Model Comparison
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
vs. GLM-5.2 (max)
Comparing 2 AI models · 7 benchmarks · Anthropic, Z AI
Recommended Pick
An Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) 9 metric wins Strongest on: TTFT, Latency, Reasoning
Best Value
GLM-5.2 (max)
100.0 value score
60.1 reasoning / $2.15/1M
Lowest Price
GLM-5.2 (max)
$1.40/1M input price
Best Reasoning
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
68.6 reasoning score
Blends available reasoning benchmarks
Best for Coding
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
62.0 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-5.2 (max) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
GLM-5.2 (max) is 7.1x cheaper on input tokens than Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback).
Reasoning gap
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) leads GLM-5.2 (max) by 8.5 points on reasoning.
Coding gap
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) leads GLM-5.2 (max) by 11.3 points on coding.
Top-pick rationale
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) wins 9 measurable categories, including TTFT, Latency, Reasoning, Intelligence.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
Anthropic
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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GLM-5.2 (max)
Z AI
TTFT
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Time
—
tok/s
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Tokens
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Cost
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Which answer was more useful?
Full Comparison
| Metric | Top Pick An Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) | Z GLM-5.2 (max) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $10.00/1M | $1.40/1M |
| Output Cost | $50.00/1M | $4.40/1M |
| Blended (3:1) | $20.00/1M | $2.15/1M |
| Specifications | ||
| Organization | Anthropic | Z AI |
| Release Date | Jun 9, 2026 | Jun 16, 2026 |
| Performance & Speed | ||
| Throughput | — | 114.2 tok/s |
| TTFT | — | 2085ms |
| Latency | — | 19604ms |
| Composite Indices | ||
| Value Score | 12.3 | 100.0 |
| Reasoning Score | 68.6 | 60.1 |
| Intelligence | 59.9 | 50.7 |
| Coding | 62.0 | 50.7 |
| Standard Benchmarks | ||
| GPQA | 92.6% | 89.5% |
| HLE | 53.3% | 40.1% |
| SciCode | 60.2% | 50.5% |
| LCR | 70.0% | 71.3% |
| IFBench | 63.5% | 73.3% |
| TAU-bench v2 | 98.5% | 99.1% |
| TerminalBench Hard | 62.9% | 50.8% |
Key Takeaways
GLM-5.2 (max) offers the best value at $1.40/1M, making it ideal for high-volume applications and cost-conscious projects.
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) has the strongest reasoning profile with a 68.6 reasoning score, combining the available reasoning-heavy benchmarks.
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) reaches a 62.0 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
Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
GLM-5.2 (max)
- Cost-sensitive applications
- High-volume processing
