Grok 4.6 vs GLM-4.7
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Grok 4.6 | GLM-4.7 |
|---|---|---|
| Provider | xAI | Zhipu AI |
| Input Price (1M) | $2.00 | $0.60 |
| Output Price (1M) | $6.00 | $2.20 |
| Context Window | 500,000 | 204,800 |
Verdict
Grok 4.6 costs $2.00 per 1M input tokens and $6.00 per 1M output tokens. GLM-4.7 costs $0.60 per 1M input tokens and $2.20 per 1M output tokens. GLM-4.7 is 70% cheaper on input tokens than Grok 4.6. For output tokens, GLM-4.7 is the more affordable option at $2.20/1M vs $6.00.
On context window, Grok 4.6 supports 500,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Grok 4.6
- ✓ You need a larger context window (500,000 tokens)
- ✓ You are already integrated with xAI
When to choose GLM-4.7
- ✓ You need the lowest input token cost ($ 0.60/1M)
- ✓ Your workload is output-heavy — GLM-4.7 generates text cheaper
- ✓ You are already integrated with Zhipu AI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is Grok 4.6 cheaper than GLM-4.7? ▼
GLM-4.7 is cheaper on input tokens at $0.60/1M vs $2.00/1M for Grok 4.6 — a 70% saving.
What is the context window of Grok 4.6 vs GLM-4.7? ▼
Grok 4.6 has a 500,000-token context window. GLM-4.7 has a 204,800-token context window. Grok 4.6 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Grok 4.6 or GLM-4.7? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GLM-4.7 is the cheaper option. For maximum context length, Grok 4.6 supports 500,000 tokens. Use the comparison table above to find the right fit for your workload.