comparison
Qwen3 Max vs GLM 4.6
Token pricing, context window and real monthly cost, side by side. GLM 4.6 is the cheaper of the two for a typical workload — about 1.8× less.
Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.
Qwen3 Max is one class larger (Flagship vs Mid). Lean to the cheaper GLM 4.6 unless your task is demanding enough to need the larger class.
| metric | Qwen3 Max | GLM 4.6 |
|---|---|---|
| Input / 1M | $0.78 | $0.50 |
| Output / 1M | $3.90 | $2.00 |
| Context | 262K | 205K |
| Technical class | Flagship | Mid |
| Cost @ typical workload | $624/mo | $350/mo |
| Modality | Text only | Text only |
| Price source | routed | routed |
| Provider | Qwen | Z.AI |
Snapshot . Cost uses a typical workload; tune it in the calculator. How we measure →
Which should you pick?
On a typical workload, GLM 4.6 costs $350/mo against Qwen3 Max's $624/mo — roughly 1.8× cheaper. But the ranking depends on your output-to-input ratio: output is the pricier direction for both, so an output-heavy job (code generation, long answers) widens the gap while an input-heavy one (summarization, retrieval) narrows it. If you need to fit more in a single prompt, Qwen3 Max has the larger 262K-token window (~393 pages). By technical class (size and context, not measured capability), Qwen3 Max is a Flagship and GLM 4.6 a Mid — so the lower price partly reflects a smaller class, not just a discount.
These are list and routed market prices, not measured outcomes. Two models at the same rate can still cost different amounts to finish the same task, because verbose or reasoning-heavy models emit more tokens. That gap is exactly what measured cost-per-task captures. The technical-class read above is likewise spec-based — size, context and modality, not measured performance — so a smaller model can still outperform a larger one on your specific task.
Frequently asked questions
Is Qwen3 Max or GLM 4.6 cheaper?
For a typical workload (1,500 input + 500 output tokens × 200,000 requests/month), GLM 4.6 costs $350/mo versus $624/mo for Qwen3 Max — about 1.8× less. Because output is priced higher than input, the winner can flip if your workload writes much more or less than this; check your own numbers in the calculator.
What's the main difference between Qwen3 Max and GLM 4.6?
On price, Qwen3 Max is $0.78/$3.90 per 1M (in/out) and GLM 4.6 is $0.50/$2.00. By technical class (size & context) it's Flagship (Qwen3 Max) versus Mid (GLM 4.6). Qwen3 Max has the larger context window at 262K tokens.
More comparisons
- GPT-5.4 vs Qwen3 Max
- GPT-5.4 mini vs Qwen3 Max
- GPT-5.4 mini vs GLM 4.6
- Qwen3 Max vs GPT-5.4 nano
- GLM 4.6 vs GPT-5.4 nano
- Claude Sonnet 4.6 vs Qwen3 Max
Related
- Qwen3 Max and GLM 4.6 — full specs and price history.
- API cost calculator — compare on your own workload.
- All comparisons — the full head-to-head index.