comparison
GLM 4.6 vs Llama 4 Maverick
Token pricing, context window and real monthly cost, side by side. Llama 4 Maverick is the cheaper of the two for a typical workload — about 2.5× less.
Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.
By size & context, Llama 4 Maverick (Flagship) sits above GLM 4.6 (Mid) yet costs less. On spec it's the straightforward pick; choose GLM 4.6 only for something it offers that Llama 4 Maverick doesn't — modality, provider or ecosystem.
| metric | GLM 4.6 | Llama 4 Maverick |
|---|---|---|
| Input / 1M | $0.50 | $0.20 |
| Output / 1M | $2.00 | $0.80 |
| Context | 205K | 1.0M |
| Technical class | Mid | Flagship |
| Cost @ typical workload | $350/mo | $140/mo |
| Modality | Text only | text + image |
| Price source | routed | routed |
| Provider | Z.AI | Meta |
Snapshot . Cost uses a typical workload; tune it in the calculator. How we measure →
Which should you pick?
On a typical workload, Llama 4 Maverick costs $140/mo against GLM 4.6's $350/mo — roughly 2.5× 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, Llama 4 Maverick has the larger 1.0M-token window (~1,573 pages). Only Llama 4 Maverick accepts image input — decisive if your prompts include images. By technical class (size and context, not measured capability), Llama 4 Maverick is the larger class (Flagship) and the cheaper of the two — on spec, the stronger pick here.
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 GLM 4.6 or Llama 4 Maverick cheaper?
For a typical workload (1,500 input + 500 output tokens × 200,000 requests/month), Llama 4 Maverick costs $140/mo versus $350/mo for GLM 4.6 — about 2.5× 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 GLM 4.6 and Llama 4 Maverick?
On price, GLM 4.6 is $0.50/$2.00 per 1M (in/out) and Llama 4 Maverick is $0.20/$0.80. By technical class (size & context) it's Mid (GLM 4.6) versus Flagship (Llama 4 Maverick). Llama 4 Maverick has the larger context window at 1.0M tokens. Only Llama 4 Maverick accepts image input.
Which handles longer prompts, GLM 4.6 or Llama 4 Maverick?
Llama 4 Maverick — its 1.0M-token context window (~1,573 pages of text) is the larger of the two, by roughly 5×.
More comparisons
- GPT-5.4 mini vs GLM 4.6
- GPT-5.4 nano vs Llama 4 Maverick
- GLM 4.6 vs GPT-5.4 nano
- Llama 4 Maverick vs gpt-oss-120b
- Claude Haiku 4.5 vs GLM 4.6
- Gemini 2.5 Pro vs GLM 4.6
Related
- GLM 4.6 and Llama 4 Maverick — full specs and price history.
- API cost calculator — compare on your own workload.
- All comparisons — the full head-to-head index.