Mistral Medium 3.5 vs GLM-4.7
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Mistral Medium 3.5 | GLM-4.7 |
|---|---|---|
| Provider | Mistral | Zhipu AI |
| Input Price (1M) | $1.50 | $0.60 |
| Output Price (1M) | $7.50 | $2.20 |
| Context Window | 262,000 | 204,800 |
Verdict
Mistral Medium 3.5 costs $1.50 per 1M input tokens and $7.50 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 60% cheaper on input tokens than Mistral Medium 3.5. For output tokens, GLM-4.7 is the more affordable option at $2.20/1M vs $7.50.
On context window, Mistral Medium 3.5 supports 262,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Mistral Medium 3.5
- ✓ You need a larger context window (262,000 tokens)
- ✓ You are already integrated with Mistral
When to choose GLM-4.7
- ✓ You need the lowest input token cost ($ 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 Mistral Medium 3.5 cheaper than GLM-4.7? ▼
GLM-4.7 is cheaper on input tokens at $0.60/1M vs $1.50/1M for Mistral Medium 3.5 — a 60% saving.
What is the context window of Mistral Medium 3.5 vs GLM-4.7? ▼
Mistral Medium 3.5 has a 262,000-token context window. GLM-4.7 has a 204,800-token context window. Mistral Medium 3.5 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Mistral Medium 3.5 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, Mistral Medium 3.5 supports 262,000 tokens. Use the comparison table above to find the right fit for your workload.