Model Comparison
GLM-4.7-Flash (Reasoning)
vs. Qwen3.6 35B A3B (Reasoning)
Comparing 2 AI models · 7 benchmarks · Z AI, Alibaba
Recommended Pick
Al Qwen3.6 35B A3B (Reasoning) 10 metric wins Strongest on: Throughput, Reasoning, Intelligence
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
Qwen3.6 35B A3B (Reasoning)
49.3 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.6 35B A3B (Reasoning)
35.2 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-4.7-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 3.5x cheaper on input tokens than Qwen3.6 35B A3B (Reasoning).
Speed gap
Qwen3.6 35B A3B (Reasoning) generates about 2.2x as many tokens per second as GLM-4.7-Flash (Reasoning).
Reasoning gap
Qwen3.6 35B A3B (Reasoning) leads GLM-4.7-Flash (Reasoning) by 17.5 points on reasoning.
Coding gap
Qwen3.6 35B A3B (Reasoning) leads GLM-4.7-Flash (Reasoning) by 9.3 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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Qwen3.6 35B A3B (Reasoning)
Alibaba
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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Which answer was more useful?
Full Comparison
| Metric | Z GLM-4.7-Flash (Reasoning) | Top Pick Al Qwen3.6 35B A3B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.07/1M | $0.25/1M |
| Output Cost | $0.40/1M | $1.49/1M |
| Blended (3:1) | $0.15/1M | $0.56/1M |
| Specifications | ||
| Organization | Z AI | Alibaba |
| Release Date | Jan 19, 2026 | Apr 16, 2026 |
| Performance & Speed | ||
| Throughput | 76.4 tok/s | 168.2 tok/s |
| TTFT | 994ms | 1351ms |
| Latency | 27179ms | 33420ms |
| Composite Indices | ||
| Value Score | 100.0 | 42.4 |
| Reasoning Score | 31.8 | 49.3 |
| Intelligence | 30.1 | 43.5 |
| Coding | 25.9 | 35.2 |
| Standard Benchmarks | ||
| GPQA | 58.1% | 84.1% |
| HLE | 7.1% | 20.2% |
| SciCode | 33.7% | 35.8% |
| LCR | 35.0% | 63.7% |
| IFBench | 60.8% | 64.4% |
| TAU-bench v2 | 98.8% | 95.3% |
| TerminalBench Hard | 22.0% | 34.8% |
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.
Qwen3.6 35B A3B (Reasoning) has the strongest reasoning profile with a 49.3 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3.6 35B A3B (Reasoning) reaches a 35.2 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
GLM-4.7-Flash (Reasoning)
- Cost-sensitive applications
- High-volume processing
Qwen3.6 35B A3B (Reasoning)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
