GLM 4.6 vs Qwen3 30B A3B Thinking
Detailed comparison between GLM 4.6 and Qwen3 30B A3B Thinking for RAG applications. See which LLM best meets your accuracy, performance, and cost needs.
Model Comparison
GLM 4.6 takes the lead.
Both GLM 4.6 and Qwen3 30B A3B Thinking are powerful language models designed for RAG applications. However, their performance characteristics differ in important ways.
Why GLM 4.6:
- GLM 4.6 has 158 higher ELO rating
- GLM 4.6 has a 10.9% higher win rate
Overview
Key metrics
ELO Rating
Overall ranking quality
GLM 4.6
Qwen3 30B A3B Thinking
Win Rate
Head-to-head performance
GLM 4.6
Qwen3 30B A3B Thinking
Quality Score
Overall quality metric
GLM 4.6
Qwen3 30B A3B Thinking
Average Latency
Response time
GLM 4.6
Qwen3 30B A3B Thinking
Visual Performance Analysis
Performance
ELO Rating Comparison
Win/Loss/Tie Breakdown
Quality Across Datasets (Overall Score)
Latency Distribution (ms)
Breakdown
How the models stack up
| Metric | GLM 4.6 | Qwen3 30B A3B Thinking | Description |
|---|---|---|---|
| Overall Performance | |||
| ELO Rating | 1489 | 1331 | Overall ranking quality based on pairwise comparisons |
| Win Rate | 42.7% | 31.9% | Percentage of comparisons won against other models |
| Quality Score | 4.81 | 4.90 | Average quality across all RAG metrics |
| Pricing & Context | |||
| Input Price per 1M | $0.40 | $0.05 | Cost per million input tokens |
| Output Price per 1M | $1.75 | $0.34 | Cost per million output tokens |
| Context Window | 203K | 33K | Maximum context window size |
| Release Date | 2025-09-30 | 2025-08-28 | Model release date |
| Performance Metrics | |||
| Avg Latency | 33.1s | 12.3s | Average response time across all datasets |
Dataset Performance
By benchmark
Comprehensive comparison of RAG quality metrics (correctness, faithfulness, grounding, relevance, completeness) and latency for each benchmark dataset.
MSMARCO
| Metric | GLM 4.6 | Qwen3 30B A3B Thinking | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.80 | 4.90 | Factual accuracy of responses |
| Faithfulness | 4.77 | 4.90 | Adherence to source material |
| Grounding | 4.77 | 4.90 | Citations and context usage |
| Relevance | 4.83 | 5.00 | Query alignment and focus |
| Completeness | 4.70 | 4.80 | Coverage of all aspects |
| Overall | 4.77 | 4.90 | Average across all metrics |
| Latency Metrics | |||
| Mean | 34694ms | 12522ms | Average response time |
| Min | 9198ms | 1541ms | Fastest response time |
| Max | 69527ms | 49799ms | Slowest response time |
PG
| Metric | GLM 4.6 | Qwen3 30B A3B Thinking | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.87 | 4.90 | Factual accuracy of responses |
| Faithfulness | 4.87 | 4.87 | Adherence to source material |
| Grounding | 4.83 | 4.87 | Citations and context usage |
| Relevance | 4.90 | 4.93 | Query alignment and focus |
| Completeness | 4.57 | 4.77 | Coverage of all aspects |
| Overall | 4.81 | 4.87 | Average across all metrics |
| Latency Metrics | |||
| Mean | 36774ms | 16030ms | Average response time |
| Min | 9584ms | 3483ms | Fastest response time |
| Max | 104257ms | 44237ms | Slowest response time |
SciFact
| Metric | GLM 4.6 | Qwen3 30B A3B Thinking | Description |
|---|---|---|---|
| Quality Metrics | |||
| Correctness | 4.63 | 4.97 | Factual accuracy of responses |
| Faithfulness | 4.87 | 4.97 | Adherence to source material |
| Grounding | 4.87 | 4.93 | Citations and context usage |
| Relevance | 4.90 | 5.00 | Query alignment and focus |
| Completeness | 4.57 | 4.83 | Coverage of all aspects |
| Overall | 4.77 | 4.94 | Average across all metrics |
| Latency Metrics | |||
| Mean | 27880ms | 8384ms | Average response time |
| Min | 3248ms | 2185ms | Fastest response time |
| Max | 68513ms | 19414ms | Slowest response time |
Explore More
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