Lite
- Qwen3.5-9B vs gpt-oss-120b
- Qwen3.5-9B vs Gemma 4 31B
- Qwen3.5-9B vs Qwen3.7 Flash
- Qwen3.5-9B vs Gemma 4 26B A4B
- Qwen3.5-9B vs gpt-oss-20b
- Qwen3.5-9B vs GPT-5 Nano
- Qwen3.5-9B vs Qwen3 235B A22B Instruct 2507
- Qwen3.5-9B vs Mercury 2.5
- Qwen3.5-9B vs Nemotron 3.5 Lightning
- Qwen3.5-9B vs Qwen3 Coder 30B A3B Instruct
Our take
Ling 3.0 Flash is 3.7x cheaper for a typical chat. Ling 3.0 Flash scores higher on the Artificial Analysis Intelligence Index (20.1 vs 13.3). 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 Ling 3.0 Flash or Qwen3.5-9B cheaper?
Ling 3.0 Flash is cheaper for a typical chat (2K input tokens and 500 output tokens). Ling 3.0 Flash costs $0.02 per 1M input tokens and $0.06 per 1M output tokens, while Qwen3.5-9B costs $0.10 per 1M input tokens and $0.15 per 1M output tokens.
Which has a bigger context window, Ling 3.0 Flash or Qwen3.5-9B?
Ling 3.0 Flash supports up to 262K tokens of context, compared with 262K for Qwen3.5-9B.
Is Ling 3.0 Flash smarter than Qwen3.5-9B?
On the Artificial Analysis Intelligence Index, Ling 3.0 Flash scores 20.1 and Qwen3.5-9B scores 13.3, putting Ling 3.0 Flash ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Ling 3.0 Flash and Qwen3.5-9B at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Ling 3.0 Flash and Qwen3.5-9B answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Ling 3.0 Flash and Qwen3.5-9B at the same time. Compare the answers side by side and keep the best one.