AI model comparison
GLM 5.3 vs Qwen3.8 27B
Side by side comparison of GLM 5.3 and Qwen3.8 27B on pricing, benchmark scores, context window, and more.
GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks.
- Input / 1M
- $0.07
- Output / 1M
- $1.40
- Context
- 1.05M
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
- Input / 1M
- $0.04
- Output / 1M
- $1.25
- Context
- 1M
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
Qwen3.8 27B
1.2x cheaper for a typical chat
Higher intelligence score
GLM 5.3
31.7 vs 20.1 on Artificial Analysis
Larger context window
GLM 5.3
1.05M vs 1M tokens
Newer release
GLM 5.3
Released August 18, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.8 27B20.1Coding index
Qwen3.8 27B68.1Agentic index
Qwen3.8 27B45.8Pricing
GLM 5.3 vs Qwen3.8 27B API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.8 27B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.07 | $0.04 |
| Output tokensPer 1M tokens | $1.40 | $1.25 |
| Cached input (read)Per 1M tokens | $0.07 | $0.00 |
| 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
Qwen3.8 27B$0.70Coding task
30K in, 4K out
Qwen3.8 27B$6.17$5.12 cachedLong document summary
150K in, 2K out
Qwen3.8 27B$8.35$3.09 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3.8 27B | |
|---|---|---|
| Context window | 1.05M tokens | 1M tokens |
| Max output | 944K tokens | 66K tokens |
| Input types | Text | Image, Text, Video |
| Output types | Text | Text |
| Reasoning effort levels | Max, High, Low | Extra high, Medium, Low, None |
| Default reasoning effort | Max | Extra high |
| Release date | August 18, 2026 | August 14, 2026 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.8 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.
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Qwen3.8 27BView full model details- Qwen3.8 27B vs MiMo-V2.6-Pro
- Qwen3.8 27B vs DeepSeek V4.1 Flash 1017
- Qwen3.8 27B vs MiniMax M3.1 Flash
- Qwen3.8 27B vs Step 5 Preview
- Qwen3.8 27B vs GPT-6 Luna
- Qwen3.8 27B vs MiMo-V2.6-Flash
- Qwen3.8 27B vs Mistral Large 4
- Qwen3.8 27B vs DeepSeek V4 Pro 0813
- Qwen3.8 27B vs MiniMax M3
- Qwen3.8 27B vs Nemotron 3.5 Super VL
- Qwen3.8 27B vs Inkling Small
- Qwen3.8 27B vs Inkling
- Qwen3.8 27B vs Nemotron 3 Ultra
- Qwen3.8 27B vs Qwen3.8 Flash
- Qwen3.8 27B vs GLM 5.3 FlashX
- Qwen3.8 27B vs Qwen3.6 35B A3B
Our take
Qwen3.8 27B is 1.2x cheaper for a typical chat. GLM 5.3 scores higher on the Artificial Analysis Intelligence Index (31.7 vs 20.1). GLM 5.3 has the larger context window (1.05M vs 1M 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 GLM 5.3 or Qwen3.8 27B cheaper?
Qwen3.8 27B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3.8 27B costs $0.04 per 1M input tokens and $1.25 per 1M output tokens, while GLM 5.3 costs $0.07 per 1M input tokens and $1.40 per 1M output tokens.
Which has a bigger context window, GLM 5.3 or Qwen3.8 27B?
GLM 5.3 supports up to 1.05M tokens of context, compared with 1M for Qwen3.8 27B.
Is GLM 5.3 smarter than Qwen3.8 27B?
On the Artificial Analysis Intelligence Index, GLM 5.3 scores 31.7 and Qwen3.8 27B scores 20.1, putting GLM 5.3 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use GLM 5.3 and Qwen3.8 27B at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see GLM 5.3 and Qwen3.8 27B answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to GLM 5.3 and Qwen3.8 27B at the same time. Compare the answers side by side and keep the best one.