| Signal | Qwen3 8B | Delta | GLM 4.5V |
|---|---|---|---|
Capabilities | 67 | -17 | |
Benchmarks | 60 | -1 | |
Pricing | 100 | +1 | |
Context window size | 73 | +4 | |
Recency | 56 | -19 | |
Output Capacity | 65 | -5 | |
| Overall Result | 2 wins | of 6 | 4 wins |
Score History
60.6
current score
GLM 4.5V
right now
62
current score
Alibaba
Zhipu AI
Qwen3 8B saves you $125.00/month
That's $1500.00/year compared to GLM 4.5V at your current usage level of 100K calls/month.
| Metric | Qwen3 8B | GLM 4.5V | Winner |
|---|---|---|---|
| Overall Score | 61 | 62 | GLM 4.5V |
| Rank | #137 | #136 | GLM 4.5V |
| Quality Rank | #137 | #136 | GLM 4.5V |
| Adoption Rank | #137 | #136 | GLM 4.5V |
| Parameters | 8B | -- | -- |
| Context Window | 131K | 66K | Qwen3 8B |
| Pricing | $0.05/$0.40/M | $0.60/$1.80/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 83 | GLM 4.5V |
| Benchmarks | 60 | 60 | GLM 4.5V |
| Pricing | 100 | 98 | Qwen3 8B |
| Context window size | 73 | 69 | Qwen3 8B |
| Recency | 56 | 75 | GLM 4.5V |
| Output Capacity | 65 | 70 | GLM 4.5V |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 61/100 (rank #137), placing it in the top 53% of all 290 models tracked.
Scores 62/100 (rank #136), placing it in the top 53% of all 290 models tracked.
With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Qwen3 8B offers 81% better value per quality point. At 1M tokens/day, you'd spend $6.75/month with Qwen3 8B vs $36.00/month with GLM 4.5V - a $29.25 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Qwen3 8B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.40/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (62/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Qwen3 8B and GLM 4.5V are extremely close in overall performance (only 1.3999999999999986 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Qwen3 8B
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 8B
81% lower pricing; better value at scale
Best for Reliability
Qwen3 8B
Higher uptime and faster response speeds
Best for Prototyping
Qwen3 8B
Stronger community support and better developer experience
Best for Production
Qwen3 8B
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen3 8B | GLM 4.5V |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Zhipu AI
Qwen3 8B saves you $2.67/month
That's 82% cheaper than GLM 4.5V at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Qwen3 8B | GLM 4.5V |
|---|---|---|
| Context Window | 131K | 66K |
| Max Output Tokens | 8,192 | 16,384 |
| Open Source | Yes | Yes |
| Created | Apr 28, 2025 | Aug 11, 2025 |