AI model comparison
Qwen3.5-9B vs gpt-oss-120b
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
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
OpenAI
gpt-oss-120b
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases.
- Input / 1M
- $0.04
- Output / 1M
- $0.17
- Context
- 131K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
gpt-oss-120b
1.7x cheaper for a typical chat
Higher intelligence score
Qwen3.5-9B
13.3 vs 11.6 on Artificial Analysis
Larger context window
Qwen3.5-9B
262K vs 131K tokens
Newer release
Qwen3.5-9B
Released March 10, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.5-9B13.3gpt-oss-120b11.6Coding index
Qwen3.5-9B23.5gpt-oss-120b30.4Agentic index
Qwen3.5-9BNot availablegpt-oss-120b3.7Pricing
Qwen3.5-9B vs gpt-oss-120b API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.5-9B | gpt-oss-120b |
|---|---|---|
| Input tokensPer 1M tokens | $0.10 | $0.04 |
| Output tokensPer 1M tokens | $0.15 | $0.17 |
| 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
Qwen3.5-9B$0.27gpt-oss-120b$0.16Coding task
30K in, 4K out
Qwen3.5-9B$3.60gpt-oss-120b$1.79Long document summary
150K in, 2K out
Qwen3.5-9B$15.30gpt-oss-120b$5.89Specs
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 | gpt-oss-120b |
|---|---|---|
| Context window | 262K tokens | 131K tokens |
| Max output | 33K tokens | 118K tokens |
| Input types | Image, Text, Video | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | High, Medium, Low |
| Default reasoning effort | Not available | Medium |
| Release date | March 10, 2026 | August 5, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.5-9B | gpt-oss-120b |
|---|---|---|
| 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.
Qwen3.5-9BView full model details- Qwen3.5-9B vs Gemini 2.5 Flash Lite
- Qwen3.5-9B vs Gemma 4 31B
- Qwen3.5-9B vs Qwen3.7 Flash
- 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 32B
- Qwen3.5-9B vs Qwen3 Coder 30B A3B Instruct
gpt-oss-120bView full model details- gpt-oss-120b vs Muse Spark 1.3 Contributor
- gpt-oss-120b vs Gemini 2.5 Flash Lite
- gpt-oss-120b vs Gemma 4 31B
- gpt-oss-120b vs Qwen3.7 Flash
- gpt-oss-120b vs gpt-oss-20b
- gpt-oss-120b vs GPT-5 Nano
- gpt-oss-120b vs Qwen3 235B A22B Instruct 2507
- gpt-oss-120b vs Mercury 2.5
- gpt-oss-120b vs Nemotron 3.5 Lightning
- gpt-oss-120b vs GPT-4.1 Nano
- gpt-oss-120b vs Granite 4.2 8B
- gpt-oss-120b vs Nemotron 3 Super
- gpt-oss-120b vs Mistral Small 4
- gpt-oss-120b vs Qwen3 Coder 30B A3B Instruct
- gpt-oss-120b vs Nemotron 3 Nano 30B A3B
Our take
gpt-oss-120b is 1.7x cheaper for a typical chat. Qwen3.5-9B scores higher on the Artificial Analysis Intelligence Index (13.3 vs 11.6). Qwen3.5-9B has the larger context window (262K vs 131K 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 Qwen3.5-9B or gpt-oss-120b cheaper?
gpt-oss-120b is cheaper for a typical chat (2K input tokens and 500 output tokens). gpt-oss-120b costs $0.04 per 1M input tokens and $0.17 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, Qwen3.5-9B or gpt-oss-120b?
Qwen3.5-9B supports up to 262K tokens of context, compared with 131K for gpt-oss-120b.
Is Qwen3.5-9B smarter than gpt-oss-120b?
On the Artificial Analysis Intelligence Index, Qwen3.5-9B scores 13.3 and gpt-oss-120b scores 11.6, putting Qwen3.5-9B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3.5-9B and gpt-oss-120b at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3.5-9B and gpt-oss-120b answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3.5-9B and gpt-oss-120b at the same time. Compare the answers side by side and keep the best one.