GLM-4.6 Instruct vs Llama 4 Maverick Chat: which model should you choose?
We compared GLM-4.6 Instruct and Llama 4 Maverick Chat on price, context window and 12 benchmarks. GLM-4.6 Instruct has the stronger average benchmark score; Llama 4 Maverick Chat is cheaper on a blended 3:1 basis.
GLM-4.6 Instruct
GLM-4.6 Instruct is a multimodal model from Zhipu AI. It offers a 1,000,000-token context window, costs $5.15 per million input tokens and $24.32 per million output tokens, and averages 80.4 across the index's benchmark suite.
- Input
- $5.15 / 1M
- Output
- $24.32 / 1M
- Context
- 1,000,000
- Avg score
- 80.4
- Open weights
- Yes
Llama 4 Maverick Chat
Llama 4 Maverick Chat is a multimodal model from Meta AI. It offers a 128,000-token context window, costs $5.09 per million input tokens and $23.20 per million output tokens, and averages 79.7 across the index's benchmark suite.
- Input
- $5.09 / 1M
- Output
- $23.20 / 1M
- Context
- 128,000
- Avg score
- 79.7
- Open weights
- Yes
Specification comparison
| Spec | GLM-4.6 Instruct | Llama 4 Maverick Chat | Edge |
|---|---|---|---|
| Input price / 1M | $5.15 | $5.09 | B |
| Output price / 1M | $24.32 | $23.20 | B |
| Context window | 1,000,000 | 128,000 | A |
| Max output | 128,000 | 32,768 | A |
| Average score | 80.4 | 79.7 | A |
| Arena Elo | 1426.6 | 1419.9 | A |
| Open weights | Yes | Yes | Tie |
Benchmark comparison
GLM-4.6 Instruct wins 9, Llama 4 Maverick Chat wins 2, and 1 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GLM-4.6 Instruct | Llama 4 Maverick Chat | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 80.6 | 80.5 | 0.1 | GLM-4.6 Instruct |
| GPQA Diamond | 75.8 | 73.0 | 2.8 | GLM-4.6 Instruct |
| SWE-bench Verified | 70.5 | 66.6 | 3.9 | GLM-4.6 Instruct |
| HumanEval | 85.3 | 83.2 | 2.1 | GLM-4.6 Instruct |
| MATH-500 | 84.9 | 84.8 | 0.1 | GLM-4.6 Instruct |
| AIME 2025 | 74.5 | 78.9 | 4.4 | Llama 4 Maverick Chat |
| LiveCodeBench | 72.6 | 76.3 | 3.7 | Llama 4 Maverick Chat |
| IFEval | 87.4 | 87.4 | 0.0 | Tie |
| TruthfulQA | 83.8 | 81.5 | 2.3 | GLM-4.6 Instruct |
| HellaSwag | 90.6 | 88.8 | 1.8 | GLM-4.6 Instruct |
| MMMU | 78.9 | 75.4 | 3.5 | GLM-4.6 Instruct |
| Arena Elo | 1426.6 | 1419.9 | 6.7 | GLM-4.6 Instruct |
Price analysis
On a blended 3:1 input-to-output basis, GLM-4.6 Instruct costs about $9.94 per million tokens and Llama 4 Maverick Chat costs about $9.62. Llama 4 Maverick Chat is roughly 3% cheaper than GLM-4.6 Instruct. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GLM-4.6 Instruct has the larger context window at 1,000,000 tokens, compared with 128,000 for Llama 4 Maverick Chat. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GLM-4.6 Instruct wins 9, Llama 4 Maverick Chat wins 2, and 1 are tied. On the index average, GLM-4.6 Instruct leads Llama 4 Maverick Chat by 0.7 points (80.4 versus 79.7).
The price picture favours Llama 4 Maverick Chat. The context picture favours GLM-4.6 Instruct. 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 GLM-4.6 Instruct for quality-sensitive work and Llama 4 Maverick Chat for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.
Choose GLM-4.6 Instruct if
- You want the higher average benchmark score in this index.
- You need the larger 1,000,000-token context window.
- You need the larger 128,000-token output limit.
Choose Llama 4 Maverick Chat if
- Unit cost matters and you want the cheaper blended price.
FAQ
Is GLM-4.6 Instruct better than Llama 4 Maverick Chat?
On the index average, GLM-4.6 Instruct leads Llama 4 Maverick Chat by 0.7 points (80.4 versus 79.7). The better choice depends on price, context and your task. GLM-4.6 Instruct wins 9 benchmarks, Llama 4 Maverick Chat wins 2.
Which is cheaper, GLM-4.6 Instruct or Llama 4 Maverick Chat?
Llama 4 Maverick Chat is cheaper on a blended 3:1 basis at about $9.62 per million tokens, versus $9.94 for GLM-4.6 Instruct.
Which has the larger context window?
GLM-4.6 Instruct has the larger context window at 1,000,000 tokens. Llama 4 Maverick Chat has 128,000 tokens.
Are these models open weights?
GLM-4.6 Instruct is open weights; Llama 4 Maverick Chat is open weights.
Which should I choose for production?
If you need a single default, start with GLM-4.6 Instruct for quality-sensitive work and Llama 4 Maverick Chat for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.