AI model comparison
Qwen3.5-27B vs GLM 4.7
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Qwen
Qwen3.5-27B
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance.
- Input / 1M
- $0.26
- Output / 1M
- $2.60
- Context
- 262K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Qwen3.5-27B
1.3x cheaper for a typical chat
Higher intelligence score
Qwen3.5-27B
22.9 vs 22.2 on Artificial Analysis
Larger context window
Qwen3.5-27B
262K vs 205K tokens
Newer release
Qwen3.5-27B
Released February 25, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.5-27B22.9Coding index
Qwen3.5-27BNot availableAgentic index
Qwen3.5-27BNot availablePricing
Qwen3.5-27B vs GLM 4.7 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.5-27B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.26 | $0.60 |
| Output tokensPer 1M tokens | $2.60 | $2.20 |
| Cached input (read)Per 1M tokens | Not available | $0.11 |
| 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
Qwen3.5-27B$1.82Coding task
30K in, 4K out
Qwen3.5-27B$18.20Long document summary
150K in, 2K out
Qwen3.5-27B$44.20Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3.5-27B | |
|---|---|---|
| Context window | 262K tokens | 205K tokens |
| Max output | 82K tokens | 131K 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 | December 22, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.5-27B | |
|---|---|---|
| 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.
Qwen3.5-27BView full model details- Qwen3.5-27B vs Qwen3.6 Plus
- Qwen3.5-27B vs Gemini 3 Flash Preview
- Qwen3.5-27B vs Qwen3.7 Plus
- Qwen3.5-27B vs Grok 4.3
- Qwen3.5-27B vs DeepSeek V4 Flash 0423
- Qwen3.5-27B vs Kimi K2.5
- Qwen3.5-27B vs Nemotron 3 Ultra
- Qwen3.5-27B vs Gemini 3.5 Flash Lite
- Qwen3.5-27B vs Kimi K2 Thinking
- Qwen3.5-27B vs Qwen3.5 397B A17B
- Qwen3.5-27B vs Qwen3.6 27B
- GLM 4.7 vs DeepSeek V4 Flash 0423
- GLM 4.7 vs GLM 5
- GLM 4.7 vs GLM 5.1
- GLM 4.7 vs Gemini 3.5 Flash Lite
- GLM 4.7 vs Kimi K2.5
- GLM 4.7 vs GLM 5V Turbo
- GLM 4.7 vs Nemotron 3 Ultra
- GLM 4.7 vs Kimi K2 Thinking
- GLM 4.7 vs Qwen3.5 397B A17B
- GLM 4.7 vs GPT-5 Mini
- GLM 4.7 vs Qwen3.6 27B
- GLM 4.7 vs GPT-5.1-Codex-Mini
- GLM 4.7 vs GLM 4.6
Our take
Qwen3.5-27B is 1.3x cheaper for a typical chat. Qwen3.5-27B scores higher on the Artificial Analysis Intelligence Index (22.9 vs 22.2). Qwen3.5-27B has the larger context window (262K vs 205K 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 Qwen3.5-27B or GLM 4.7 cheaper?
Qwen3.5-27B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3.5-27B costs $0.26 per 1M input tokens and $2.60 per 1M output tokens, while GLM 4.7 costs $0.60 per 1M input tokens and $2.20 per 1M output tokens.
Which has a bigger context window, Qwen3.5-27B or GLM 4.7?
Qwen3.5-27B supports up to 262K tokens of context, compared with 205K for GLM 4.7.
Is Qwen3.5-27B smarter than GLM 4.7?
On the Artificial Analysis Intelligence Index, Qwen3.5-27B scores 22.9 and GLM 4.7 scores 22.2, putting Qwen3.5-27B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3.5-27B and GLM 4.7 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3.5-27B and GLM 4.7 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3.5-27B and GLM 4.7 at the same time. Compare the answers side by side and keep the best one.