Model Comparison
R1 (Jan '25)
vs. GLM-4.6 (Non-reasoning)
Comparing 2 AI models · 12 benchmarks · DeepSeek, Z AI
Recommended Pick
De R1 (Jan '25) 12 metric wins Strongest on: TTFT, Latency, Reasoning
Best Value
GLM-4.6 (Non-reasoning)
100.0 value score
37.4 reasoning / $1.00/1M
Lowest Price
GLM-4.6 (Non-reasoning)
$0.60/1M input price
Best Reasoning
R1 (Jan '25)
57.1 reasoning score
Blends available reasoning benchmarks
Best for Coding
GLM-4.6 (Non-reasoning)
30.2 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-4.6 (Non-reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
GLM-4.6 (Non-reasoning) is 2.8x cheaper on input tokens than R1 (Jan '25).
Reasoning gap
R1 (Jan '25) leads GLM-4.6 (Non-reasoning) by 19.7 points on reasoning.
Coding gap
GLM-4.6 (Non-reasoning) leads R1 (Jan '25) by 14.3 points on coding.
Top-pick rationale
R1 (Jan '25) wins 12 measurable categories, including TTFT, Latency, Reasoning, Math.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
R1 (Jan '25)
DeepSeek
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
GLM-4.6 (Non-reasoning)
Z AI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick De R1 (Jan '25) | Z GLM-4.6 (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $1.68/1M | $0.60/1M |
| Output Cost | $4.70/1M | $2.20/1M |
| Blended (3:1) | $2.43/1M | $1.00/1M |
| Specifications | ||
| Organization | DeepSeek | Z AI |
| Release Date | Jan 20, 2025 | Sep 30, 2025 |
| Performance & Speed | ||
| Throughput | — | 60.4 tok/s |
| TTFT | — | 1606ms |
| Latency | — | 1606ms |
| Composite Indices | ||
| Value Score | 62.7 | 100.0 |
| Reasoning Score | 57.1 | 37.4 |
| Intelligence | 18.8 | 30.2 |
| Coding | 15.9 | 30.2 |
| Math | 68.0 | 44.3 |
| Standard Benchmarks | ||
| GPQA | 70.8% | 63.2% |
| MMLU Pro | 84.4% | 78.4% |
| HLE | 9.3% | 5.2% |
| LiveCodeBench | 61.7% | 56.1% |
| MATH 500 | 96.6% | — |
| AIME 2025 | 68.0% | 44.3% |
| AIME (Original) | 68.3% | — |
| SciCode | 35.7% | 33.1% |
| LCR | 52.3% | 26.3% |
| IFBench | 39.0% | 36.7% |
| TAU-bench v2 | 11.4% | 76.9% |
| TerminalBench Hard | 6.1% | 28.8% |
Key Takeaways
GLM-4.6 (Non-reasoning) offers the best value at $0.60/1M, making it ideal for high-volume applications and cost-conscious projects.
R1 (Jan '25) has the strongest reasoning profile with a 57.1 reasoning score, combining the available reasoning-heavy benchmarks.
GLM-4.6 (Non-reasoning) reaches a 30.2 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
R1 (Jan '25)
- Complex reasoning tasks
- Research & analysis
GLM-4.6 (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
- Code generation
- Software development
