Model Comparison
GLM-4.7-Flash (Reasoning)
vs. Llama 4 Scout
Comparing 2 AI models · 12 benchmarks · Z AI, Meta
Recommended Pick
Z GLM-4.7-Flash (Reasoning) 13 metric wins Strongest on: Value, Input price, Output price
Best Value
GLM-4.7-Flash (Reasoning)
100.0 value score
31.8 reasoning / $0.15/1M
Lowest Price
GLM-4.7-Flash (Reasoning)
$0.07/1M input price
Best Reasoning
GLM-4.7-Flash (Reasoning)
31.8 reasoning score
Blends available reasoning benchmarks
Best for Coding
GLM-4.7-Flash (Reasoning)
25.9 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
GLM-4.7-Flash (Reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
GLM-4.7-Flash (Reasoning) is 2.4x cheaper on input tokens than Llama 4 Scout.
Speed gap
Llama 4 Scout generates about 1.4x as many tokens per second as GLM-4.7-Flash (Reasoning).
Reasoning gap
GLM-4.7-Flash (Reasoning) leads Llama 4 Scout by 0.7 points on reasoning.
Coding gap
GLM-4.7-Flash (Reasoning) leads Llama 4 Scout by 19.2 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
GLM-4.7-Flash (Reasoning)
Z AI
TTFT
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Time
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tok/s
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Tokens
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Cost
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Llama 4 Scout
Meta
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick Z GLM-4.7-Flash (Reasoning) | Me Llama 4 Scout |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.07/1M | $0.17/1M |
| Output Cost | $0.40/1M | $0.66/1M |
| Blended (3:1) | $0.15/1M | $0.29/1M |
| Specifications | ||
| Organization | Z AI | Meta |
| Release Date | Jan 19, 2026 | Apr 5, 2025 |
| Performance & Speed | ||
| Throughput | 80.6 tok/s | 112.5 tok/s |
| TTFT | 998ms | 624ms |
| Latency | 25822ms | 624ms |
| Composite Indices | ||
| Value Score | 100.0 | 50.9 |
| Reasoning Score | 31.8 | 31.0 |
| Intelligence | 30.1 | 13.5 |
| Coding | 25.9 | 6.7 |
| Math | — | 14.0 |
| Standard Benchmarks | ||
| GPQA | 58.1% | 58.7% |
| MMLU Pro | — | 75.2% |
| HLE | 7.1% | 4.3% |
| LiveCodeBench | — | 29.9% |
| MATH 500 | — | 84.4% |
| AIME 2025 | — | 14.0% |
| AIME (Original) | — | 28.3% |
| SciCode | 33.7% | 17.0% |
| LCR | 35.0% | 25.8% |
| IFBench | 60.8% | 39.5% |
| TAU-bench v2 | 98.8% | 15.5% |
| TerminalBench Hard | 22.0% | 1.5% |
Key Takeaways
GLM-4.7-Flash (Reasoning) offers the best value at $0.07/1M, making it ideal for high-volume applications and cost-conscious projects.
GLM-4.7-Flash (Reasoning) has the strongest reasoning profile with a 31.8 reasoning score, combining the available reasoning-heavy benchmarks.
GLM-4.7-Flash (Reasoning) reaches a 25.9 coding index, making it the top choice for software development and code generation tasks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
GLM-4.7-Flash (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Llama 4 Scout
- General-purpose AI
- Versatile applications
