Command A Pro vs GLM-4.6: which model should you choose?
We compared Command A Pro and GLM-4.6 on price, context window and 12 benchmarks. Command A Pro has the stronger average benchmark score; GLM-4.6 is cheaper on a blended 3:1 basis.
Command A Pro
Command A Pro is a multimodal model from Cohere. It offers a 200,000-token context window, costs $14.28 per million input tokens and $68.05 per million output tokens, and averages 81.3 across the index's benchmark suite.
- Input
- $14.28 / 1M
- Output
- $68.05 / 1M
- Context
- 200,000
- Avg score
- 81.3
- Open weights
- No
GLM-4.6
GLM-4.6 is a multimodal model from Zhipu AI. It offers a 128,000-token context window, costs $5.10 per million input tokens and $18.45 per million output tokens, and averages 80.2 across the index's benchmark suite.
- Input
- $5.10 / 1M
- Output
- $18.45 / 1M
- Context
- 128,000
- Avg score
- 80.2
- Open weights
- Yes
Specification comparison
| Spec | Command A Pro | GLM-4.6 | Edge |
|---|---|---|---|
| Input price / 1M | $14.28 | $5.10 | B |
| Output price / 1M | $68.05 | $18.45 | B |
| Context window | 200,000 | 128,000 | A |
| Max output | 16,384 | 8,192 | A |
| Average score | 81.3 | 80.2 | A |
| Arena Elo | 1434.6 | 1440.7 | B |
| Open weights | No | Yes | B |
Benchmark comparison
Command A Pro wins 8, GLM-4.6 wins 4, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | Command A Pro | GLM-4.6 | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 81.3 | 84.0 | 2.7 | GLM-4.6 |
| GPQA Diamond | 79.1 | 78.3 | 0.8 | Command A Pro |
| SWE-bench Verified | 71.2 | 67.4 | 3.8 | Command A Pro |
| HumanEval | 87.5 | 83.8 | 3.7 | Command A Pro |
| MATH-500 | 83.1 | 83.4 | 0.3 | GLM-4.6 |
| AIME 2025 | 78.2 | 80.2 | 2.0 | GLM-4.6 |
| LiveCodeBench | 74.0 | 71.6 | 2.4 | Command A Pro |
| IFEval | 89.0 | 86.4 | 2.6 | Command A Pro |
| TruthfulQA | 83.3 | 82.5 | 0.8 | Command A Pro |
| HellaSwag | 90.1 | 89.4 | 0.7 | Command A Pro |
| MMMU | 77.2 | 75.4 | 1.8 | Command A Pro |
| Arena Elo | 1434.6 | 1440.7 | 6.1 | GLM-4.6 |
Price analysis
On a blended 3:1 input-to-output basis, Command A Pro costs about $27.72 per million tokens and GLM-4.6 costs about $8.44. GLM-4.6 is roughly 70% cheaper than Command A Pro. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Command A Pro has the larger context window at 200,000 tokens, compared with 128,000 for GLM-4.6. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, Command A Pro wins 8, GLM-4.6 wins 4, and 0 are tied. On the index average, Command A Pro leads GLM-4.6 by 1.1 points (81.3 versus 80.2).
The price picture favours GLM-4.6. The context picture favours Command A Pro. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with Command A Pro for quality-sensitive work and GLM-4.6 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose Command A Pro if
- You want the higher average benchmark score in this index.
- You need the larger 200,000-token context window.
- You need the larger 16,384-token output limit.
Choose GLM-4.6 if
- Unit cost matters and you want the cheaper blended price.
- You need open weights for self-hosting or fine-tuning.
FAQ
Is Command A Pro better than GLM-4.6?
On the index average, Command A Pro leads GLM-4.6 by 1.1 points (81.3 versus 80.2). The better choice depends on price, context and your task. Command A Pro wins 8 benchmarks, GLM-4.6 wins 4.
Which is cheaper, Command A Pro or GLM-4.6?
GLM-4.6 is cheaper on a blended 3:1 basis at about $8.44 per million tokens, versus $27.72 for Command A Pro.
Which has the larger context window?
Command A Pro has the larger context window at 200,000 tokens. GLM-4.6 has 128,000 tokens.
Are these models open weights?
Command A Pro is proprietary; GLM-4.6 is open weights.
Which should I choose for production?
If you need a single default, start with Command A Pro for quality-sensitive work and GLM-4.6 for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.