AI model comparison
GLM 4.5 vs Qwen3 235B A22B Thinking 2507
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Z.ai
GLM 4.5
GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens.
GLM 4.5 is scheduled to be retired on December 31, 2026. Consider GLM 5.3 instead.
- Input / 1M
- $0.60
- Output / 1M
- $2.20
- Context
- 131K
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
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
GLM 4.5
1.2x cheaper for a typical chat
Higher intelligence score
GLM 4.5
12.8 vs 12.7 on Artificial Analysis
Larger context window
GLM 4.5
131K vs 128K tokens
Newer release
GLM 4.5
Released July 25, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3 235B A22B Thinking 250712.7Coding index
Qwen3 235B A22B Thinking 250722.1Agentic index
Qwen3 235B A22B Thinking 25071.3Pricing
GLM 4.5 vs Qwen3 235B A22B Thinking 2507 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3 235B A22B Thinking 2507 | |
|---|---|---|
| Input tokensPer 1M tokens | $0.60 | $0.45 |
| Output tokensPer 1M tokens | $2.20 | $3.50 |
| Cached input (read)Per 1M tokens | $0.11 | 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 235B A22B Thinking 2507$2.65Coding task
30K in, 4K out
Qwen3 235B A22B Thinking 2507$27.50Long document summary
150K in, 2K out
Qwen3 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 235B A22B Thinking 2507 | |
|---|---|---|
| Context window | 131K tokens | 128K tokens |
| Max output | 98K tokens | 16K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | July 25, 2025 | July 25, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3 235B A22B Thinking 2507 | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Not supported | Not supported |
| JSON mode | Supported | Not supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Not supported | Supported |
| Deterministic seed | Not 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.
Qwen3 235B A22B Thinking 2507View full model details- Qwen3 235B A22B Thinking 2507 vs Gemini 2.5 Flash
- Qwen3 235B A22B Thinking 2507 vs Mistral Medium 3.5
- Qwen3 235B A22B Thinking 2507 vs Nova 2 Lite
- Qwen3 235B A22B Thinking 2507 vs R1 0528
- Qwen3 235B A22B Thinking 2507 vs Command A
- Qwen3 235B A22B Thinking 2507 vs GPT-4.1
- Qwen3 235B A22B Thinking 2507 vs Kimi K2 0711
- Qwen3 235B A22B Thinking 2507 vs o3 Mini
- Qwen3 235B A22B Thinking 2507 vs Qwen3 235B A22B Instruct 2507
- Qwen3 235B A22B Thinking 2507 vs Qwen3 Coder 480B A35B
- Qwen3 235B A22B Thinking 2507 vs Sonar Reasoning Pro
- Qwen3 235B A22B Thinking 2507 vs o3 Mini High
- Qwen3 235B A22B Thinking 2507 vs Qwen3 VL 235B A22B Instruct
Our take
GLM 4.5 is 1.2x cheaper for a typical chat. GLM 4.5 scores higher on the Artificial Analysis Intelligence Index (12.8 vs 12.7). GLM 4.5 has the larger context window (131K 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 GLM 4.5 or Qwen3 235B A22B Thinking 2507 cheaper?
GLM 4.5 is cheaper for a typical chat (2K input tokens and 500 output tokens). GLM 4.5 costs $0.60 per 1M input tokens and $2.20 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, GLM 4.5 or Qwen3 235B A22B Thinking 2507?
GLM 4.5 supports up to 131K tokens of context, compared with 128K for Qwen3 235B A22B Thinking 2507.
Is GLM 4.5 smarter than Qwen3 235B A22B Thinking 2507?
On the Artificial Analysis Intelligence Index, GLM 4.5 scores 12.8 and Qwen3 235B A22B Thinking 2507 scores 12.7, putting GLM 4.5 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use GLM 4.5 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 GLM 4.5 and Qwen3 235B A22B Thinking 2507 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to GLM 4.5 and Qwen3 235B A22B Thinking 2507 at the same time. Compare the answers side by side and keep the best one.