| Signal | Llama 4 Maverick | Delta | GLM 4.6 |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 70 | 0 | |
Pricing | 99 | +1 | |
Context window size | 96 | +11 | |
Recency | 67 | -32 | |
Output Capacity | 70 | -18 | |
| Overall Result | 2 wins | of 6 | 3 wins |
Score History
71.1
current score
Llama 4 Maverick
right now
70.7
current score
Meta
Zhipu AI
Llama 4 Maverick saves you $89.00/month
That's $1068.00/year compared to GLM 4.6 at your current usage level of 100K calls/month.
| Metric | Llama 4 Maverick | GLM 4.6 | Winner |
|---|---|---|---|
| Overall Score | 71 | 71 | Llama 4 Maverick |
| Rank | #53 | #54 | Llama 4 Maverick |
| Quality Rank | #53 | #54 | Llama 4 Maverick |
| Adoption Rank | #53 | #54 | Llama 4 Maverick |
| Parameters | -- | -- | -- |
| Context Window | 1049K | 205K | Llama 4 Maverick |
| Pricing | $0.15/$0.60/M | $0.39/$1.90/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Llama 4 Maverick |
| Benchmarks | 70 | 70 | GLM 4.6 |
| Pricing | 99 | 98 | Llama 4 Maverick |
| Context window size | 96 | 84 | Llama 4 Maverick |
| Recency | 67 | 99 | GLM 4.6 |
| Output Capacity | 70 | 89 | GLM 4.6 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 71/100 (rank #53), placing it in the top 82% of all 290 models tracked.
Scores 71/100 (rank #54), placing it in the top 82% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Llama 4 Maverick offers 67% better value per quality point. At 1M tokens/day, you'd spend $11.25/month with Llama 4 Maverick vs $34.35/month with GLM 4.6 - a $23.10 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Llama 4 Maverick also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.60/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (71/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Llama 4 Maverick and GLM 4.6 are extremely close in overall performance (only 0.3999999999999915 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Llama 4 Maverick
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 4 Maverick
67% lower pricing; better value at scale
Best for Reliability
Llama 4 Maverick
Higher uptime and faster response speeds
Best for Prototyping
Llama 4 Maverick
Stronger community support and better developer experience
Best for Production
Llama 4 Maverick
Wider enterprise adoption and proven at scale
by Meta
| Capability | Llama 4 Maverick | GLM 4.6 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
Zhipu AI
Llama 4 Maverick saves you $1.99/month
That's 67% cheaper than GLM 4.6 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Llama 4 Maverick | GLM 4.6 |
|---|---|---|
| Context Window | 1.0M | 205K |
| Max Output Tokens | 16,384 | 204,800 |
| Open Source | Yes | Yes |
| Created | Apr 5, 2025 | Sep 30, 2025 |
Llama 4 Maverick scores 71/100 (rank #53) compared to GLM 4.6's 71/100 (rank #54), giving it a 0-point advantage. Llama 4 Maverick is the stronger overall choice, though GLM 4.6 may excel in specific areas like certain benchmarks.
Llama 4 Maverick is ranked #53 and GLM 4.6 is ranked #54 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Llama 4 Maverick is cheaper at $0.60/M output tokens vs GLM 4.6's $1.90/M output tokens - 3.2x more expensive. Input token pricing: Llama 4 Maverick at $0.15/M vs GLM 4.6 at $0.39/M.
Llama 4 Maverick has a larger context window of 1,048,576 tokens compared to GLM 4.6's 204,800 tokens. A larger context window means the model can process longer documents and conversations.